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The coronavirus disease 2019 (COVID-19) pandemic has clearly shown that major challenges and threats for humankind need to be addressed with global answers and shared decisions. Data and their analytics are crucial components of such decision-making activities. Rather interestingly, one of the most difficult aspects is reusing and sharing of accurate and detailed clinical data collected by Electronic Health Records (EHR), even if these data have a paramount importance. EHR data, in fact, are not only essential for supporting day-by-day activities, but also they can leverage research and support critical decisions about effectiveness of drugs and therapeutic strategies. In this paper, we will concentrate our attention on collaborative data infrastructures to support COVID-19 research and on the open issues of data sharing and data governance that COVID-19 had made emerge. Data interoperability, healthcare processes modelling and representation, shared procedures to deal with different data privacy regulations, and data stewardship and governance are seen as the most important aspects to boost collaborative research. Lessons learned from COVID-19 pandemic can be a strong element to improve international research and our future capability of dealing with fast developing emergencies and needs, which are likely to be more frequent in the future in our connected and intertwined world.

Background: High-flow nasal oxygen (HFNO) improves exercise capacity, oxygen saturation, and symptoms in patients with chronic obstructive pulmonary disease (COPD). Due to the need of electricity supply, HFNO has not been applied during free ambulation. Objective: We evaluated whether HFNO delivered during walking by a battery-supplied portable device was more effective than usual portable oxygen in improving exercise capacity in patients with COPD and severe exercise limitation. The effects on 6-min walking tests (6MWTs) were the primary outcome. Methods: After a baseline 6MWT, 20 stable patients requiring an oxygen inspiratory fraction (FiO2) 2. Walked distance, perceived dyspnea, pulse oximetry, and inspiratory capacity at end of the tests as well as patients’ comfort were compared between the tests. Results: As compared to baseline, walked distance improved significantly more in HFNO than in the control test (by 61.1 ± 37.8 and 39.7 ± 43.8 m, respectively, p = 0.01). There were no significant differences between the tests in dyspnea, peripheral oxygen saturation, or inspiratory capacity, but HFNO test was appreciated as more comfortable. Conclusion: In patients with COPD and severe exercise limitation, HFNO delivered by a battery-supplied portable device was more effective in improving walking distance than usual oxygen supplementation.

AIMS To study the predictive factors for the development of clinical manifestations in poisoning due to the erroneous taking of low-dose methotrexate (MTX). METHODS A retrospective observational study was performed. Only cases of erroneous administration in non-oncologic outpatients were included (July 2008-March 2020). RESULTS Forty-one cases were included. All patients were taking MTX for the first time. In 36 cases, patients took MTX daily instead of weekly. In the other five patients, MTX was sold instead of methylergometrine. Clinical manifestations were absent in 12/41 patients (29.3%). All 29 (70.7%) symptomatic patients recognized the medication error when they developed clinical manifestations: dermatological, haematological and gastrointestinal symptoms. Statistical results showed that symptomatic patients were older, received a higher amount of total dose and were treated for longer. Moreover, the probability of being symptomatic increases as a function of age and of total dose. Asymptomatic patients were treated with folinic acid (30 mg/m2 /day) for 5 days. Symptomatic patients were treated with folinic acid together with treatments for the specific clinical manifestations. No patients were treated with glucarpidase. All patients fully recovered. CONCLUSIONS When MTX is prescribed for the first time, it is important to clearly communicate with patients to avoid therapeutic errors. In our experience, age, total dose taken and number of days of assumption are predictive for the presence/absence of clinical manifestations. These parameters must be evaluated together to identify patients needing maximum starting treatment with folinic acid and closer monitoring.

Background The Barthel Index dyspnea (BId) is responsive to physiological changes and pulmonary rehabilitation in patients with chronic obstructive pulmonary disease (COPD). However, the minimum clinically important difference (MCID) has not been established yet. Aim To identify the MCID of BId in patients with COPD stratified according to the presence of chronic respiratory failure (CRF) or not. Materials and Methods Using the Medical Research Council (MRC) score as an anchor, receiver operating characteristic curves and quantile regression were retrospectively evaluated before and after pulmonary rehabilitation in 2327 patients with COPD (1151 of them with CRF). Results The median post-rehabilitation changes in BId for all patients were -10 (interquartile range = -17 to -3, p

STUDY OBJECTIVES: There are few studies evaluating (1) exercise capacity as assessed by the 6-minute walking distance (6MWD) test in large populations with obstructive sleep apnea (OSA); and (2) correlations with patients’ comorbidities. METHODS: This study presents a cluster analysis performed on the data of 1,228 patients. Severity of exercise limitation was defined on the basis of 6MWD. RESULTS: Sixty-one percent showed exercise limitation (29.2% and 31.9% mild and severe exercise limitation, respectively). About 60% and 40% of patients were included in cluster 1 (CL1) and 2 (CL2), respectively. CL1 included younger patients with high prevalence of apneas, desaturations, and hypertension with better exercise tolerance. CL2 included older patients, all with chronic obstructive pulmonary disease (COPD), high prevalence of chronic respiratory failure (CRF), fewer apneas but severe mean desaturation, daytime hypoxemia, more severe exercise limitation, and exercise-induced desaturations. Only CRF and COPD significantly (P < .001) correlated with 6MWD < 85% of predicted value. 6MWD correlated positively with apnea-hypopnea index, oxygen desaturation index, nocturnal pulse oxygen saturation (SpO(2)), resting arterial oxygen tension, mean SpO(2) on exercise, and negatively with age, body mass index, time spent during night with SpO(2) < 90%, mean nocturnal desaturation, arterial carbon dioxide tension, and number of comorbidities. Patients without severe comorbidities had higher exercise capacity than those with severe comorbidities, (P < .001). Exercise limitation was significantly worse in OSA severity class I when compared to other classes (P < .001). CONCLUSIONS: A large number of patients with OSA experience exercise limitation. Older age, comorbidities such as COPD and CRF, OSA severity class I, severe mean nocturnal desaturation, and daytime hypoxemia are associated with worse exercise tolerance. CITATION: Vitacca M, Paneroni M, Braghiroli A, et al. Exercise capacity and comorbidities in patients with obstructive sleep apnea. J Clin Sleep Med. 2020;16(4):531–538.

BACKGROUND: Patients undergoing prolonged mechanical ventilation represent up to 15% of all patients requiring weaning from mechanical ventilation. Although recent guidelines have recommended including physiotherapy early during mechanical ventilation to speed the process of weaning, only indirect evidence supporting the use of physiotherapy is available for patients receiving prolonged mechanical ventilation. The aim of our study was to evaluate the effects of a physiotherapy program in subjects requiring prolonged mechanical ventilation and the correlates of successful weaning. METHODS: A retrospective analysis was performed on 1,313 consecutive patients admitted to a weaning unit over a 15-y period to be liberated from prolonged mechanical ventilation. Subjects underwent a program of intensive physiotherapy organized in 4 incremental steps (1–4) and were analyzed according to the steps achieved (> 2 steps or ≤ 2 steps). The rate of successful weaning was recorded, and possible predictors were considered. The 15-y period of observation was divided into 3 consecutive 5-y intervals. RESULTS: Out of 560 subjects undergoing final analysis, 349 (62.3%) were successfully weaned. The weaning success rate was significantly greater in subjects attaining > 2 steps than in subjects who attained ≤ 2 steps (72.1% vs 55.9%, respectively, odds ratio = 2.04, 95% CI = 1.42–2.96, P 2 physiotherapy steps was the main predictor of successful weaning (odds ratio = 2.17, 95% CI = 1.48–3.23, P

Background For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been grueling with lingering effects. Many of the symptoms characterized as the post-acute sequelae of COVID-19 (PASC) could have multiple causes or are similarly seen in non-COVID patients. Accurate identification of PASC phenotypes will be important to guide future research and help the healthcare system focus its efforts and resources on adequately controlled age- and gender-specific sequelae of a COVID-19 infection. Methods In this retrospective electronic health record (EHR) cohort study, we applied a computational framework for knowledge discovery from clinical data, MLHO, to identify phenotypes that positively associate with a past positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19. We evaluated the post-test phenotypes in two temporal windows at 3–6 and 6–9 months after the test and by age and gender. Data from longitudinal diagnosis records stored in EHRs from Mass General Brigham in the Boston Metropolitan Area was used for the analyses. Statistical analyses were performed on data from March 2020 to June 2021. Study participants included over 96 thousand patients who had tested positive or negative for COVID-19 and were not hospitalized. Results We identified 33 phenotypes among different age/gender cohorts or time windows that were positively associated with past SARS-CoV-2 infection. All identified phenotypes were newly recorded in patients’ medical records 2 months or longer after a COVID-19 RT-PCR test in non-hospitalized patients regardless of the test result. Among these phenotypes, a new diagnosis record for anosmia and dysgeusia (OR 2.60, 95% CI [1.94–3.46]), alopecia (OR 3.09, 95% CI [2.53–3.76]), chest pain (OR 1.27, 95% CI [1.09–1.48]), chronic fatigue syndrome (OR 2.60, 95% CI [1.22–2.10]), shortness of breath (OR 1.41, 95% CI [1.22–1.64]), pneumonia (OR 1.66, 95% CI [1.28–2.16]), and type 2 diabetes mellitus (OR 1.41, 95% CI [1.22–1.64]) is one of the most significant indicators of a past COVID-19 infection. Additionally, more new phenotypes were found with increased confidence among the cohorts who were younger than 65. Conclusions The findings of this study confirm many of the post-COVID-19 symptoms and suggest that a variety of new diagnoses, including new diabetes mellitus and neurological disorder diagnoses, are more common among those with a history of COVID-19 than those without the infection. Additionally, more than 63% of PASC phenotypes were observed in patients under 65 years of age, pointing out the importance of vaccination to minimize the risk of debilitating post-acute sequelae of COVID-19 among younger adults.

Many countries have experienced 2 predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic.In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic.Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19.Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain.Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.

Made available in DSpace on 2022-04-29T08:35:59Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-12-01 Division of Intramural Research, National Institute of Allergy and Infectious Diseases Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases National Institute of Allergy and Infectious Diseases National Center for Advancing Translational Sciences National Heart, Lung, and Blood Institute National Institute of Environmental Health Sciences U.S. National Library of Medicine National Institute of Neurological Disorders and Stroke Division of Cancer Prevention, National Cancer Institute Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19–25%), cerebrovascular diseases (24%, 13–35%), nontraumatic intracranial hemorrhage (34%, 20–50%), encephalitis and/or myelitis (37%, 17–60%) and myopathy (72%, 67–77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease. Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Department of Biomedical Informatics Harvard Medical School Department of Neurology University of Pittsburgh, Biomedical Science Tower 3, Suite 7014, 3501 5th Avenue Department of Pediatrics Wake Forest School of Medicine Department of Critical Care National University Health Systems Department of Preventive Medicine Northwestern University Department of Biomedical Informatics University of Pittsburgh Department of Surgery National University Health Systems Department of Internal Medicine University of Kansas Medical Center Data Analytics Center University of Pennsylvania Health System Department of Computational Medicine and Bioinformatics University of Michigan Department of Biomedical Informatics University of Kentucky Department of Legal Economic and Social Sciences University Magna Graecia of Catanzaro Health Catalyst INC. Department of Surgery ASST Pavia Lombardia Region Health System Clinical Research Unit of Botucatu Medical School São Paulo State University Pediatric Emergency Department Hôpital Necker-Enfants Malades Assistance Publique-Hôpitaux de Paris National Center for Infectious Diseases Tan Tock Seng Hospital Departments of Biomedical Informatics Pediatrics Cincinnati Children’s Hospital Medical Center University of Cincinnati Department of Pediatrics Medical University of South Carolina Department of Surgery St. Luke’s University Health Network Department of Medicine David Geffen School of Medicine at UCLA UOC Ricerca Innovazione e Brand Reputation ASST Papa Giovanni XXIII Department of Electrical Computer and Biomedical Engineering University of Pavia IT Department Innovation & Data APHP Greater Paris University Hospital I.T. Department ASST Pavia Health Informatics Hospital Universitario, 12 de Octubre Strategy and Transformation Department APHP Greater Paris University Hospital Faculty of Medicine and Medical Center University of Freiburg Digital Research Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children Scientific Direction IRCCS Ca’ Granda Ospedale Maggiore Policlinico di Milano North Carolina Translational and Clinical Sciences (NC TraCS) Institute University of North Carolina BIOMERIS (BIOMedical Research Informatics Solutions) Department of Biomedical Informatics HEGP APHP Greater Paris University Hospital Department of Medical and Surgical Sciences Data Analytics Research Center University Magna Graecia of Catanzaro Department of Anesthesia St. Luke’s University Health Network Université Paris-Saclay Inria CEA INRIA Sophia-Antipolis–ZENITH Team LIRMM Computational Health Informatics Program Boston Children’s Hospital Department of Internal Medicine University of Kentucky Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Department of Internal Medicine and Therapeutics University of Pavia Informatics Institute University of Alabama at Birmingham IAM Unit Bordeaux University Hospital/ERIAS-Inserm U1219 BPH Biomedical Informatics Center Medical University of South Carolina Clinical Research Informatics Boston Children’s Hospital Department of Biomedical and Health Informatics Children’s Hospital of Philadelphia SED/SIERRA Inria Centre de Paris Health Information Technology & Services University of Michigan Internal Medicine Department Botucatu Medical School São Paulo State University Heinrich-Lanz-Center for Digital Health University Medicine Mannheim Heidelberg University Department of Anesthesiology Critical Care and Pain Medicine Boston Children’s Hospital Department of Learning Health Sciences University of Michigan Medical School MSHI Medical University of South Carolina Department of Medicine Massachusetts General Hospital Division of Human Genetics Department of Pediatrics The Children’s Hospital of Philadelphia Center for Medical Information and Communication Technology University Hospital Renaissance Computing Institute/Department of Computer Science University of North Carolina Clinical Research Unit Saint Antoine Hospital APHP Greater Paris University Hospital Clevy.io Department of Biostatistics Harvard T.H. Chan School of Public Health VA Informatics and Computing Infrastructure VA Salt Lake City Health Care System MICHR Informatics University of Michigan Laboratory of Informatics and Systems Engineering for Clinical Research Istituti Clinici Scientifici Maugeri SpA SB IRCCS Harvard Catalyst Harvard Medical School Clinical Research Unit Paris Saclay APHP Greater Paris University Hospital Department of Anesthesiology and Critical Care Children’s Hospital of Philadelphia VA Informatics and Computing Infrastructure Tennessee Valley Healthcare System Veterans Affairs Medical Center École Normale Supérieure PSL Université Paris BIG-ARC The University of Texas Health Science Center at Houston School of Biomedical Informatics Pediatric Infectious Disease Department Hospital Universitario, 12 de Octubre Department of Infectious Diseases Great Ormond Street Hospital for Children Department of Neurology Massachusetts General Hospital Internal Medicine Department of Botucatu Medical School São Paulo State University Department of Pediatrics Boston Children’s Hospital Center for Biomedical Informatics Wake Forest School of Medicine Department of Medical Informatics University of Erlangen-Nürnberg Department of Veterans Affairs Office of Research and Development Biomedical Data Science Lab ITACA Institute Universitat Politècnica de València Nurse Department of FMB-Medicine School of Botucatu Management Engineering ASST Pavia Lombardia Region Health System Department of Anesthesiology University Hospital Erlangen FAU Erlangen-Nürnberg Critical Care Medicine Department of Medicine St. Luke’s University Health Network Department of Medicine National University Hospital Department of Information Management Chang Gung University Clinical & Translational Science Institute Medical College of Wisconsin Montréal Neurological Institute McGill University SequeL Inria Lille Respiratory Department ICS S Maugeri IRCCS Department of Health Management and Informatics University of Missouri Department of Oncology ASST Papa Giovanni XXIII Clinical Research Unit of Botucatu Medical School São Paulo State University Internal Medicine Department Botucatu Medical School São Paulo State University Internal Medicine Department of Botucatu Medical School São Paulo State University Division of Intramural Research, National Institute of Allergy and Infectious Diseases: AI11679 Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases: AI11679 National Institute of Allergy and Infectious Diseases: AI11679 National Center for Advancing Translational Sciences: CTSA Award #UL1TR001878 National Center for Advancing Translational Sciences: CTSA Award #UL1TR002366 National Heart, Lung, and Blood Institute: K23HL148394 National Institute of Environmental Health Sciences: P30ES017885 U.S. National Library of Medicine: R01LM012095 National Institute of Neurological Disorders and Stroke: R01NS098023 Division of Cancer Prevention, National Cancer Institute: U24CA210967 National Center for Advancing Translational Sciences: UL1TR001420 National Center for Advancing Translational Sciences: UL1TR001857

The aim of the study was the objective assessment of the effectiveness of a microfragmented dermal extract obtained with Rigenera™ technology in promoting the wound healing process in an in vivo homogeneous experimental human acute surgical wound model. The study included 20 patients with 24 acute postsurgical soft tissue loss and a planned sequential two-stage repair with a dermal substitute and an autologous split-thickness skin graft. Each acute postsurgical soft tissue loss was randomized to be treated either with an Integra® dermal substitute enriched with the autologous dermal micrografts obtained with Rigenera™ technology (group A—Rigenera™ protocol) or with an Integra® dermal substitute only (group B—control). The reepithelialization rate in the wounds was assessed in both groups at 4 weeks through digital photography with the software “ImageJ.” The dermal cell suspension enrichment with the Rigenera™ technology was considered effective if the reepithelialized area was higher than 25% of the total wound surface as this threshold was considered far beyond the expected spontaneous reepithelialization rate. In the Rigenera™ protocol group, the statistical analysis failed to demonstrate any significant difference vs. the controls. The old age of the patients likely influenced the outcome as the stem cell regenerative potential is reduced in the elderly. A further explanation for the unsatisfying results of our trial might be the inadequate amount of dermal stem cells used to enrich the dermal substitutes. In our study, we used a 1 : 200 donor/recipient site ratio to minimize donor site morbidity. The gross dimensional disparity between the donor and recipient sites and the low concentration of dermal mesenchymal stromal stem cells might explain the poor epithelial proliferative boost observed in our study. A potential option in the future might be preconditioning of the dermal stem cell harvest with senolytic active principles that would fully enhance their regenerative potential. This trial is registered with trial protocol number NCT03912675.

Background Persistence of breathlessness after recovery from SARS-CoV-2 pneumonia is frequent. Recovery from acute respiratory failure (ARF) is usually determined by normalized arterial blood gases (ABGs), but the prevalence of persistent exercise-induced desaturation (EID) and dyspnea is still unknown. Methods We investigated the prevalence of EID in 70 patients with normal arterial oxygen at rest after recovery from ARF due to COVID-19 pneumonia. Patients underwent a 6-min walking test (6MWT) before discharge from hospital. We recorded dyspnea score and heart rate during 6MWT. We also investigated the possible role of lung ultrasound (LU) in predicting EID. Patients underwent a LU scan and scores for each explored area were summed to give a total LU score. Results In 30 patients (43%), oxygen desaturation was >4% during 6MWT. These patients had significantly higher dyspnea and heart rate compared to non-desaturators. LU score >8.5 was significantly able to discriminate patients with EID. Conclusion In SARS-CoV-2 pneumonia, ABGs at discharge cannot predict the persistence of EID, which is frequent. LU may be useful to identify patients at risk who could benefit from a rehabilitation program.

This cohort study aims to describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19., Key Points Question What are international trends in hospitalizations for children and youth with SARS-CoV-2, and what are the epidemiological and clinical features of these patients? Findings This cohort study of 671 children and youth found discrete surges in hospitalizations with variable trends and timing across countries. Common complications included cardiac arrhythmias and viral pneumonia, and laboratory findings included elevations in markers of inflammation and abnormalities of coagulation; few children and youth were treated with medications directed specifically at SARS-CoV-2. Meaning These findings suggest large-scale informatics-based approaches used to incorporate electronic health record data across health care systems can provide an efficient source of information to monitor disease activity and define epidemiological and clinical features of pediatric patients hospitalized with SARS-CoV-2 infections., Importance Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients. Objective To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19. Design, Setting, and Participants This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study. Main Outcomes and Measures Patient characteristics, clinical features, and medication use. Results There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study’s cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0- to 2-year (199 patients [30%]) and 12- to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19–directed medications. Conclusions and Relevance This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and identified common complications and laboratory abnormalities in children and youth with COVID-19 infection. Large-scale informatics-based approaches to integrate and analyze data across health care systems complement methods of disease surveillance and advance understanding of epidemiological and clinical features associated with COVID-19 in children and youth.

Background: Currently, evidence-based learning systems to increase knowledge and evidence level of wound care are unavailable to wound care nurses in Denmark, which means that they need to learn about diabetic foot ulcers from experience and peer-to-peer training, or by asking experienced colleagues. Interactive evidence-based learning systems built on case-based reasoning (CBR) have the potential to increase wound care nurses’ diabetic foot ulcer knowledge and evidence levels. Method: A prototype of a CBR-interactive, evidence-based algorithm-operated learning system calculates a dissimilarity score (DS) that gives a quantitative measure of similarity between a new case and cases stored in a case base in relation to six variables: necrosis, wound size, granulation, fibrin, dry skin, and age. Based on the DS, cases are selected by matching the six variables with the best predictive power and by weighing the impact of each variable according to its contribution to the prediction. The cases are ranked, and the six cases with the lowest DS are visualized in the system. Results: Conventional education, that is, evidence-based learning material such as books and lectures, may be less motivating and pedagogical than peer-to-peer training, which is, however, often less evidence-based. The CBR interactive learning systems presented in this study may bridge the two approaches. Showing wound care nurses how individual variables affect outcomes may help them achieve greater insights into pathophysiological processes. Conclusion: A prototype of a CBR-interactive, evidence-based learning system that is centered on diabetic foot ulcers and related treatments bridges the gap between traditional evidence-based learning and more motivating and interactive learning approaches.

Background The genetic architecture of Brugada syndrome (BrS) is emerging as an increasingly complex area of investigation. The identification of genetically homogeneous populations can provide mechanistic insights and improve genotype-phenotype correlation. Objective To characterize and define the clinical implications of a novel BrS founder mutation. Using a haplotype-based approach we investigated whether 2 SCN5A genetic variants could derive from founder events. Methods Single nucleotide polymorphisms were genotyped in 201 subjects, haplotypes reconstructed, and mutational age estimated. Clinical phenotypes and historical records were collected. Results A SCN5A variant (c.3352C>T; p.Gln1118Ter) was identified in 3 probands with BrS originating from south Italy. The same mutation was identified in a proband from central Italy and in 1 U.S. resident subject with Italian ancestry. The 5 individuals carried a common core haplotype, whose frequency was extremely low in local noncarrier probands and in population controls (0%–6.06%). The clinical presentation included multigenerational dominant transmission of Brugada electrocardiographic pattern, high incidence of sudden cardiac death (SCD), and cardiac conduction defects (CCD). We reconstructed 7-generation pedigrees with common geographic origin. Variant’s age estimates suggested that origin of the p.Gln1118Ter dates back 76 generations (95% confidence interval: 28–200). A second SCN5A variant (c.5350G>A; p.Glu1784Lys) identified in the region did not show similar founder signal. Conclusion p.Gln1118Ter is a novel BrS/CCD/SCD founder mutation. We illustrate how these findings provide insights on the inheritance patterns and phenotypes associated with SCN5A mutation.

ObjectivesTo perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions.DesignRetrospective cohort study.SettingThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe.ParticipantsPatients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2.Primary and secondary outcome measuresPatients were categorized as “ever-severe” or “never-severe” using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction.ResultsOf 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites.ConclusionsLaboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.

Objective The Consortium for Clinical Characterization of COVID-19 by EHR (4CE) is an international collaboration addressing coronavirus disease 2019 (COVID-19) with federated analyses of electronic health record (EHR) data. We sought to develop and validate a computable phenotype for COVID-19 severity. Materials and Methods Twelve 4CE sites participated. First, we developed an EHR-based severity phenotype consisting of 6 code classes, and we validated it on patient hospitalization data from the 12 4CE clinical sites against the outcomes of intensive care unit (ICU) admission and/or death. We also piloted an alternative machine learning approach and compared selected predictors of severity with the 4CE phenotype at 1 site. Results The full 4CE severity phenotype had pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of individual code categories for acuity had high variability—up to 0.65 across sites. At one pilot site, the expert-derived phenotype had mean area under the curve of 0.903 (95% confidence interval, 0.886-0.921), compared with an area under the curve of 0.956 (95% confidence interval, 0.952-0.959) for the machine learning approach. Billing codes were poor proxies of ICU admission, with as low as 49% precision and recall compared with chart review. Discussion We developed a severity phenotype using 6 code classes that proved resilient to coding variability across international institutions. In contrast, machine learning approaches may overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold-standard outcomes, possibly owing to heterogeneous pandemic conditions. Conclusions We developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.

Benefits of pulmonary rehabilitation in Interstitial Lung Diseases (ILD) have been reported. The aim of this large multicenter study was to identify the success predictors of pulmonary rehabilitation in a real-life setting.Data of 240 in-patients (110 idiopathic pulmonary fibrosis (IPF), 106 ILD other than IPF and 24 undetermined ILD) undergoing pulmonary rehabilitation in a 10-year period were retrospectively evaluated. Six minute walking distance (6MWT), body weight-walking distance product tests, dyspnoea and arterial blood gases were assessed at admission and discharge. Differences in post rehabilitation changes in outcome measures as function of baseline characteristics were evaluated.After rehabilitation, patients showed improvements in all outcome measures (p 0.05), regardless of the underlying diagnosis or disease severity. Patients needing oxygen therapy at rest showed reduced benefits. Baseline 6MWD inversely correlated with its changes at discharge. Non-significant greater benefits after rehabilitation were found in IPF patients under antifibrotic therapy. In a subset of 50 patients assessed on average 10.3 ± 3.5 months after discharge, the benefits in 6MWD were not maintained (312.9 ± 139.4, 369.7 ± 122.5 and 310.8 ± 139.6 m at admission, discharge and follow up respectively: p 0.0001).Pulmonary rehabilitation may improve dyspnoea, exercise capacity and fatigue in patients with ILD of different aethiologies and level of severity. The long-term effects need to be established.

A bulk of evidence in the field of translational medicine applied to clinical toxicology and rehabilitation has highlighted the possibility of using biomarkers as a support in the diagnosis of alcohol-related diseases and in monitoring of alcohol withdrawal. In a cohort of 55 subjects admitted to a 4-week residential rehabilitation period for alcohol detoxification, we applied a complementary approach correlating novel and conventional peripheral blood and urine parameters in combination with clinical and functional evaluation, contextually considered with the patient's history. Biomarkers of oxidative, inflammatory, hepatic, and neurochemical effects paralleled by alcohol craving and clinical scale measurements were determined at two specific time points, i.e., admission and discharge. Concerning the post-discharge assessment (i.e., relapse evaluation one month after discharge), a follow-up oral interview during a clinical examination was applied to evaluate alcohol abstinence.Selected biomarkers, i.e., MCP1, F2-IsoPs, and SOD1, were altered in chronic alcoholics at admission, and then showed a clearly changing trend during hospitalization. Our findings demonstrated that these specific non-traditional biomarkers, measured together with more conventional ones (e.g., CDT, EtG, IL8, ALT, AST, GGT), could represent novel key parameters for monitoring alcohol use disorders and withdrawal, being also suggestive of the complexity of the psychoneuroimmune response to alcohol. A general improvement in psychological functioning (i.e., decreases in anxiety, depression, and psychological distress) was also revealed during the 4-week rehabilitation treatment, paralleled by an increase of well-being and positive changes in terms of scores. Moreover, a positive association between SOD1 and drink craving at admission was evidenced. Notably, both SOD1 and well-being displayed a significant relation with lower risk of alcohol relapse one month after discharge, indicating that SOD1 is a good predictor of reduced relapse probability. This 4-week residential rehabilitation protocol represents a sound strategy enabling identification of alcohol use disorders and monitoring of alcohol addiction state and withdrawal. However, it has to be emphasized that results derived from this pilot study need to be extensively validated in large and independent cohorts of subjects.

Objectives Despite the widespread diffusion of continuous glucose monitoring (CGM) systems, which includes both real-time CGM (rtCGM) and intermittently scanned CGM (isCGM), an effective application of CGM technology in clinical practice is still limited. The study aimed to investigate the relationship between isCGM-derived glycemic metrics and glycated hemoglobin (HbA1c), identifying overall CGM targets and exploring the inter-subject variability. Methods A group of 27 children and adolescents with type 1 diabetes under multiple daily injection insulin-therapy was enrolled. All participants used the isCGM Abbott’s FreeStyle Libre system on average for eight months, and clinical data were collected from the Advanced Intelligent Distant-Glucose Monitoring platform. Starting from each HbA1c exam date, windows of past 30, 60, and 90 days were considered to compute several CGM metrics. The relationships between HbA1c and each metric were explored through linear mixed models, adopting an HbA1c target of 7%. Results Time in Range and Time in Target Range show a negative relationship with HbA1c (R2>0.88) whereas Time Above Range and Time Severely Above Range show a positive relationship (R2>0.75). Focusing on Time in Range in 30-day windows, random effect represented by the patient’s specific intercept reveals a high variability compared to the overall population intercept. Conclusions This study confirms the relationship between several CGM metrics and HbA1c; it also highlights the importance of an individualized interpretation of the CGM data.

Background Inconsistent data support the role of CACNA1C as a disease-causing gene responsible for Brugada syndrome (BrS). As of today, the only gene consistently linked with BrS is SCN5A. Several CACNA1c genetic variants have been reported in association wirh BrS; however, due to the limited evidence, CACNA1C is not suggested for routine genetic screening for BrS. Purpose In this study, we carried out a systematic screening of CACNA1C gene, including a functional evaluation of the identified variants, in order to determine the yield of screening in a large series of BrS probands and to address the hypothesis that an appropriate clinical selection of patients would substantially improve the yield of genetic testing. Methods and results Overall 564 consecutive patients, referred for BrS genetic testing, were sequenced for CACNA1C gene. Patients were divided in two groups: discovery cohort (n=200 patients) and confirmation cohort (n=363 patients). Furthermore, analysis of the clinical phenotypes of a matched SCN5A positive BrS cohort (n=146) was included for phenotype characterization. In the discovery cohort we identified 11 different genetic variants of whom 2 (18%) were considered as potentially causative based on ACMG guidelines. However, a large proportion (81%) was classified as variants of unknown significance (VUS). Functional evaluation of the identified variants, including pathogenic and VUS, was assessed by patch-clamp and immunofluorescence studies. Re-evaluation of the variants, including functional studies results, indicated an increase of pathogenic or likely pathogenic variants (81%) getting a yield of screening of 5% in the discovery cohort. Results from the confirmation cohort confirmed a low rate of CACNA1C carriers with a yield of screening of 2.2%. Analysing the clinical phenotype of all CACNA1C carriers showed a significantly shorter QTc [371 ms ± 16 ms vs. 399±18 ms; p=0.000004]. Furthermore, the prevalence of CACNA1C variants was highest (12.9%) among patients with a QTc in the lowest quartile (QTc Conclusion We confirmed that CACNA1C variants are not a common cause of BrS, with a yield of screening of 2–5%. However, pathogenic variants are more frequent (12.5%) in patients with a shorter QTc, suggesting a genetic testing strategy in this subgroup of BrS patients. Furthermore, our data highlights the impact of robust functional studies to improve variant classification and reduce uncertainties. Funding Acknowledgement Type of funding source: None

IntroductionThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE) includes hundreds of hospitals internationally using a federated computational approach to COVID-19 research using the EHR.ObjectiveWe sought to develop and validate a standard definition of COVID-19 severity from readily accessible EHR data across the Consortium.MethodsWe developed an EHR-based severity algorithm and validated it on patient hospitalization data from 12 4CE clinical sites against the outcomes of ICU admission and/or death. We also used a machine learning approach to compare selected predictors of severity to the 4CE algorithm at one site.ResultsThe 4CE severity algorithm performed with pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of single code categories for acuity were unacceptably inaccurate - varying by up to 0.65 across sites. A multivariate machine learning approach identified codes resulting in mean AUC 0.956 (95% CI: 0.952, 0.959) compared to 0.903 (95% CI: 0.886, 0.921) using expert-derived codes. Billing codes were poor proxies of ICU admission, with 49% precision and recall compared against chart review at one partner institution.DiscussionWe developed a proxy measure of severity that proved resilient to coding variability internationally by using a set of 6 code classes. In contrast, machine-learning approaches may tend to overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold standard outcomes, possibly due to pandemic conditions.ConclusionWe developed an EHR-based algorithm for COVID-19 severity and validated it at 12 international sites.

Background and Aim: The Barthel Dyspnoea Index (BDi) is responsive to change in patients with chronic obstructive pulmonary disease (COPD). However, the minimum clinically important difference (MCID) has not been established. We aimed to identify the MCID for the BDi using anchor-based and distribution-based methods. Methods: In a retrospective analysis we assessed BDi before and after inpatient pulmonary rehabilitation in 2328 patients with COPD (1152 with chronic respiratory failure - CRF). The Medical Research Council (MRC) score was measured concurrently as anchors. We used receiver operating characteristic (ROC) curves, linear regression, and distribution-based methods to estimate the MCID for the BDi; we included only patients with paired BDi scores in the analysis. Results: The mean change for the whole group in BDi score with pulmonary rehabilitation was -10 (IQR -17 : -3; p Conclusions: The most conservative estimate of the MCID for the BDi is -9 points in patients with COPD and -12 in patients without CRF. This estimate could be useful in the clinical interpretation of BDi data, particularly in response to intervention studies.

Background: Progesterone receptor (PgR) negative breast cancer (BC) is an aggressive subtype with poor prognosis and reduced response to endocrine treatments. Several studies have suggested that androgen receptor (AR) expression is associated with a favorable tumor biology, longer recurrence free survival (RFS), and overall survival. In the literature no data exist regarding the role of AR expression in early stage estrogen receptor (ER)+/PgR– BCs. The aim of this study was to evaluate the prognostic role of AR expression in this setting. Patients and methods: This is a monocentric retrospective study in which 208 patients who underwent surgical intervention for ER+/PgR−/Human Epidermal growth factor Receptor 2 (HER2)– BC were included. The primary objective was to analyze the relationship between AR expression and RFS. Results: At a median follow-up of 77 months, 75 patients (36%) had a disease relapse (all sites included). AR expression was significantly higher in patients who did not relapse compared with those who relapsed with an impact on RFS (hazard ratio [HR] = 0.99, p = 0.025). Patients with AR expression ⩾80% had a lower risk of relapse compared with those with AR Conclusions: The results of this study support the potential prognostic role of AR in patients with ER+/PgR− BCs and may contribute to the identification of subgroups of high-risk patients.

The global healthcare landscape is continuously changing throughout the world as technology advances, leading to a gradual change in lifestyle. Several diseases such as asthma and cardiovascular conditions are becoming more diffuse, due to a rise in pollution exposure and a more sedentary lifestyle. Healthcare providers deal with increasing new challenges, and thanks to fast-developing big data technologies, they can be faced with systems that provide direct support to citizens. In this context, within the EU-funded Participatory Urban Living for Sustainable Environments (PULSE) project, we are implementing a data analytic platform designed to provide public health decision makers with advanced approaches, to jointly analyze maps and geospatial information with healthcare and air pollution data. In this paper we describe a component of such platforms, which couples deep learning analysis of urban geospatial images with healthcare indexes collected by the 500 Cities project. By applying a pre-learned deep Neural Network architecture, satellite images of New York City are analyzed and latent feature variables are extracted. These features are used to derive clusters, which are correlated with healthcare indicators by means of a multivariate classification model. Thanks to this pipeline, it is possible to show that, in New York City, health care indexes are significantly correlated to the urban landscape. This pipeline can serve as a basis to ease urban planning, since the same interventions can be organized on similar areas, even if geographically distant.

Background:. Traditionally, nonmelanoma skin cancers (NMSCs) are considered mainly UV-related malignancies. Nevertheless, a strong correlation between the embryologically relevant sites (ERS) of the head and neck and the preferential sites of onset of basal cell carcinomas (BCCs) has long been supposed and demonstrated. The aim of this research was the investigation of the potential correlation between the ERS of the head and neck and the sites of tumor onset in all of the NMSCs. Methods:. The distribution of 1165 NMSC was correlated with the ERS of the head and neck using the universally accepted anatomical diagrams featuring the congenital head and neck clefts and an original anatomical diagram showing the most credited sites of the embryonic fusion planes of the auricle. Results:. In our sample, both BCC and SSC display an increased likelihood of onset in the ERS of the head and neck. A proportion of 93.10% BCCs was distributed within ERS, while 6.90% derived from non-embryologically relevant sites (P < 0.001). A proportion of 69.70% SCCs was distributed within ERS, while 30.30% derived from non-embryologically relevant sites (P < 0.001). The probability of tumors within ERS was significantly higher for BCC versus SCC (P < 0.001), with BCCs having a 5-fold increase in the probability of occurring in ERS compared to SCCs (P < 0.001). Conclusions:. The ERS might host areas of cellular instability yielding to the development of an NMSC. The environmental UV exposure plays a relatively main role versus dysontogenic factors in the pathogenesis of SCC.

The presented collection of data comprises of a set of 12 linear and nonlinear indices computed at different time scales and extracted from Fetal Heart Rate (FHR) traces acquired through Hewlett Packard CTG fetal monitors (series 1351A), connected to a PC. The sampling frequency of the recorded FHR signal is equal 2 Hz. The recorded populations consist of two groups of fetuses: 60 healthy and 60 Intra Uterine Growth Restricted (IUGR) fetuses. IUGR condition is a fetal condition defined as the abnormal rate of fetal growth. In clinical practice, diagnosis is confirmed at birth and may only be suspected during pregnancy. The pathology is a documented cause of fetal and neonatal morbidity and mortality. The described database was employed in a set of machine learning approaches for the early detection of the IUGR condition: “Integrating machine learning techniques and physiology based heart rate features for antepartum fetal monitoring” [1]. The added value of the proposed indices is their interpretability and close connection to physiological and pathological aspect of FHR regulation. Additional information on data acquisition, feature extraction and potential relevance in clinical practice are discussed in [1]. Keywords: Fetal heart rate monitoring, Cardiotocography, Intra uterine growth restricted, Physiology-based features, Multivariate analysis, Predictive analytics

Background. Poststroke dysphagia is associated with considerable morbidity and has high health care cost implications. Objective. To evaluate whether anodal transcranial direct current stimulation (tDCS) over the lesioned hemisphere and cathodal tDCS to the contralateral one during the early stage of rehabilitation can improve poststroke dysphagia. Methods. A total of 40 patients referred to our neurorehabilitation department were randomized to receive anodal tDCS over the damaged hemisphere plus cathodal stimulation over the contralateral one versus sham stimulation during swallowing maneuvers over the course of 10 sessions of treatment. Swallowing function was evaluated before and after stimulation using the Dysphagia Outcome and Severity Scale (DOSS). Results. The percentage of patients who reached various thresholds of improvement was higher in the tDCS group than in the sham group, but the differences were not significant (eg, DOSS score ≥ 20% increase from baseline: 55% in the tDCS group vs 40% in the sham group; P = .53). Among all variables recorded at baseline, only a subgroup of patients without nasogastric tube showed a significantly higher improvement with tDCS treatment versus sham (DOSS score ≥10% and ≥20% from baseline: 64.29% vs 0%, P = .01). Conclusions. In patients with poststroke dysphagia, treatment with dual tDCS in the early phase of rehabilitation does not significantly increase the probability of recovery compared with sham stimulation.

Background Currently, a major point of concern in the management of Inflammatory Bowel Diseases (IBD) is the absence of accurate and specific circulating biomarkers able to drive diagnosis in a timely and noninvasive manner. Aim of the present study was to explore blood biomarkers of IBD by coupling the targeted detection of circulating fibroblast activation protein (FAP), a recognized valuable marker of bowel lesion in IBD, and Raman spectroscopy (RS), a quick and label-free metabolomic technique that provides a real-time biochemical characterization of plasma samples without any previously known target. Methods Blood samples were collected from over 140 patients with IBD and 170 control subjects matched for gender and age. Isolated plasma was analysed by enzyme-linked immunosorbent assay for quantitative detection of circulating form of FAP. RS was performed on dry droplets of plasma, with the aim to decipher specific fingerprint of IBD in peripheral blood. A predictive model was built on FAP and Raman data separately, to determine specificity, sensitivity and accuracy of the two approaches in patients classification. Supervised multivariate model was applied on a subset of 203 patients to discriminate IBD and control subjects based on combined datasets. Results FAP levels were reduced in patients with IBD as compared to controls (p Conclusion RS and FAP dosage enable new discoveries in the biological fingerprint of IBD plasma and provide novel candidate biomarkers of IBD. Our preliminary results strongly suggest that novel blood-based approaches could represent a fast noninvasive way to triage patents with suspected IBD in first care diagnostic, to be applied prior to further specific evaluation.

Introduction: Automatic event detection (AED) of residual apnea-hypopnea index (AHI) by ventilators is a current practice in sleep and mechanical ventilation Units but this methodology has not been validated in an unselected population of OSA patients. Aim of the present study was to assess in a “real-life” condition the reliability of AED during PAP therapy by the in-built software compared to full polysomnography during follow-up. Methods: We enrolled 300 OSA patients (105 F; AHI 45.3 ± 27.8) already on Positive airway pressure (PAP) therapy: 53% of the patients were on CPAP while other modalities were used in the rest of the sample. Results: Overall, the built-in software identified residual obstructive AHI (AHIPAP) > 5, 10 or 15 in 18.7, 8.6 or 4.6% of patients, respectively. By using AHIPAP, 28.4% of patients were wrongly classified as “well controlled” despite a residual AHIPSG>5 (6% considering a residual AHIVENT >15); 7% of patients were classified as not controlled while AHIPSG was 15). Type of ventilation, ventilator parameters, adherence to treatment and level of baseline or follow-up Epworth Sleepiness Scale score were similar between groups. The sensitivity and positive predicted values were very low. Positive likelihood ratio appears adequate only for residual AHIPAP ≥10, but negative likelihood ratio was inconclusive for all the cut-off considered. Discussion: The results of the present study suggest a more cautious approach in the follow-up of OSA patients, since a protocol based only on AED detection and symptoms assessment may not be accurate especially for AHIPAP

Background: Dermal substitutes are currently largely used for the treatment of huge skin loss in patients in critical general health conditions, for the treatment of severe burns and to promote the healing process in chronic wounds. Aims: The authors performed a retrospective assessment of their experience with bioengineered skin to possibly identify the most appropriate clinical indication and management for each substitute. Materials and Methods: The study involved 109 patients with 127 skin defects repaired with dermal substitutes over a 9 years period, from 2007 to 2016. Hyalomatrix® was used in 63 defects, whereas Integra® and Nevelia® were used in 56 and 8 defects, respectively. Results: The statistical analysis failed to reveal a correlation between the choice of a specific dermal substitute and any possible clinical variable except in the soft-tissue defects of the scalp where Hyalomatrix® was electively used. Conclusions: In the authors’ experience, the scalp defects followed a radical excision of skin tumours that included the periosteum. Here, the preliminary cover with a hyaluronan three-dimensional scaffold constantly allowed for the regeneration of a derma-like layer with a rich vascular network fit for supporting a split-thickness skin graft. Nevertheless, the authors still prefer Integra® when the goal is a better cosmetic outcome and Hyalomatrix® when a faster wound healing is required, especially in the management of deep wounds where the priority is a fast obliteration with a newly formed tissue with a rich blood supply. However, these clinical indications still are anecdotally based.

Long QT syndrome (LQTS) is a common inheritable arrhythmogenic disorder, often secondary to mutations in the KCNQ1, KCNH2, and SCN5A genes. The disease is characterized by a prolonged ventricular repolarization (QTc interval) that confers susceptibility to life-threatening arrhythmic events (LAEs). This study sought to create an evidence-based risk stratification scheme to personalize the quantification of the arrhythmic risk in patients with LQTS. Data from 1,710 patients with LQTS followed up for a median of 7.1 years (interquartile range [IQR]: 2.7 to 13.4 years) were analyzed to estimate the 5-year risk of LAEs based on QTc duration and genotype and to assess the antiarrhythmic efficacy of beta-blockers. The relationship between QTc duration and risk of events was investigated by comparison of linear and cubic spline models, and the linear model provided the best fit. The 5-year risk of LAEs while patients were off therapy was then calculated in a multivariable Cox model with QTc and genotype considered as independent factors. The estimated risk of LAEs increased by 15% for every 10-ms increment of QTc duration for all genotypes. Intergenotype comparison showed that the risk for patients with LQT2 and LQT3 increased by 130% and 157% at any QTc duration versus patients with LQT1. Analysis of response to beta-blockers showed that only nadolol reduced the arrhythmic risk in all genotypes significantly compared with no therapy (hazard ratio: 0.38; 95% confidence interval: 0.15 to 0.93; p = 0.03). The study provides an estimator of risk of LAEs in LQTS that allows a granular estimate of 5-year arrhythmic risk and demonstrate the superiority of nadolol in reducing the risk of LAEs in LQTS. This work was supported by the Ricerca Corrente funding scheme of the Italian Ministry of Health. Dr. Ortiz has received personal fees from Health in Code, SL. Dr. Monserrat is a shareholder in Health in Code, SL. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. Sí

COVID-19 survivors are associated with acute respiratory failure (ARF) and show a high prevalence of impairment in physical performance. The present studied aimed to assess whether we may cluster these individuals according to an exercise test. The presented study is a retrospective analysis of 154 survivors who were admitted to two hospitals of Istituti Clinici Scientifici Maugeri network, Italy. Clinical characteristics, walked distance, heart rate (HR), pulse oximetry (SpO2), dyspnoea, and leg fatigue (Borg scale: Borg-D and Borg-F, respectively) while performing the six-minute walking test (6MWT) were entered into unsupervised clustering analysis. Multivariate linear regression identified variables that were informative for the set of variables used for cluster definition. Cluster 1 (C1: 86.4% of participants) and Cluster 2 (C2: 13.6%) were identified. Compared to C1, the individuals in C2 were significantly older, showed significantly higher increase in fatigue and in dyspnoea, greater reduction in SpO2, and a lower HRpeak during the test. The need of walking aids, time from admission to acute care hospitals, age, body mass index, endotracheal intubation, baseline HR and baseline Borg-D, and exercise-induced SpO2 change were significantly associated with the variables that were used for cluster definition. Different characteristics and physiological parameters during the 6MWT characterise survivors of COVID-19-associated ARF. These results may help in the management of the long-term effects of the disease.

Made available in DSpace on 2022-04-29T08:35:26Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-10-01 National Human Genome Research Institute National Center for Advancing Translational Sciences National Heart, Lung, and Blood Institute National Institutes of Health U.S. National Library of Medicine National Institute of Neurological Disorders and Stroke Canadian Thoracic Society Background: Many countries have experienced 2 predominant waves of COVID-19–related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic. Objective: In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic. Methods: Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19. Results: Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain. Conclusions: Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve. Department of Biomedical Informatics Harvard Medical School BIOMERIS (BIOMedical Research Informatics Solutions) Clinical Research Unit Botucatu Medical School São Paulo State University Division of Nephrology Department of Medicine Ente Ospedaliero Cantonale Department of Electrical Computer and Biomedical Engineering University of Pavia Information Technology Department Azienda Socio-Sanitaria Territoriale di Pavia Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Massachusetts Veterans Epidemiology Research and Information Center Veterans Affairs Boston Healthcare System Department of Medicine Massachusetts General Hospital Department of Medicine David Geffen School of Medicine University of California Los Angeles Health Informatics Hospital Universitario 12 de Octubre Department of Learning Health Sciences University of Michigan Medical School Department of Biomedical Informatics University of Kentucky Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Institute for Biomedical Informatics University of Pennsylvania Perelman School of Medicine Department of Preventive Medicine Northwestern University Institute for Biomedical Informatics University of Kentucky Medical University of South Carolina Department of Computer Science Renaissance Computing Institute University of North Carolina at Chapel Hill Department of Biostatistics Harvard T.H. Chan School of Public Health Department of Anaesthesia National University Health System Institute of Medical Biometry and Statistics Faculty of Medicine and Medical Center University of Freiburg Michigan Institute for Clinical & Health Research Informatics University of Michigan Laboratory of Informatics and Systems Engineering for Clinical Research Istituti Clinici Scientifici Maugeri SpA SB IRCCS Clinical Hospital of Botucatu Medical School São Paulo State University Informatique et Archivistique Médicales Unit Bordeaux University Hospital Department of Biomedical Informatics University of Pittsburgh Department of Neurology Massachusetts General Hospital Department of Biomedical Informatics Hôpital Necker-Enfants Malade Assistance Publique Hôpitaux de Paris University of Paris Department of Biomedical Informatics Institute for Digital Medicine National University Health System Internal Medicine Department Botucatu Medical School São Paulo State University Department of Computational Medicine & Bioinformatics Internal Medicine Human Genetics and Public Health University of Michigan Division of Medical Informatics Department of Internal Medicine University of Kansas Medical Center Data Analytics Center University of Pennsylvania Health System Department of Medicine National University Health System Department of Neurology University of Pittsburgh Section of Nephrology Department of Pediatrics Brenner Children's Hospital Wake Forest School of Medicine Clinical Research Unit Botucatu Medical School São Paulo State University Clinical Hospital of Botucatu Medical School São Paulo State University Internal Medicine Department Botucatu Medical School São Paulo State University National Human Genome Research Institute: 3U01HG008685-05S2 National Human Genome Research Institute: 5R01HG009174-04 National Center for Advancing Translational Sciences: 5UL1TR001857-05 National Heart, Lung, and Blood Institute: K23HL148394 National Heart, Lung, and Blood Institute: L40HL148910 National Institutes of Health: P30ES017885 U.S. National Library of Medicine: R01LM012095 U.S. National Library of Medicine: R01LM013345 National Institute of Neurological Disorders and Stroke: R01NS098023 U.S. National Library of Medicine: T15LM007092 National Institutes of Health: U24CA210967 National Center for Advancing Translational Sciences: UL1TR000005 National Center for Advancing Translational Sciences: UL1TR001420 National Center for Advancing Translational Sciences: UL1TR001450 National Center for Advancing Translational Sciences: UL1TR001857 National Center for Advancing Translational Sciences: UL1TR001878 National Center for Advancing Translational Sciences: UL1TR001881 Canadian Thoracic Society: UL1TR001998 National Center for Advancing Translational Sciences: UL1TR002240 Canadian Thoracic Society: UL1TR002366 National Center for Advancing Translational Sciences: UL1TR002541

Objective: A study was established to objectively assess the effects of low-intensity electromagnetic and electric stimulation plus negative pressure on mature scars. Background: Radiofrequency plus negative pressure therapy demonstrated a favorable reorganization and regeneration of the collagen and elastic fibers and was proposed for the treatment of cellulitis and skin stretch marks. Methods: Twenty-six mature scars in 20 Caucasian patients (15 females and 5 males) were enrolled in the study. The treatments were carried out with a Class I, BF-type electromedical device equipped with a radiofrequency generator, an electric pulse generator, and a vacuum pump twice a week for 3 months. Corneometry, transepidermal water loss, elastometry, colorimetry, and three-dimensional skin surface pattern were objectively assessed with Multi Probe Adapter System MPA and PRIMOS pico. A subjective assessment was carried out with the VAS and PSAS scales. Each scar was compared before and after the treatment and with the skin in the corresponding healthy contralateral anatomical area at the same times. Results: Reduction of the scar surface wrinkling and overall scar flattening were demonstrated after the treatment. The scar slightly tended to approach the color and elasticity of healthy skin too. Conclusions: The combined local treatment of mature scars with low-intensity electromagnetic and electric stimulation in association with negative pressure might suggest a favorable synergic effect on the scar collagen and elastic fiber remodeling.

Objective The study aimed to evaluate whether high-flow oxygen therapy (HFOT) during training was more effective than oxygen in improving exercise capacity in hypoxemic chronic obstructive pulmonary disease (COPD). Methods A total of 171 patients with COPD and chronic hypoxemia were consecutively recruited in 8 rehabilitation hospitals in a randomized controlled trial. Cycle-ergometer exercise training was used in 20 supervised sessions at iso inspiratory oxygen fraction in both groups. Pre- and post-training endurance time (Tlim), 6-minute walking distance (6MWD), respiratory and limb muscle strength, arterial blood gases, Barthel Index, Barthel Dyspnea Index, COPD Assessment Test, Maugeri Respiratory Failure questionnaire, and patient satisfaction were evaluated. Results Due to 15.4% and 24.1% dropout rates, 71 and 66 patients were analyzed in HFOT and Venturi mask (V-mask) groups, respectively. Exercise capacity significantly improved after training in both groups with similar patient satisfaction. Between-group difference in post-training improvement in 6MWD (mean: 17.14 m; 95% CI = 0.87 to 33.43 m) but not in Tlim (mean: 141.85 seconds; 95% CI = −18.72 to 302.42 seconds) was significantly higher in HFOT. The minimal clinically important difference of Tlim was reached by 47% of patients in the V-mask group and 56% of patients in the HFOT group, whereas the minimal clinically important difference of 6MWD was reached by 51% of patients in the V-mask group and 69% of patients in the HFOT group, respectively. Conclusion In patients with hypoxemic COPD, exercise training is effective in improving exercise capacity. Impact Statement The addition of HFOT during exercise training is not more effective than oxygen through V-mask in improving endurance time, the primary outcome, whereas it is more effective in improving walking distance.

Background and objectives Intrauterine Growth Restriction (IUGR) is a fetal condition defined as the abnormal rate of fetal growth. The pathology is a documented cause of fetal and neonatal morbidity and mortality. In clinical practice, diagnosis is confirmed at birth and may only be suspected during pregnancy. Therefore, designing an accurate model for the early and prompt identification of pathology in the antepartum period is crucial in view of pregnancy management. Methods We tested the performance of 15 machine learning techniques in discriminating healthy versus IUGR fetuses. The various models were trained with a set of 12 physiology based heart rate features extracted from a single antepartum CardioTocographic (CTG) recording. The reason for the utilization of time, frequency, and nonlinear indices is based on their standalone documented ability to describe several physiological and pathological fetal conditions. Results We validated our approach on a database of 60 healthy and 60 IUGR fetuses. The machine learning methodology achieving the best performance was Random Forests. Specifically, we obtained a mean classification accuracy of 0.911 [0.860, 0.961 (0.95 confidence interval)] averaged over 10 test sets (10 Fold Cross Validation). Similar results were provided by Classification Trees, Logistic Regression, and Support Vector Machines. A features ranking procedure highlighted that nonlinear indices showed the highest capability to discriminate between the considered fetal conditions. Nevertheless, is the combination of features investigating CTG signal in different domains, that contributes to an increase in classification accuracy. Conclusions We provided validation of an accurate artificially intelligence framework for the diagnosis of IUGR condition in the antepartum period. The employed physiology based heart rate features constitute an interpretable link between the machine learning results and the quantitative estimators of fetal wellbeing.

Discussion about patients' end-of-life (E-o-L) preferences should be part of the routine practice. Using a semi-structured interview with a scenario-based decision, we performed a prospective multicentre study to elicit the patients' E-o-L preferences in very severe chronic obstructive pulmonary disease (COPD). We also checked their ability to retain this information and the respect of their decisions when they die. Forty-three out of ninety-one of the eligible patients completed the study. The choice of E-o-L practice was equally distributed among the three proposed options: endotracheal intubation (ETI), 'ceiling' non-invasive ventilation (NIV), and palliation of symptoms with oxygen and morphine. NIV and ETI were more frequently chosen by patients who already experienced them. ETI preference was also associated with the use of anti-depressant drugs and a low educational level, while a higher educational level and a previous discussion with a pneumologist significantly correlated with the preference for oxygen and morphine. Less than 50% of the patients retained a full comprehension of the options at 24 hours. About half of the patients who died in the follow-up period were not treated according to their wishes. In conclusion, in end-stage COPD more efforts are needed to improve communication, patients' knowledge of the disease and E-o-L practice.

Background:. The combination of surgery and postoperative radiotherapy allows for the most effective results with keloids. In this trial, surgery and intraoperative radiation therapy (IORT) technology were used—the hypothesis being that the earlier the application of postoperative radiotherapy, the better the wound healing evolution. Methods:. The study included 16 patients with 21 keloids. The keloids were radically excised and repaired with direct suture or local skin flaps. Collimated electron radiotherapy was applied within 45 minutes of surgery. The outcomes were assessed according to the modified Patient and Observer Scar Assessment Scale; the modified Vancouver Scar Scale; and the modified Common Terminology Criteria for Adverse Events v. 4.0 for skin and subcutaneous tissue disorders. Results:. Recurrences were observed in one out of 16 patients, and in two out of 21 keloids (9.5%). The modified Patient and Observer Scar Assessment Scale demonstrated a statistically significant improvement in pain, itching, color, stiffness, thickness, and irregularity after the treatment. The modified Patient and Observer Scar Assessment Scale displayed a statistically significant improvement in the scar vascularity, pigmentation, thickness, and pliability after the treatment. The modified Vancouver Scar Scale demonstrated a statistically significant improvement in 90.48% of the scars after the treatment. The modified Common Terminology Criteria for Adverse Events v. 4.0 for skin and subcutaneous tissue disorders demonstrated an improvement in erythema multiforme and skin pain across the whole sample, with a temporary hyperpigmentation in 19% of the scars after the treatment. Conclusion:. The combination of surgery and collimated electron radiotherapy with IORT technology demonstrated favorable results in 90.5% of the cases.

The search for the genetic determinants of extreme human longevity has been challenged by the phenotype's rarity and its nonspecific definition by investigators. To address these issues, we established a consortium of four studies of extreme longevity that contributed 2,070 individuals who survived to the oldest one percentile of survival for the 1900 U.S. birth year cohort. We conducted various analyses to discover longevity-associated variants (LAV) and characterized those LAVs that differentiate survival to extreme age at death (eSAVs) from those LAVs that become more frequent in centenarians because of mortality selection (eg, survival to younger years). The analyses identified new rare variants in chromosomes 4 and 7 associated with extreme survival and with reduced risk for cardiovascular disease and Alzheimer's disease. The results confirm the importance of studying truly rare survival to discover those combinations of common and rare variants associated with extreme longevity and longer health span.

BPIFB4 is associated with exceptional longevity: four single-nucleotide polymorphisms distinguish the wild-type form from a longevity-associated variant conferring positive effects on blood pressure. The effect of a rare variant (RV; allele frequency, 4%) on blood pressure is unknown. Here, we show that overexpression of RV-BPIFB4 in ex-vivo mouse vessels impairs phosphorylation of endothelial nitric oxide synthase (eNOS), blunting acetylcholine-evoked vasorelaxation; in vivo, virally mediated overexpression of RV-BPIFB4 increases blood pressure, an action absent in eNOS-deficient mice. In humans, we found RV carriers to have increased diastolic blood pressure, a finding that was more marked in subjects on anti-hypertensive medication; moreover, recombinant RV-BPIFB4 protein impaired eNOS function in ex-vivo human vessels. Thus, RV-BPIFB4 acts directly on blood pressure homeostasis and may represent a novel biomarker of vascular dysfunction and hypertension.

Lombardy was the first area in Italy to have an outbreak of coronavirus disease 19 (COVID-19) at the beginning of 2020. In this context, cancer has been reported as a major risk factor for adverse outcomes and death, so oncology societies have quickly released guidelines on cancer care during the pandemic. The aim of this study was to investigate the management of cancer patients and oncological treatments during the COVID-19 pandemic and to describe the containment measures performed in our outpatient clinic at Pavia (Lombardy). A comparison with the same period of the four previous years (2019, 2018, 2017, and 2016) was also performed. Using our electronic databases, we evaluated the number and characteristics of patients accessing the hospital for anticancer drug infusion from 24 February, 2020 to 30 April, 2020 and the number of radiological exams performed. Although a significant reduction in access for therapy was seen when compared with 2019 (2590 versus 2974, access rate ratio (ARR) = 0.85, p &lt, 0.001), no significant differences in access numbers and ARR was evident between 2020 and 2018, 2017, or 2016 (2590 versus 2626 (ARR = 0.07), 2660 (ARR = 0.99), and 2694 (ARR = 0.96), respectively, p &gt, 0.05). In 2020, 63 patients delayed treatment: 38% for &ldquo, pandemic fear&rdquo, 18% for travel restrictions, 13% for quarantine, 18% for flu syndrome other than COVID-19, and 13% for worsening of clinical conditions and death. Only 7/469 patients developed COVID-19. A significant reduction in radiological exams was found in 2020 versus all the other years considered (211 versus 360, 355, 385, 390 for the years 2020, 2019, 2018, 2017, and 2016, respectively, p &lt, 0.001). The low incidence of COVID-19 among our cancer patients, along with the hospital policy to control infection, enabled safe cancer treatment and a continuum of care in most patients, while a small fraction of patients experienced a therapeutic delay due to patient-related reasons.

Within the EU-funded Pulse project, we are implementing a data analytic platform designed to provide public health decision makers with advanced approaches to jointly analyze maps and geospatial information with health care data and air pollution measurements. In this paper we describe a component of such platform, designed to couple deep learning analysis of geospatial images of cities and some healthcare and behavioral indexes collected by the 500 cities US project, showing that, in New York City, urban landscape significantly correlates with the access to healthcare services.

BACKGROUND: Humidification is a standard of care during invasive mechanical ventilation. Two types of devices are used for this purpose: heated humidifiers and heat-and-moisture exchangers (HME). AIM: To compare the short-term physiologic effects of an active HME, with those of heated humidifiers and HMEs in terms of respiratory effort, ventilatory pattern, and arterial blood gases during invasive mechanical ventilation. METHODS: We conducted a randomized crossover study with 3 different devices in 15 stable subjects who had a tracheostomy and were ventilator-dependent. Transdiaphragmatic pressure, ventilatory pattern, arterial blood gases, and dyspnea scale were recorded at baseline and at the end of a 20-min period with each device. RESULTS: Compared with heated humidifiers, the active HME was associated with higher diaphragmatic pressure-time product per minute (117.10 [interquartile range {IQR} 34.58–298.60]) versus 80.86 (IQR, 25.46–110.55) cm H2O×s/min, P = .01), higher PaCO2 (48.50 [IQR, 40.65–53.70] vs 39.60 [IQR, 37.50–49.95]) mm Hg, P = .02) and lower pH (7.41 [IQR, 7.36–7.49] vs 7.45 [IQR, 7.40–7.51], P = .030) without any significant difference in ventilatory pattern. A significantly worse dyspnea scale score (active HME, 3 (2–4) vs heated humidifiers: 4 (3–5); P = .009) was also observed. No significant differences were seen between active HME and HME. CONCLUSIONS: This study indicated that, compared with the heated humidifiers, the use of the active HME or the HME increased inspiratory effort, PaCO2, pH, and dyspnea in stable subjects who were tracheostomized and ventilator-dependent.

Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called “Learning Healthcare System Cycle,” where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how “Big Data enabled” integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrhythmogenic Diseases.

Background: An increased weight of the breasts causes several spinal postural alterations that reduce the ability to perform dynamic tasks requiring a stable balance. The effects of the increased weight of the breasts on static posture after implant breast augmentation have not been investigated yet. Methods: Forty volunteer healthy women were asked to wear different sized breast implants (800, 400, and 300 g) inside a dedicated sports bra for 6½ consecutive hours during their everyday life activities, 1 day for every implant size. Posture changes were assessed with the association of a physiatric clinical examination with a static force platform analysis. Results: A significant increase in cervical lordosis after the use of 400-g breast implants and upward was demonstrated. This alteration was stable between the 400-g and 800-g breast implants. The 400-g (per breast) implant might therefore be the load threshold that breaks the cervical postural physiologic balance. A significant increase in lumbar lordosis was demonstrated only after the use of the 800-g breast implants. The static force platform assessment demonstrated a worsening of the balance independent from the visual control with the use of 400-g and 800-g implants. Conclusions: Heavy breast implants proved to induce reversible alterations in the spinal curve, and 400 g is the cutoff for functional physiologic compensation in the short term. Such a weight might be considered the safety limit for the use of breast implants for cosmetic purposes.

The aim of the study was to evaluate the diagnostic performance of a new ultrasound elastography (USE) parameter based on the measurement of the percentage of maximal stiffness within a nodule as compared with the already established elastographic strain index (SI) and to investigate their diagnostic performance according to nodule size.The study included 218 nodules. Each nodule underwent conventional ultrasound (US), USE evaluation, and fine-needle aspiration cytology (FNAC). Thyroid nodules were further stratified into 4 subgroups (G) according to their size (G1,1 cm; G2, 1-2 cm; G3,3 cm). USE evaluation comprised the measurement of the percentage of the areas included in the region of interest corresponding to the maximal stiffness (% Index) and of the SI.The % Index and of the SI were significantly higher in malignant than in benign thyroid nodules, and both measurements displayed a good diagnostic performance (SI sensitivity and specificity, 0.66 and 0.90, respectively; % Index sensitivity and specificity, 0.76 and 0.89, respectively). Compared with SI, the % Index was more informative, both in the whole group of thyroid nodules (odds ratio [OR], 18.68; 95% confidence interval [CI], 6.06 to 63.49; P.0001 versus OR, 26.15; 95% CI, 8.01 to 102.87; P.0001, respectively) and in the G1 and G2 subgroups.The % Index is a stronger predictor of nodule malignancy than both the SI and the conventional US signs. This is particularly true in nodules smaller than 1 cm, which are more difficult to explore both by conventional US and FNAC.

Background The coexistence of chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA), also referred to as overlap syndrome (OS), is associated with a high rate of morbidity, COPD exacerbations and mortality. Treatment with continuous positive airway pressure (CPAP) has proven to significantly decrease the rate of these complications. However, data concerning the effect of CPAP on pulmonary function are scarce and conflicting. The aim of our study was to evaluate the effect of 1 year of CPAP treatment on arterial blood gases (ABGs) and pulmonary function tests in patients with OS and its potential relationship with the baseline severity of airway obstruction. A secondary aim was to search for predictors of changes in the evaluated parameters. Methods A retrospective study on a cohort of 92 patients (74 males) discharged from the Pulmonary Rehabilitation Unit of the Istituti Clinici Scientifici Maugeri in Pavia (Italy) from January 2013 to January 2016, with a diagnosis of OS and a prescription of CPAP, was conducted. Collected data at discharge were compared with 1-year follow-up data. Results After 1 year of CPAP, we observed the following: (I) a significant improvement in ABGs in all patients [median pO2 65.0 (59.0-70.0) vs. 71 (64.8-77.1) mmHg, pCO2 39.8 (36.2-43.5) vs. 38.3 (32.3-44.2) at baseline and after 1 year respectively, P