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The current study introduces an innovative direct and active heating system designed for precise temperature control in vineyards. This system serves as a valuable tool for investigating the influence of climate change on grapevine physiology and, consequently, the characteristics of the resulting wine. The research took place in an experimental vineyard located in Mendoza, Argentina, with V. vinifera cvs. trained to a vertical shoot positioning trellis system over two consecutive growing seasons. The system design utilized electric hot water tanks and polypropylene pipes attached to the foliage catch wires. Over two growing seasons, the system consistently elevated the ambient air temperatures within the canopy by 2.5 ± 0.12 °C compared to the control group. This temperature increase emulated the temperature projections for Mendoza as forecasted by the IPCC by the end of this century. The system displayed heating uniformity, as evidenced by the absence of both vertical and horizontal temperature gradients. Additionally, the significant variation in mean daytime and night-time temperatures between the control and heated treatments highlighted the effectiveness of the system in modifying temperature conditions on a diurnal basis. The heated treatment applied with this system proved to have an effective biological impact on the physiology of grapevines. In both seasons, plants under the heated treatment advanced their bud break and harvest dates. The study showed a significant growth enhancement in the heated treatment, with apical shoots extending significantly longer than those in the control treatment. Additionally, the total soluble solids content increased in the heating treatment, while yield decreased, for both experimental seasons. These results illustrate the robust performance of the system throughout the entire growth period, regardless of fluctuations in atmospheric conditions. This study establishes a new foundation for future research on grapevine responses to climate change. It also opens the door to the implementation of effective adaptation strategies in vineyards, promising a more resilient and adaptable future for grape cultivation.

Objective: Obesity is associated with increased thyroid-stimulating hormone (TSH) in non-pregnant subjects, but this phenomenon has not been fully characterized during pregnancy. Our aim was to evaluate the impact of BMI on first-trimester TSH in a wide cohort of pregnant women with negative anti-thyroperoxidase antibodies (AbTPO) and its implications on uterine artery pulsatility index (UtA-PI), a marker of early placentation. Methods: The study included 2268 AbTPO-negative pregnant women at their first antenatal visit. Anamnestic data, BMI, TSH, anti-nuclear antibody (ANA) and extractable nuclear antigen (ENA) positivity and mean UtA-PI were collected. Results: A total of 1693 women had normal weight, 435 were overweight and 140 were obese. Maternal age, ANA/ENA positivity, history of autoimmune diseases and familiar history of thyroid diseases were similar in the three groups. TSH was significantly higher in obese women (1.8 (IQR: 1.4–2.4) mU/L) when compared to normal weight (1.6 (IQR: 1.2–2.2) mU/L) and overweight (median: 1.6 (IQR: 1.2–2.2) mU/L) ones (P < 0.001). BMI was significantly related with the risk of having a TSH level ≥4 mU/L at logistic regression, independently from non-thyroid autoimmunity, smoking or familiar predisposition for thyroid diseases (OR: 1.125, 95% CI: 1.080–1.172, P < 0.001). A restricted cubic splines regression showed a non-linear relationship between BMI and TSH. Women with a TSH ≥4 mU/L had a higher UtA-PI, independently from BMI. Conclusion: Overweight/obesity is significantly related with TSH serum levels in AbTPO-negative pregnant women, independently from the other risk factors for hypothyroidism during pregnancy. The increase of TSH levels could be clinically relevant, as suggested by its association with abnormal UtA-PI, a surrogate marker of abnormal placentation.

Abstract Background Increased levels of pro-inflammatory proteins in plasma can be detected in older individuals and associate with the so called chronic low-grade inflammation, which contributes to a faster progression of aged-related cardiovascular (CV) diseases, including frailty, neurodegeneration, gastro-intestinal diseases and disorders reflected by alterations in the composition of gut microbiota. However, successful genetic programme of long-living individuals alters the trajectory of the ageing process, by promoting an efficient immune response that can counterbalance deleterious effects of inflammation and the CV complications. This is the case of BPIFB4 gene in which, homozygosity for a four single-nucleotide polymorphism (SNP) haplotype, the Longevity-Associated Variant (LAV) correlates with prolonged health span and reduced risk of CV complications and inflammation. The relation between LAV-BPIFB4 and inflammation has been proven in different experimental models, here we hypothesized that also human homozygous carriers of LAV-BPIFB4 gene may experience a lower inflammatory burden as detected by plasma proteomics that could explain their favourable CV risk trajectory over time. Moreover, we explored the therapeutic effects of LAV-BPIFB4 in inflammatory disease and monolayer model of intestinal barrier. Results We used high-throughput proteomic approach to explore the profiles of circulating proteins from 591 baseline participants selected from the PLIC cohort according to the BPIFB4 genotype to identify the signatures and differences of BPIFB4 genotypes useful for health and disease management. The observational analysis identified a panel of differentially expressed circulating proteins between the homozygous LAV-BPIFB4 carriers and the other alternative BPIFB4 genotypes highlighting in the latter ones a higher grade of immune-inflammatory markers. Moreover, in vitro studies performed on intestinal epithelial organs from inflammatory bowel disease (IBD) patients and monolayer model of intestinal barrier demonstrated the benefit of LAV-BPIFB4 treatment. Conclusions Homozygosity for LAV-BPIFB4 results in the attenuation of inflammation in PLIC cohort and IBD patients providing preliminary evidences for its therapeutic use in inflammatory disorders that need to be further characterized and confirmed by independent studies.

Background: Breast cancer is the most frequent tumour worldwide, and the HR+/HER2– subtype is the most common. For this tumour type, endocrine therapy (ET) is the mainstay of treatment. The association of ET and CDK4/6 inhibitors (CDK4/6i) represents the gold standard for first-line or second-line therapies. However, the optimal therapeutic strategy after CDK4/6i progression is still a matter of debate, with several randomized clinical trials still ongoing. Patients and methods: This is an observational, prospective, real-world study including women with HR+/HER2– metastatic breast cancer progressing to palbociclib plus ET. Patients received either ET or chemotherapy (CT). The primary objective was the evaluation of efficacy of the different therapeutic strategies after palbociclib in terms of median progression-free survival 2. Secondary objectives were the activity of therapeutic strategies measured with the clinical benefit rate, evaluation of the parameters used for the treatment choice, and progression-free survival 1 related to palbociclib plus ET treatment. Results: Overall, 48 patients (median age 53, range 33–78 years) were included. The median progression-free survival 2 was of 5 months in the overall cohort (95% CI 4–48 months) with a statistically significant difference between the two therapeutic strategies adopted (ET versus CT, 10 months versus 5 months, respectively). Regarding secondary objectives, the clinical benefit rate was 55.2% in the CT cohort and 50% in ET. Moreover, women treated with CT had a greater number of visceral metastases and a shorter median progression-free survival 1 than patients who received ET. Conclusions: ET and CT represent two possible therapeutic alternatives for patients progressing on CDK4/6i plus ET. The choice is based on clinical parameters, with a potential preference for ET.

BackgroundIndividuals with asthma spend less time engaging in physical activity compared to the general population. Increasing physical activity has become a patient-centered goal for the treatment of treatable traits of individuals with asthma. There are data showing the possible effects of a pulmonary rehabilitation program on physical activity in obese individuals with asthma but not in normal-weight asthmatics. The objective of this feasibility study is to estimate the number of daily steps and time spent on activity in normal-weight individuals with asthma, measured before and after a pulmonary rehabilitation program.MethodsNormal-weight individuals with moderate to severe asthma were evaluated. The individuals measured their daily steps with an accelerometer for 5 days before and after a pulmonary rehabilitation program. The study was registered on ClinicalTrials.gov: NCT05486689.ResultsIn total, 17 participants were enrolled; one dropout and data on the time in activity of two individuals are missing due to a software error during the download. Data from 16 patients were analyzed. The median number of steps/day at baseline was 5,578 (25th, 75th percentiles = 4,874, 9,685) while the median activity time was 214 min (25th, 75th percentiles = 165, 239). After the rehabilitation program, the number of daily steps increased by a median value of 472 (p-value = 0.561) and the time in activity reduced by 17 min (p-value = 0.357). We also found a significant difference in quality of life, muscle strength, and exercise capacity.ConclusionsThe results of this study make it possible to calculate the sample size of future studies whose main outcome is daily steps in normal-weight individuals with asthma. The difficulties encountered in downloading time in activity data do not allow the same for this outcome.Clinical Trial RegistrationClinicalTrials.gov, identifier NCT05486689.

Few studies examining the patient outcomes of concurrent neurological manifestations during acute COVID-19 leveraged multinational cohorts of adults and children or distinguished between central and peripheral nervous system (CNS vs. PNS) involvement. Using a federated multinational network in which local clinicians and informatics experts curated the electronic health records data, we evaluated the risk of prolonged hospitalization and mortality in hospitalized COVID-19 patients from 21 healthcare systems across 7 countries. For adults, we used a federated learning approach whereby we ran Cox proportional hazard models locally at each healthcare system and performed a meta-analysis on the aggregated results to estimate the overall risk of adverse outcomes across our geographically diverse populations. For children, we reported descriptive statistics separately due to their low frequency of neurological involvement and poor outcomes. Among the 106,229 hospitalized COVID-19 patients (104,031 patients ≥18 years; 2,198 patients

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.

Abstract Long-living individuals (LLIs) escape age-related cardiovascular complications until the very last stage of life. Previous studies have shown that a Longevity-Associated Variant (LAV) of the BPI Fold Containing Family B Member 4 (BPIFB4) gene correlates with an extraordinarily prolonged life span. Moreover, delivery of the LAV-BPIFB4 gene exerted therapeutic action in murine models of atherosclerosis, limb ischemia, diabetic cardiomyopathy, and aging. We hypothesize that downregulation of BPIFB4 expression marks the severity of coronary artery disease (CAD) in human subjects, and supplementation of the LAV-BPIFB4 protects the heart from ischemia. In an elderly cohort with acute myocardial infarction (MI), patients with three-vessel CAD were characterized by lower levels of the natural logarithm (Ln) of peripheral blood BPIFB4 (p = 0.0077). The inverse association between Ln BPIFB4 and three-vessel CAD was confirmed by logistic regression adjusting for confounders (Odds Ratio = 0.81, p = 0.0054). Moreover, in infarcted mice, a single administration of LAV-BPIFB4 rescued cardiac function and vascularization. In vitro studies showed that LAV-BPIFB4 protein supplementation exerted chronotropic and inotropic actions on induced pluripotent stem cell (iPSC)-derived cardiomyocytes. In addition, LAV-BPIFB4 inhibited the pro-fibrotic phenotype in human cardiac fibroblasts. These findings provide a strong rationale and proof of concept evidence for treating CAD with the longevity BPIFB4 gene/protein.

ObjectiveThe 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 methodsTwelve 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.ResultsThe 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.DiscussionWe 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.ConclusionsWe developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.

ObjectiveParoxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations.MethodsConfounding factors, including the heterogeneous etiology of epilepsies and medication effects, hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a genome-wide association study (GWAS) on epilepsy (n = 12 803 people with epilepsy and 24 218 controls) with that from a GWAS on background EEG (n = 8425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta, and theta. We replicated our findings in an independent epilepsy replication dataset (n = 4851 people with epilepsy and 20 428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores, and Mendelian randomization analyses.ResultsOur analyses show strong genetic correlations of genetic generalized epilepsy (GGE) with background EEG oscillations, primarily in the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations.SignificanceOur results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic workup of epilepsy.

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.

Summary: Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods: We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings: Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES −1.18 years [95% CI −2.05, −0.32]), had fewer respiratory symptoms (RD −0.15 [95% CI −0.33, −0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD −0.35 [95% CI −0.64, −0.07]), lower lymphocyte count (ES −0.16 × 109/uL [95% CI −0.30, −0.01]), lower C-reactive protein (ES −28.5 mg/L [95% CI −46.3, −10.7]), and lower troponin (ES −0.14 ng/mL [95% CI −0.26, −0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES −1.6 years [95% CI −2.5, −0.8]), had less frequent SIRS (RD −0.18 [95% CI −0.30, −0.05]), lower lymphocyte count (ES −0.39 × 109/uL [95% CI −0.52, −0.25]), lower troponin (ES −0.16 ng/mL [95% CI −0.30, −0.01]) and less frequently received anticoagulation therapy (RD −0.19 [95% CI −0.37, −0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (−1.3 days [95% CI −2.3, −0.4]). Interpretation: Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time. Funding: None.

Summary: Background: Characterizing Post-Acute Sequelae of COVID (SARS-CoV-2 Infection), or PASC has been challenging due to the multitude of sub-phenotypes, temporal attributes, and definitions. Scalable characterization of PASC sub-phenotypes can enhance screening capacities, disease management, and treatment planning. Methods: We conducted a retrospective multi-centre observational cohort study, leveraging longitudinal electronic health record (EHR) data of 30,422 patients from three healthcare systems in the Consortium for the Clinical Characterization of COVID-19 by EHR (4CE). From the total cohort, we applied a deductive approach on 12,424 individuals with follow-up data and developed a distributed representation learning process for providing augmented definitions for PASC sub-phenotypes. Findings: Our framework characterized seven PASC sub-phenotypes. We estimated that on average 15.7% of the hospitalized COVID-19 patients were likely to suffer from at least one PASC symptom and almost 5.98%, on average, had multiple symptoms. Joint pain and dyspnea had the highest prevalence, with an average prevalence of 5.45% and 4.53%, respectively. Interpretation: We provided a scalable framework to every participating healthcare system for estimating PASC sub-phenotypes prevalence and temporal attributes, thus developing a unified model that characterizes augmented sub-phenotypes across the different systems. Funding: Authors are supported by National Institute of Allergy and Infectious Diseases, National Institute on Aging, National Center for Advancing Translational Sciences, National Medical Research Council, National Institute of Neurological Disorders and Stroke, European Union, National Institutes of Health, National Center for Advancing Translational Sciences.

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.

Background: Advanced breast cancer (ABC) is characterized by multidimensional clinical complexity that is usually not considered in randomized clinical trials. In the present real-life study, we investigated the link between clinical complexity and quality of life of patients with HR+/HER2– ABC treated with CDK4/6 inhibitors. Methods: We evaluated multimorbidity burden assessed with the Cumulative Illness Rating Scale (CIRS), polypharmacy and patient-reported outcomes (PROs). PROs were assessed at baseline (T0), after 3 months of therapy (T1), and at disease progression (T2) using EORTC QLC-C30 and QLQ-BR23 questionnaires. Baseline PROs and changes between T0 and T1 were evaluated amongst patients with different multimorbidity burden (CIRS 0.05). Conclusion: Multimorbidity and polypharmacy increase the clinical complexity of patients with ABC and may affect baseline PROs. The safety profile of CDK4/6 inhibitors seems to be maintained in this population. Further studies are needed to assess clinical complexity in patients with ABC. This article is part of the Tackling clinical complexity in breast cancer Special Issue: https://www.drugsincontext.com/special_issues/tackling-clinical-complexity-in-breast-cancer/

Tumour markers have no established role in the monitoring of the course of metastatic breast cancer during antineoplastic therapy, yet cancer antigen 15.3 (CA15.3) and carcinoembryonic antigen (CEA) are commonly used in clinical practice to aid in the early detection of progression of disease (PD). In our multicentre, prospective, real-life study, we enrolled 142 consecutive patients with advanced breast cancer receiving endocrine therapy in combination with a CDK4/6 inhibitor from January 2017 to October 2020; 75 patients had PD at the time of database closure. We measured serum marker concentrations at regular 4-month intervals together with radiological tumour response assessments and in cases of clinical suspicion of PD. Appropriate descriptive and inferential statistical methods were used to analyse serum marker level trends amongst prespecified subgroups and at specific time points (baseline, best radiologically documented tumour response and first detection of PD) in the subpopulation of patients with PD at the time of database closure. Notably, the median time from treatment initiation to best tumour response was 4.4 months. We evaluated the presence of an association between baseline CA15.3 and CEA levels and prespecified clinical characteristics but found no clinically meaningful correlation. We assessed marker level variations at the time of best radiologically documented disease response and PD: in the subgroup of patients who responded to treatment before progressing, we detected a statistically significant correlation with tumour marker variation between the time of best response and progression; this finding was not confirmed in the subgroup of patients that did not benefit from treatment. In conclusion, serum tumour marker flares can be useful in the early diagnosis of PD but should not be used as the sole factor prompting a change in treatment strategy without radiological confirmation. This article is part of the Tackling clinical complexity in breast cancer Special Issue: https://www.drugsincontext.com/special_issues/tackling-clinical-complexity-in-breast-cancer/

Abstract The risk profiles of post-acute sequelae of COVID-19 (PASC) have not been well characterized in multi-national settings with appropriate controls. We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients with COVID-19, 2.3 million control patients without COVID-19 in the inpatient and outpatient settings, and over 221 million diagnosis codes to systematically identify new-onset conditions enriched among patients with COVID-19 during the post-acute period. Compared to inpatient controls, inpatient COVID-19 cases were at significant risk for angina pectoris (RR 1.30, 95% CI 1.09–1.55), heart failure (RR 1.22, 95% CI 1.10–1.35), cognitive dysfunctions (RR 1.18, 95% CI 1.07–1.31), and fatigue (RR 1.18, 95% CI 1.07–1.30). Relative to outpatient controls, outpatient COVID-19 cases were at risk for pulmonary embolism (RR 2.10, 95% CI 1.58–2.76), venous embolism (RR 1.34, 95% CI 1.17–1.54), atrial fibrillation (RR 1.30, 95% CI 1.13–1.50), type 2 diabetes (RR 1.26, 95% CI 1.16–1.36) and vitamin D deficiency (RR 1.19, 95% CI 1.09–1.30). Outpatient COVID-19 cases were also at risk for loss of smell and taste (RR 2.42, 95% CI 1.90–3.06), inflammatory neuropathy (RR 1.66, 95% CI 1.21–2.27), and cognitive dysfunction (RR 1.18, 95% CI 1.04–1.33). The incidence of post-acute cardiovascular and pulmonary conditions decreased across time among inpatient cases while the incidence of cardiovascular, digestive, and metabolic conditions increased among outpatient cases. Our study, based on a federated international network, systematically identified robust conditions associated with PASC compared to control groups, underscoring the multifaceted cardiovascular and neurological phenotype profiles of PASC.

Abstract Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.

Summary: Background: While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods: A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1–365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings: Advanced age (HR 2.77, 95%CI 2.53–3.04, p

The impact of the COVID-19 pandemic involved the disruption of the processes of care and the need for immediately effective re-organizational procedures. In the context of digital health, it is of paramount importance to determine how a specific patients' population reflects into the healthcare dynamics of the hospital, to investigate how patients' sub-group/strata respond to the different care processes, in order to generate novel hypotheses regarding the most effective healthcare strategies. We present an analysis pipeline based on the heterogeneous collected data aimed at identifying the most frequent healthcare processes patterns, jointly analyzing them with demographic and physiological disease trajectories, and stratify the observed cohort on the basis of the mined patterns. This is a process-oriented pipeline which integrates process mining algorithms, and trajectory mining by topological data analyses and pseudo time approaches. Data was collected for 1,179 COVID-19 positive patients, hospitalized at the Italian Hospital “Istituti Clinici Salvatore Maugeri” in Lombardy, integrating different sources including text admission letters, EHR and hospital infrastructure data. We identified five temporal phenotypes, from laboratory values trajectories, which are characterized by statistically significant different death risk estimates. The process mining algorithms allowed splitting the data in sub-cohorts as function of the pandemic waves and of the temporal trajectories showing statistically significant differences in terms of events characteristics.

Michele Vitacca,1 Alberto Malovini,2 Bruno Balbi,3 Maria Aliani,4 Serena Cirio,5 Antonio Spanevello,6,7 Claudio Fracchia,8 Mauro Maniscalco,9 Giacomo Corica,10 Nicolino Ambrosino,8 Mara Paneroni1 1Istituti Clinici Scientifici Maugeri IRCCS, Respiratory Rehabilitation Unit of the Institute of Lumezzane, Brescia, Italy; 2Istituti Clinici Scientifici Maugeri IRCCS, Laboratory of Informatics and Systems Engineering for Clinical Research of the Institute of Pavia, Pavia, Italy; 3Istituti Clinici Scientifici Maugeri IRCCS, Respiratory Rehabilitation Unit of the Institute of Veruno, Novara, Italy; 4Istituti Clinici Scientifici Maugeri IRCCS, Respiratory Rehabilitation Unit of the Institute of Cassano Delle Murge, Bari, Italy; 5Istituti Clinici Scientifici Maugeri IRCCS, Respiratory Rehabilitation Unit of the Institute of Pavia, Pavia, Italy; 6Istituti Clinici Scientifici Maugeri IRCCS, Respiratory Rehabilitation Unit of the Institute of Tradate, Varese, Italy; 7University of Insubria, MACRO, Varese, Italy; 8Istituti Clinici Scientifici Maugeri IRCCS, Respiratory Rehabilitation Unit of the Institute of Montescano, Pavia, Italy; 9Istituti Clinici Scientifici Maugeri IRCCS, Respiratory Rehabilitation Unit of the Institute of Telese, Benevento, Italy; 10Istituti Clinici Scientifici Maugeri IRCCS, Health Directorate of the Institute of Lumezzane, Brescia, ItalyCorrespondence: Michele VitaccaIstituti Clinici Scientifici Maugeri IRCCS, Via Salvatore Maugeri, 4, Pavia 27100, ItalyEmail michele.vitacca@icsmaugeri.itBackground: 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< 0.001), correlating significantly with changes in MRC (r = 0.57, 95% CI = 0.53 to 0.59, p< 0.001). Comparing different methods of assessment, the MCID ranged from − 6.5 to − 9 points for patients without and − 7.5 to − 12 points for patients with CRF.Conclusion: The most conservative estimate of the MCID is − 9 points in patients with COPD, without and − 12 in those with CRF. This estimate may be useful in the clinical interpretation of data, particularly in response to intervention studies.Keywords: activities of daily life, breathlessness, dyspnea, chronic respiratory failure, exercise training, health related quality of life, rehabilitation

Abstract 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.

BackgroundMany 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. ObjectiveIn 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. MethodsUsing 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. ResultsData 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. ConclusionsPatients 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.

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.

Nozzle blockage in RH reactors is a serious operational problem since it can cause an asymmetric distribution of the steel flow in both the up-leg as well as the lower region of the vacuum chamber. This anomaly can alter the circulation rate in addition to affecting the erosion profile of the lower part of vacuum chamber refractory lining. In this study, the effect of nozzle obstruction on liquid circulation rate, wall shear stress, velocity profiles and flow pattern have been evaluated. In addition, refractory erosion in the vacuum chamber has been estimated through physical modeling and mathematical simulation results. Four blockage conditions were studied for different gas flow rates. There was a good agreement in physical and mathematical models results. Asymmetric flow was observed in vacuum chamber lower region in asymmetric blockage cases, which resulted in preferential wear on one chamber side in physical modeling experiments. The wall shear stress analysis in the vacuum chamber using a fluid dynamic model also indicates preferential erosion. When compared, refractory erosion results in physical modeling and shear stress in mathematical modeling presented good correlation. Keywords: RH degasser, Flow asymmetry, Refractory erosion, Modeling

Abstract 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.

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