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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.

ObjectiveTo assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic.Design, setting and participantsThis is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic.Primary and secondary outcome measuresThe primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the average rate of change in laboratory values during the first week of hospitalisation.ResultsBaseline Charlson Comorbidity Index and laboratory values at admission were not significantly different between the first and second waves. The improvement in laboratory values over time was faster in the second wave compared with the first. The average C reactive protein rate of change was –4.72 mg/dL vs –4.14 mg/dL per day (p=0.05). The mortality rates within each risk category significantly decreased over time, with the most substantial decrease in the high-risk group (47.1% in March–April 2020 vs 30.8% in November 2020 to January 2021, pConclusionsAdmission profiles of patients hospitalised with SARS-CoV-2 infection did not differ greatly between the first and second waves of the pandemic, but there were notable differences in laboratory improvement rates during hospitalisation. Mortality risks among patients with similar risk profiles decreased over the course of the pandemic. The improvement in laboratory values and mortality risk was consistent across multiple countries.

Background Innate immunity utilizes components of sensory signal transduction such as bitter and sweet taste receptors. In fact, empirical evidence has shown bitter and sweet taste receptors to be an integral component of antimicrobial immune response in upper respiratory tract infections. Since an efficient immune response plays a key role in the attainment of longevity, it is not surprising that the rs978739 polymorphism of the bitter taste receptor TAS2R16 gene has been shown to be associated with longevity in a population of 941 individuals ranging in age from 20 to 106 years from Calabria (Italy). There are many possible candidate genes for human longevity, however of the many genes tested, only APOE and FOXO3 survived to association in replication studies. So, it is necessary to validate in other studies genes proposed to be associated with longevity. Thus, we analysed the association of the quoted polymorphism in a population of long lived individuals (LLIs) and controls from another Italian population from Cilento. Methods The analysis has been performed on data previously obtained with genome-wide association study on a population of LLIs (age range 90–109 years) and young controls (age range 18–45 years) from Cilento (Italy). Results Statistical power calculations showed that the analysed cohort represented by 410 LLIs and 553 young controls was sufficiently powered to replicate the association between rs978739 and the longevity phenotype according to the effect size and frequencies described in the previous paper, under a dominant and additive genetic model. However, no evidence of association between rs978739 and the longevity phenotype was observed according to the additive or dominant model. Conclusion There are several reasons for the failure of the confirmation of a previous study. However, the differences between the two studies in terms of environment of the population adopted and of the criteria of inclusion have made difficult the replication of the findings.

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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.

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins. ispartof: NEUROBIOLOGY OF AGING vol:92 ispartof: location:United States status: published

We leveraged the largely untapped resource of electronic health record data to address critical clinical and epidemiological questions about Coronavirus Disease 2019 (COVID-19). To do this, we formed an international consortium (4CE) of 96 hospitals across 5 countries (www.covidclinical.net). Contributors utilized the Informatics for Integrating Biology and the Bedside (i2b2) or Observational Medical Outcomes Partnership (OMOP) platforms to map to a common data model. The group focused on comorbidities and temporal changes in key laboratory test values. Harmonized data were analyzed locally and converted to a shared aggregate form for rapid analysis and visualization of regional differences and global commonalities. Data covered 27,584 COVID-19 cases with 187,802 laboratory tests. Case counts and laboratory trajectories were concordant with existing literature. Laboratory tests at the time of diagnosis showed hospital-level differences equivalent to country-level variation across the consortium partners. Despite the limitations of decentralized data generation, we established a framework to capture the trajectory of COVID-19 disease in patients and their response to interventions.

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.

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.

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.

Programa de Pós-Graduação em Engenharia de Materiais. Departamento de Engenharia Metalúrgica, Escola de Minas, Universidade Federal de Ouro Preto. A projeção de escória pode acontecer durante o processo de refino do ferro gusa no BOF devido à formação de um volume excessivo de emulsão gás-metal-escória, que, ao crescer além da capacidade do convertedor, expele grande porção da escória e metal. Assim, são gerados problemas recorrentes para a operação, como refino menos efetivo, menor rendimento metálico, danos ao equipamento, e principalmente, poluição ambiental devido aos gases que são emitidos no momento da projeção. O objetivo deste estudo foi criar um modelamento matemático para prever a ocorrência de projeção em corridas dos convertedores BOF. Este projeto se baseia em análise multivariada de Big Data a qual permitiu identificar as variáveis de operação que mais influenciam no fenômeno projeção, dentre as quais estão o peso de briquete misto e de dunito adicionados durante o sopro, e concentração de silício presente no gusa. Além disso, foi possível treinar redes neurais artificiais em linguagem Python o que gerou um modelo de predição com confiabilidade de 96%. Slopping may occur during the hot metal refining process in the BOF due to the formation of an excessive volume of gas-metal-slag emulsion which, by growing beyond the capacity of the converter, expels a large portion of the slag and metal. This generates recurrent problems for the operation, such as reduction of refining effectiveness, lower metallic yield, damages to the equipment, and mainly, environmental pollution due to gases released during the slopping. The aim of this work was to create a mathematical model to predict the occurrence of slopping in BOF converters. It is based on multivariate Big Data analyzes in order to identify the variables that most influence the slopping phenomenon, such as the weight of mixed briquette and dunite added during blowing, and the silicon concentration in hot metal. In addition, it was possible to train artificial neural networks in Python language that generated a prediction model with 96% of reliability.

We leveraged the largely untapped resource of electronic health record data to address critical clinical and epidemiological questions about Coronavirus Disease 2019 (COVID-19). To do this, we formed an international consortium (4CE) of 96 hospitals across five countries (www.covidclinical.net). Contributors utilized the Informatics for Integrating Biology and the Bedside (i2b2) or Observational Medical Outcomes Partnership (OMOP) platforms to map to a common data model. The group focused on temporal changes in key laboratory test values. Harmonized data were analyzed locally and converted to a shared aggregate form for rapid analysis and visualization of regional differences and global commonalities. Data covered 27,584 COVID-19 cases with 187,802 laboratory tests. Case counts and laboratory trajectories were concordant with existing literature. Laboratory tests at the time of diagnosis showed hospital-level differences equivalent to country-level variation across the consortium partners. Despite the limitations of decentralized data generation, we established a framework to capture the trajectory of COVID-19 disease in patients and their response to interventions.

Variant interpretation for the diagnosis of genetic diseases is a complex process. The American College of Medical Genetics and Genomics, with the Association for Molecular Pathology, have proposed a set of evidence-based guidelines to support variant pathogenicity assessment and reporting in Mendelian diseases. Cardiovascular disorders are a field of application of these guidelines, but practical implementation is challenging due to the genetic disease heterogeneity and the complexity of information sources that need to be integrated. Decision support systems able to automate variant interpretation in the light of specific disease domains are demanded. We implemented CardioVAI (Cardio Variant Interpreter), an automated system for guidelines based variant classification in cardiovascular-related genes. Different omics-resources were integrated to assess pathogenicity of every genomic variant in 72 cardiovascular diseases related genes. We validated our method on benchmark datasets of high-confident assessed variants, reaching pathogenicity and benignity concordance up to 83 and 97.08%, respectively. We compared CardioVAI to similar methods and analyzed the main differences in terms of guidelines implementation. We finally made available CardioVAI as a web resource (http://cardiovai.engenome.com/) that allows users to further specialize guidelines recommendations.

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: 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.

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

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

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.