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2. Design and evaluation of an active vineyard heating system to simulate temperature increase in the context of climate change

Author

Miguel Ángel Cirrincione, Celeste Arancibia, Deolindo L. E. Dominguez, Emiliano Jesús Malovini, and Liliana Estela Martínez

Subjects
viticulture, climate change, heating system, temperature increase, Vitis, grapevine physiology, Agriculture, Botany, QK1-989
Abstract

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.

Published
2024
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3. Relationship between maternal obesity and first-trimester TSH in women with negative anti-TPO antibodies

Author

Laura Croce, Fausta Beneventi, Federica Ripepi, Irene De Maggio, Alberto Malovini, Camilla Bellingeri, Francesca Coperchini, Marsida Teliti, Mario Rotondi, Arsenio Spinillo, and Flavia Magri

Subjects
thyroid, pregnancy, obesity, tsh, hypothyroidism, Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

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.

Published
2024
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5. Longevity-associated BPIFB4 gene counteracts the inflammatory signaling

Author

Monica Cattaneo, Andrea Baragetti, Alberto Malovini, Elena Ciaglia, Valentina Lopardo, Elena Olmastroni, Manuela Casula, Carolina Ciacci, Alberico L. Catapano, and Annibale A. Puca

Subjects
Immunologic diseases. Allergy, RC581-607, Geriatrics, RC952-954.6
Abstract

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.

Published
2024
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6. Efficacy and activity of treatments after progression from palbociclib plus endocrine therapy in patients with HR+/HER2– metastatic breast cancer: a prospective, monocentric study

Author

Raffaella Palumbo, Erica Quaquarini, Giuseppe Saltalamacchia, Alberto Malovini, Pietro Lapidari, Barbara Tagliaferri, Ludovica Mollica, Cristina Maria Teragni, Chiara Barletta, Laura Deborah Locati, and Federico Sottotetti

Subjects
endocrine resistance, metastatic breast cancer, palbociclib, post-progression, therapeutic strategies, Therapeutics. Pharmacology, RM1-950
Abstract

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.

Published
2024
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7. Evaluation of physical activity before and after respiratory rehabilitation in normal weight individuals with asthma: a feasibility study

Author

Federico Mattia Oliva, Matteo Tarasconi, Alberto Malovini, Martina Zappa, Dina Visca, and Elisabetta Zampogna

Subjects
exercise, rehabilitation, physical activity, sedentary behavior, asthma, Sports, GV557-1198.995
Abstract

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.

Published
2024
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8. Neurological diagnoses in hospitalized COVID-19 patients associated with adverse outcomes: A multinational cohort study.

Author

Meghan R Hutch, Jiyeon Son, Trang T Le, Chuan Hong, Xuan Wang, Zahra Shakeri Hossein Abad, Michele Morris, Alba Gutiérrez-Sacristán, Jeffrey G Klann, Anastasia Spiridou, Ashley Batugo, Riccardo Bellazzi, Vincent Benoit, Clara-Lea Bonzel, William A Bryant, Lorenzo Chiudinelli, Kelly Cho, Priyam Das, Tomás González González, David A Hanauer, Darren W Henderson, Yuk-Lam Ho, Ne Hooi Will Loh, Adeline Makoudjou, Simran Makwana, Alberto Malovini, Bertrand Moal, Danielle L Mowery, Antoine Neuraz, Malarkodi Jebathilagam Samayamuthu, Fernando J Sanz Vidorreta, Emily R Schriver, Petra Schubert, Jeffery Talbert, Amelia L M Tan, Byorn W L Tan, Bryce W Q Tan, Valentina Tibollo, Patric Tippman, Guillaume Verdy, William Yuan, Paul Avillach, Nils Gehlenborg, Gilbert S Omenn, Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Shyam Visweswaran, Tianxi Cai, Yuan Luo, and Zongqi Xia

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

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

Published
2024
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9. International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

Author

Weber, Griffin M, Hong, Chuan, Xia, Zongqi, Palmer, Nathan P, Avillach, Paul, L’Yi, Sehi, Keller, Mark S, Murphy, Shawn N, Gutiérrez-Sacristán, Alba, Bonzel, Clara-Lea, Serret-Larmande, Arnaud, Neuraz, Antoine, Omenn, Gilbert S, Visweswaran, Shyam, Klann, Jeffrey G, South, Andrew M, Loh, Ne Hooi Will, Cannataro, Mario, Beaulieu-Jones, Brett K, Bellazzi, Riccardo, Agapito, Giuseppe, Alessiani, Mario, Aronow, Bruce J, Bell, Douglas S, Benoit, Vincent, Bourgeois, Florence T, Chiovato, Luca, Cho, Kelly, Dagliati, Arianna, DuVall, Scott L, Barrio, Noelia García, Hanauer, David A, Ho, Yuk-Lam, Holmes, John H, Issitt, Richard W, Liu, Molei, Luo, Yuan, Lynch, Kristine E, Maidlow, Sarah E, Malovini, Alberto, Mandl, Kenneth D, Mao, Chengsheng, Matheny, Michael E, Moore, Jason H, Morris, Jeffrey S, Morris, Michele, Mowery, Danielle L, Ngiam, Kee Yuan, Patel, Lav P, Pedrera-Jimenez, Miguel, Ramoni, Rachel B, Schriver, Emily R, Schubert, Petra, Balazote, Pablo Serrano, Spiridou, Anastasia, Tan, Amelia LM, Tan, Byorn WL, Tibollo, Valentina, Torti, Carlo, Trecarichi, Enrico M, Wang, Xuan, Kohane, Isaac S, Cai, Tianxi, and Brat, Gabriel A

Subjects
Health Services and Systems, Health Sciences, Basic Behavioral and Social Science, Behavioral and Social Science, Good Health and Well Being, Consortium for Clinical Characterization of COVID-19 by EHR, Health services and systems
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.

Published
2022

11. BPIFB4 and its longevity-associated haplotype protect from cardiac ischemia in humans and mice

Author

Monica Cattaneo, Aneta Aleksova, Alberto Malovini, Elisa Avolio, Anita Thomas, Valeria Vincenza Alvino, Michael Kilcooley, Marie Pieronne-Deperrois, Antoine Ouvrard-Pascaud, Anna Maciag, Gaia Spinetti, Sophie Kussauer, Heiko Lemcke, Anna Skorska, Praveen Vasudevan, Stefania Castiglione, Angela Raucci, Robert David, Vincent Richard, Antonio Paolo Beltrami, Paolo Madeddu, and Annibale Alessandro Puca

Subjects
Cytology, QH573-671
Abstract

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.

Published
2023
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12. Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data

Author

Klann, Jeffrey G, Estiri, Hossein, Weber, Griffin M, Moal, Bertrand, Avillach, Paul, Hong, Chuan, Tan, Amelia LM, Beaulieu-Jones, Brett K, Castro, Victor, Maulhardt, Thomas, Geva, Alon, Malovini, Alberto, South, Andrew M, Visweswaran, Shyam, Morris, Michele, Samayamuthu, Malarkodi J, Omenn, Gilbert S, Ngiam, Kee Yuan, Mandl, Kenneth D, Boeker, Martin, Olson, Karen L, Mowery, Danielle L, Follett, Robert W, Hanauer, David A, Bellazzi, Riccardo, Moore, Jason H, Loh, Ne-Hooi Will, Bell, Douglas S, Wagholikar, Kavishwar B, Chiovato, Luca, Tibollo, Valentina, Rieg, Siegbert, Li, Anthony LLJ, Jouhet, Vianney, Schriver, Emily, Xia, Zongqi, Hutch, Meghan, Luo, Yuan, Kohane, Isaac S, EHR, The Consortium for Clinical Characterization of COVID-19 by, Brat, Gabriel A, and Murphy, Shawn N

Subjects
Health Services and Systems, Health Sciences, Patient Safety, HIV/AIDS, Good Health and Well Being, COVID-19, Electronic Health Records, Hospitalization, Humans, Machine Learning, Prognosis, ROC Curve, Sensitivity and Specificity, Severity of Illness Index, novel coronavirus, disease severity, computable phenotype, medical informatics, data networking, data interoperability, Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Information and Computing Sciences, Engineering, Medical and Health Sciences, Medical Informatics, Biomedical and clinical sciences, Health sciences, Information and computing sciences
Abstract

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.

Published
2021

13. Shared genetic basis between genetic generalized epilepsy and background electroencephalographic oscillations

Author

Stevelink, Remi, Luykx, Jurjen J, Lin, Bochao D, Leu, Costin, Lal, Dennis, Smith, Alexander W, Schijven, Dick, Carpay, Johannes A, Rademaker, Koen, Baldez, Roiza A Rodrigues, Devinsky, Orrin, Braun, Kees PJ, Jansen, Floor E, Smit, Dirk JA, Koeleman, Bobby PC, Abou‐Khalil, Bassel, Auce, Pauls, Avbersek, Andreja, Bahlo, Melanie, Balding, David J, Bast, Thomas, Baum, Larry, Becker, Albert J, Becker, Felicitas, Berghuis, Bianca, Berkovic, Samuel F, Boysen, Katja E, Bradfield, Jonathan P, Brody, Lawrence C, Buono, Russell J, Campbell, Ellen, Cascino, Gregory D, Catarino, Claudia B, Cavalleri, Gianpiero L, Cherny, Stacey S, Chinthapalli, Krishna, Coffey, Alison J, Compston, Alastair, Coppola, Antonietta, Cossette, Patrick, Craig, John J, de Haan, Gerrit‐Jan, De Jonghe, Peter, de Kovel, Carolien GF, Delanty, Norman, Depondt, Chantal, Dlugos, Dennis J, Doherty, Colin P, Elger, Christian E, Eriksson, Johan G, Ferraro, Thomas N, Feucht, Martha, Francis, Ben, Franke, Andre, French, Jacqueline A, Freytag, Saskia, Gaus, Verena, Geller, Eric B, Gieger, Christian, Glauser, Tracy, Glynn, Simon, Goldstein, David B, Gui, Hongsheng, Guo, Youling, Haas, Kevin F, Hakonarson, Hakon, Hallmann, Kerstin, Haut, Sheryl, Heinzen, Erin L, Helbig, Ingo, Hengsbach, Christian, Hjalgrim, Helle, Iacomino, Michele, Ingason, Andrés, Jamnadas‐Khoda, Jennifer, Johnson, Michael R, Kälviäinen, Reetta, Kantanen, Anne‐Mari, Kasperavičiūte, Dalia, Trenite, Dorothee Kasteleijn‐Nolst, Kirsch, Heidi E, Knowlton, Robert C, Krause, Roland, Krenn, Martin, Kunz, Wolfram S, Kuzniecky, Ruben, Kwan, Patrick, Lau, Yu‐Lung, Lehesjoki, Anna‐Elina, Lerche, Holger, Lieb, Wolfgang, Lindhout, Dick, Lo, Warren D, Lopes‐Cendes, Iscia, Lowenstein, Daniel H, Malovini, Alberto, Marson, Anthony G, Mayer, Thomas, McCormack, Mark, and Mills, James L

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Genetics, Brain Disorders, Clinical Research, Human Genome, Neurodegenerative, Epilepsy, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Algorithms, Beta Rhythm, Cohort Studies, Databases, Factual, Electroencephalography, Epilepsy, Generalized, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Mendelian Randomization Analysis, Risk Assessment, Theta Rhythm, beta power, EEG, generalized epilepsy, GGE, oscillations, PRS, International League Against Epilepsy Consortium on Complex Epilepsies, Epi25 Collaborative, Neurology & Neurosurgery, Clinical sciences
Abstract

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.

Published
2021

16. Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortium

Author

Aaron, James R., Adam, Atif, Agapito, Giuseppe, Albayrak, Adem, Albi, Giuseppe, Alessiani, Mario, Alloni, Anna, Amendola, Danilo F., Angoulvant, François, Anthony, Li LLJ., Aronow, Bruce J., Ashraf, Fatima, Atz, Andrew, Avillach, Paul, Panickan, Vidul Ayakulangara, Azevedo, Paula S., Badenes, Rafael, Balshi, James, Batugo, Ashley, Beaulieu-Jones, Brendin R., Beaulieu-Jones, Brett K., Bell, Douglas S., Bellasi, Antonio, Bellazzi, Riccardo, Benoit, Vincent, Beraghi, Michele, Bernal-Sobrino, José Luis, Bernaux, Mélodie, Bey, Romain, Bhatnagar, Surbhi, Blanco-Martínez, Alvar, Boeker, Martin, Bonzel, Clara-Lea, Booth, John, Bosari, Silvano, Bourgeois, Florence T., Bradford, Robert L., Brat, Gabriel A., Bréant, Stéphane, Brown, Nicholas W., Bruno, Raffaele, Bryant, William A., Bucalo, Mauro, Bucholz, Emily, Burgun, Anita, Cai, Tianxi, Cannataro, Mario, Carmona, Aldo, Cattelan, Anna Maria, Caucheteux, Charlotte, Champ, Julien, Chen, Jin, Chen, Krista Y., Chiovato, Luca, Chiudinelli, Lorenzo, Cho, Kelly, Cimino, James J., Colicchio, Tiago K., Cormont, Sylvie, Cossin, Sébastien, Craig, Jean B., Cruz-Bermúdez, Juan Luis, Cruz-Rojo, Jaime, Dagliati, Arianna, Daniar, Mohamad, Daniel, Christel, Das, Priyam, Devkota, Batsal, Dionne, Audrey, Duan, Rui, Dubiel, Julien, DuVall, Scott L., Esteve, Loic, Estiri, Hossein, Fan, Shirley, Follett, Robert W., Ganslandt, Thomas, García-Barrio, Noelia, Garmire, Lana X., Gehlenborg, Nils, Getzen, Emily J., Geva, Alon, Goh, Rachel SJ., González, Tomás González, Gradinger, Tobias, Gramfort, Alexandre, Griffier, Romain, Griffon, Nicolas, Grisel, Olivier, Gutiérrez-Sacristán, Alba, Guzzi, Pietro H., Han, Larry, Hanauer, David A., Haverkamp, Christian, Hazard, Derek Y., He, Bing, Henderson, Darren W., Hilka, Martin, Ho, Yuk-Lam, Holmes, John H., Honerlaw, Jacqueline P., Hong, Chuan, Huling, Kenneth M., Hutch, Meghan R., Issitt, Richard W., Jannot, Anne Sophie, Jouhet, Vianney, Kainth, Mundeep K., Kate, Kernan F., Kavuluru, Ramakanth, Keller, Mark S., Kennedy, Chris J., Kernan, Kate F., Key, Daniel A., Kirchoff, Katie, Klann, Jeffrey G., Kohane, Isaac S., Krantz, Ian D., Kraska, Detlef, Krishnamurthy, Ashok K., L'Yi, Sehi, Leblanc, Judith, Lemaitre, Guillaume, Lenert, Leslie, Leprovost, Damien, Liu, Molei, Will Loh, Ne Hooi, Long, Qi, Lozano-Zahonero, Sara, Luo, Yuan, Lynch, Kristine E., Mahmood, Sadiqa, Maidlow, Sarah E., Makoudjou, Adeline, Makwana, Simran, Malovini, Alberto, Mandl, Kenneth D., Mao, Chengsheng, Maram, Anupama, Maripuri, Monika, Martel, Patricia, Martins, Marcelo R., Marwaha, Jayson S., Masino, Aaron J., Mazzitelli, Maria, Mazzotti, Diego R., Mensch, Arthur, Milano, Marianna, Minicucci, Marcos F., Moal, Bertrand, Ahooyi, Taha Mohseni, Moore, Jason H., Moraleda, Cinta, Morris, Jeffrey S., Morris, Michele, Moshal, Karyn L., Mousavi, Sajad, Mowery, Danielle L., Murad, Douglas A., Murphy, Shawn N., Naughton, Thomas P., Breda Neto, Carlos Tadeu, Neuraz, Antoine, Newburger, Jane, Ngiam, Kee Yuan, Njoroge, Wanjiku FM., Norman, James B., Obeid, Jihad, Okoshi, Marina P., Olson, Karen L., Omenn, Gilbert S., Orlova, Nina, Ostasiewski, Brian D., Palmer, Nathan P., Paris, Nicolas, Patel, Lav P., Pedrera-Jiménez, Miguel, Pfaff, Ashley C., Pfaff, Emily R., Pillion, Danielle, Pizzimenti, Sara, Priya, Tanu, Prokosch, Hans U., Prudente, Robson A., Prunotto, Andrea, Quirós-González, Víctor, Ramoni, Rachel B., Raskin, Maryna, Rieg, Siegbert, Roig-Domínguez, Gustavo, Rojo, Pablo, Romero-Garcia, Nekane, Rubio-Mayo, Paula, Sacchi, Paolo, Sáez, Carlos, Salamanca, Elisa, Samayamuthu, Malarkodi Jebathilagam, Sanchez-Pinto, L. Nelson, Sandrin, Arnaud, Santhanam, Nandhini, Santos, Janaina C.C., Sanz Vidorreta, Fernando J., Savino, Maria, Schriver, Emily R., Schubert, Petra, Schuettler, Juergen, Scudeller, Luigia, Sebire, Neil J., Serrano-Balazote, Pablo, Serre, Patricia, Serret-Larmande, Arnaud, Shah, Mohsin A., Hossein Abad, Zahra Shakeri, Silvio, Domenick, Sliz, Piotr, Son, Jiyeon, Sonday, Charles, South, Andrew M., Sperotto, Francesca, Spiridou, Anastasia, Strasser, Zachary H., Tan, Amelia LM., Tan, Bryce W.Q., Tan, Byorn W.L., Tanni, Suzana E., Taylor, Deanne M., Terriza-Torres, Ana I., Tibollo, Valentina, Tippmann, Patric, Toh, Emma MS., Torti, Carlo, Trecarichi, Enrico M., Vallejos, Andrew K., Varoquaux, Gael, Vella, Margaret E., Verdy, Guillaume, Vie, Jill-Jênn, Visweswaran, Shyam, Vitacca, Michele, Wagholikar, Kavishwar B., Waitman, Lemuel R., Wang, Xuan, Wassermann, Demian, Weber, Griffin M., Wolkewitz, Martin, Wong, Scott, Xia, Zongqi, Xiong, Xin, Ye, Ye, Yehya, Nadir, Yuan, William, Zachariasse, Joany M., Zahner, Janet J., Zambelli, Alberto, Zhang, Harrison G., Zöller, Daniela, Zuccaro, Valentina, Zucco, Chiara, Li, Xiudi, Rofeberg, Valerie N., Elias, Matthew D., Laird-Gion, Jessica, and Newburger, Jane W.

Published
2023
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17. Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort study

Author

Aaron, James R., Agapito, Giuseppe, Albayrak, Adem, Albi, Giuseppe, Alessiani, Mario, Alloni, Anna, Amendola, Danilo F., François Angoulvant, Anthony, Li L.L.J., Aronow, Bruce J., Ashraf, Fatima, Atz, Andrew, Avillach, Paul, Azevedo, Paula S., Balshi, James, Beaulieu-Jones, Brett K., Bell, Douglas S., Bellasi, Antonio, Bellazzi, Riccardo, Benoit, Vincent, Beraghi, Michele, Bernal-Sobrino, José Luis, Bernaux, Mélodie, Bey, Romain, Bhatnagar, Surbhi, Blanco-Martínez, Alvar, Bonzel, Clara-Lea, Booth, John, Bosari, Silvano, Bourgeois, Florence T., Bradford, Robert L., Brat, Gabriel A., Bréant, Stéphane, Brown, Nicholas W., Bruno, Raffaele, Bryant, William A., Bucalo, Mauro, Bucholz, Emily, Burgun, Anita, Cai, Tianxi, Cannataro, Mario, Carmona, Aldo, Caucheteux, Charlotte, Champ, Julien, Chen, Jin, Chen, Krista Y., Chiovato, Luca, Chiudinelli, Lorenzo, Cho, Kelly, Cimino, James J., Colicchio, Tiago K., Cormont, Sylvie, Cossin, Sébastien, Craig, Jean B., Cruz-Bermúdez, Juan Luis, Cruz-Rojo, Jaime, Dagliati, Arianna, Daniar, Mohamad, Daniel, Christel, Das, Priyam, Devkota, Batsal, Dionne, Audrey, Duan, Rui, Dubiel, Julien, DuVall, Scott L., Esteve, Loic, Estiri, Hossein, Fan, Shirley, Follett, Robert W., Ganslandt, Thomas, Barrio, Noelia García, Garmire, Lana X., Gehlenborg, Nils, Getzen, Emily J., Geva, Alon, Gradinger, Tobias, Gramfort, Alexandre, Griffier, Romain, Griffon, Nicolas, Grisel, Olivier, Gutiérrez-Sacristán, Alba, Han, Larry, Hanauer, David A., Haverkamp, Christian, Hazard, Derek Y., He, Bing, Henderson, Darren W., Hilka, Martin, Ho, Yuk-Lam, Holmes, John H., Hong, Chuan, Huling, Kenneth M., Hutch, Meghan R., Issitt, Richard W., Jannot, Anne Sophie, Jouhet, Vianney, Kavuluru, Ramakanth, Keller, Mark S., Kennedy, Chris J., Key, Daniel A., Kirchoff, Katie, Klann, Jeffrey G., Kohane, Isaac S., Krantz, Ian D., Kraska, Detlef, Krishnamurthy, Ashok K., L'Yi, Sehi, Le, Trang T., Leblanc, Judith, Lemaitre, Guillaume, Lenert, Leslie, Leprovost, Damien, Liu, Molei, Will Loh, Ne Hooi, Long, Qi, Lozano-Zahonero, Sara, Luo, Yuan, Lynch, Kristine E., Mahmood, Sadiqa, Maidlow, Sarah E., Makoudjou, Adeline, Malovini, Alberto, Mandl, Kenneth D., Mao, Chengsheng, Maram, Anupama, Martel, Patricia, Martins, Marcelo R., Marwaha, Jayson S., Masino, Aaron J., Mazzitelli, Maria, Mensch, Arthur, Milano, Marianna, Minicucci, Marcos F., Moal, Bertrand, Ahooyi, Taha Mohseni, Moore, Jason H., Moraleda, Cinta, Morris, Jeffrey S., Morris, Michele, Moshal, Karyn L., Mousavi, Sajad, Mowery, Danielle L., Murad, Douglas A., Murphy, Shawn N., Naughton, Thomas P., Breda Neto, Carlos Tadeu, Neuraz, Antoine, Newburger, Jane, Ngiam, Kee Yuan, Njoroge, Wanjiku F.M., Norman, James B., Obeid, Jihad, Okoshi, Marina P., Olson, Karen L., Omenn, Gilbert S., Orlova, Nina, Ostasiewski, Brian D., Palmer, Nathan P., Paris, Nicolas, Patel, Lav P., Pedrera-Jiménez, Miguel, Pfaff, Emily R., Pfaff, Ashley C., Pillion, Danielle, Pizzimenti, Sara, Prokosch, Hans U., Prudente, Robson A., Prunotto, Andrea, Quirós-González, Víctor, Ramoni, Rachel B., Raskin, Maryna, Rieg, Siegbert, Roig-Domínguez, Gustavo, Rojo, Pablo, Rubio-Mayo, Paula, Sacchi, Paolo, Sáez, Carlos, Salamanca, Elisa, Samayamuthu, Malarkodi Jebathilagam, Sanchez-Pinto, L. Nelson, Sandrin, Arnaud, Santhanam, Nandhini, Santos, Janaina C.C., Sanz Vidorreta, Fernando J., Savino, Maria, Schriver, Emily R., Schubert, Petra, Schuettler, Juergen, Scudeller, Luigia, Sebire, Neil J., Serrano-Balazote, Pablo, Serre, Patricia, Serret-Larmande, Arnaud, Shah, Mohsin, Hossein Abad, Zahra Shakeri, Silvio, Domenick, Sliz, Piotr, Son, Jiyeon, Sonday, Charles, South, Andrew M., Spiridou, Anastasia, Strasser, Zachary H., Tan, Amelia L.M., Tan, Bryce W.Q., Tan, Byorn W.L., Tanni, Suzana E., Taylor, Deanne M., Terriza-Torres, Ana I., Tibollo, Valentina, Tippmann, Patric, Toh, Emma M.S., Torti, Carlo, Trecarichi, Enrico M., Tseng, Yi-Ju, Vallejos, Andrew K., Varoquaux, Gael, Vella, Margaret E., Verdy, Guillaume, Vie, Jill-Jênn, Visweswaran, Shyam, Vitacca, Michele, Wagholikar, Kavishwar B., Waitman, Lemuel R., Wang, Xuan, Wassermann, Demian, Weber, Griffin M., Wolkewitz, Martin, Wong, Scott, Xia, Zongqi, Xiong, Xin, Ye, Ye, Yehya, Nadir, Yuan, William, Zambelli, Alberto, Zhang, Harrison G., Zo¨ller, Daniela, Zuccaro, Valentina, Zucco, Chiara, Mesa, Rebecca, and Verdy, Guillame

Published
2023
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18. Prevalence of exercise-induced oxygen desaturation after recovery from SARS-CoV-2 pneumonia and use of lung ultrasound to predict need for pulmonary rehabilitation

Author

A. Carlucci, M. Paneroni, M. Carotenuto, E. Bertella, S. Cirio, A. Gandolfo, C. Simonelli, M. Vigna, C. Lastoria, A. Malovini, B. Fusar Poli, and M. Vitacca

Subjects
COVID-19 Pneumonia, Acute respiratory failure, 6-min walking test, Lung ultrasound, desaturation, Diseases of the respiratory system, RC705-779
Abstract

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.

Published
2023
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19. Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortiumResearch in context

Author

Francesca Sperotto, Alba Gutiérrez-Sacristán, Simran Makwana, Xiudi Li, Valerie N. Rofeberg, Tianxi Cai, Florence T. Bourgeois, Gilbert S. Omenn, David A. Hanauer, Carlos Sáez, Clara-Lea Bonzel, Emily Bucholz, Audrey Dionne, Matthew D. Elias, Noelia García-Barrio, Tomás González González, Richard W. Issitt, Kate F. Kernan, Jessica Laird-Gion, Sarah E. Maidlow, Kenneth D. Mandl, Taha Mohseni Ahooyi, Cinta Moraleda, Michele Morris, Karyn L. Moshal, Miguel Pedrera-Jiménez, Mohsin A. Shah, Andrew M. South, Anastasia Spiridou, Deanne M. Taylor, Guillaume Verdy, Shyam Visweswaran, Xuan Wang, Zongqi Xia, Joany M. Zachariasse, Jane W. Newburger, Paul Avillach, James R. Aaron, Atif Adam, Giuseppe Agapito, Adem Albayrak, Giuseppe Albi, Mario Alessiani, Anna Alloni, Danilo F. Amendola, François Angoulvant, Li LLJ. Anthony, Bruce J. Aronow, Fatima Ashraf, Andrew Atz, Vidul Ayakulangara Panickan, Paula S. Azevedo, Rafael Badenes, James Balshi, Ashley Batugo, Brendin R. Beaulieu-Jones, Brett K. Beaulieu-Jones, Douglas S. Bell, Antonio Bellasi, Riccardo Bellazzi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Blanco-Martínez, Martin Boeker, John Booth, Silvano Bosari, Robert L. Bradford, Gabriel A. Brat, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Anita Burgun, Mario Cannataro, Aldo Carmona, Anna Maria Cattelan, Charlotte Caucheteux, Julien Champ, Jin Chen, Krista Y. Chen, Luca Chiovato, Lorenzo Chiudinelli, Kelly Cho, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Arianna Dagliati, Mohamad Daniar, Christel Daniel, Priyam Das, Batsal Devkota, Rui Duan, Julien Dubiel, Scott L. DuVall, Loic Esteve, Hossein Estiri, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Rachel SJ. Goh, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Pietro H. Guzzi, Larry Han, Christian Haverkamp, Derek Y. Hazard, Bing He, Darren W. Henderson, Martin Hilka, Yuk-Lam Ho, John H. Holmes, Jacqueline P. Honerlaw, Chuan Hong, Kenneth M. Huling, Meghan R. Hutch, Anne Sophie Jannot, Vianney Jouhet, Mundeep K. Kainth, Kernan F. Kate, Ramakanth Kavuluru, Mark S. Keller, Chris J. Kennedy, Daniel A. Key, Katie Kirchoff, Jeffrey G. Klann, Isaac S. Kohane, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Sehi L'Yi, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Ne Hooi Will Loh, Qi Long, Sara Lozano-Zahonero, Yuan Luo, Kristine E. Lynch, Sadiqa Mahmood, Adeline Makoudjou, Alberto Malovini, Chengsheng Mao, Anupama Maram, Monika Maripuri, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Diego R. Mazzotti, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Bertrand Moal, Jason H. Moore, Jeffrey S. Morris, Sajad Mousavi, Danielle L. Mowery, Douglas A. Murad, Shawn N. Murphy, Thomas P. Naughton, Carlos Tadeu Breda Neto, Antoine Neuraz, Jane Newburger, Kee Yuan Ngiam, Wanjiku FM. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Nina Orlova, Brian D. Ostasiewski, Nathan P. Palmer, Nicolas Paris, Lav P. Patel, Ashley C. Pfaff, Emily R. Pfaff, Danielle Pillion, Sara Pizzimenti, Tanu Priya, Hans U. Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Nekane Romero-Garcia, Paula Rubio-Mayo, Paolo Sacchi, Elisa Salamanca, Malarkodi Jebathilagam Samayamuthu, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C.C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Emily R. Schriver, Petra Schubert, Juergen Schuettler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Zahra Shakeri Hossein Abad, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Zachary H. Strasser, Amelia LM. Tan, Bryce W.Q. Tan, Byorn W.L. Tan, Suzana E. Tanni, Ana I. Terriza-Torres, Valentina Tibollo, Patric Tippmann, Emma MS. Toh, Carlo Torti, Enrico M. Trecarichi, Andrew K. Vallejos, Gael Varoquaux, Margaret E. Vella, Jill-Jênn Vie, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Demian Wassermann, Griffin M. Weber, Martin Wolkewitz, Scott Wong, Xin Xiong, Ye Ye, Nadir Yehya, William Yuan, Janet J. Zahner, Alberto Zambelli, Harrison G. Zhang, Daniela Zöller, Valentina Zuccaro, and Chiara Zucco

Subjects
Multisystem inflammatory syndrome, Paediatric inflammatory multisystem syndrome, COVID-19, SARS-CoV-2, Variants, Pediatrics, Medicine (General), R5-920
Abstract

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.

Published
2023
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20. Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort studyResearch in Context

Author

Arianna Dagliati, Zachary H. Strasser, Zahra Shakeri Hossein Abad, Jeffrey G. Klann, Kavishwar B. Wagholikar, Rebecca Mesa, Shyam Visweswaran, Michele Morris, Yuan Luo, Darren W. Henderson, Malarkodi Jebathilagam Samayamuthu, Bryce W.Q. Tan, Guillame Verdy, Gilbert S. Omenn, Zongqi Xia, Riccardo Bellazzi, Shawn N. Murphy, John H. Holmes, Hossein Estiri, James R. Aaron, Giuseppe Agapito, Adem Albayrak, Giuseppe Albi, Mario Alessiani, Anna Alloni, Danilo F. Amendola, François Angoulvant, Li L.L.J. Anthony, Bruce J. Aronow, Fatima Ashraf, Andrew Atz, Paul Avillach, Paula S. Azevedo, James Balshi, Brett K. Beaulieu-Jones, Douglas S. Bell, Antonio Bellasi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Blanco-Martínez, Clara-Lea Bonzel, John Booth, Silvano Bosari, Florence T. Bourgeois, Robert L. Bradford, Gabriel A. Brat, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Emily Bucholz, Anita Burgun, Tianxi Cai, Mario Cannataro, Aldo Carmona, Charlotte Caucheteux, Julien Champ, Jin Chen, Krista Y. Chen, Luca Chiovato, Lorenzo Chiudinelli, Kelly Cho, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Mohamad Daniar, Christel Daniel, Priyam Das, Batsal Devkota, Audrey Dionne, Rui Duan, Julien Dubiel, Scott L. DuVall, Loic Esteve, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Noelia García- Barrio, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Alba Gutiérrez-Sacristán, Larry Han, David A. Hanauer, Christian Haverkamp, Derek Y. Hazard, Bing He, Martin Hilka, Yuk-Lam Ho, Chuan Hong, Kenneth M. Huling, Meghan R. Hutch, Richard W. Issitt, Anne Sophie Jannot, Vianney Jouhet, Ramakanth Kavuluru, Mark S. Keller, Chris J. Kennedy, Daniel A. Key, Katie Kirchoff, Isaac S. Kohane, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Sehi L'Yi, Trang T. Le, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Ne Hooi Will Loh, Qi Long, Sara Lozano-Zahonero, Kristine E. Lynch, Sadiqa Mahmood, Sarah E. Maidlow, Adeline Makoudjou, Alberto Malovini, Kenneth D. Mandl, Chengsheng Mao, Anupama Maram, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Bertrand Moal, Taha Mohseni Ahooyi, Jason H. Moore, Cinta Moraleda, Jeffrey S. Morris, Karyn L. Moshal, Sajad Mousavi, Danielle L. Mowery, Douglas A. Murad, Thomas P. Naughton, Carlos Tadeu Breda Neto, Antoine Neuraz, Jane Newburger, Kee Yuan Ngiam, Wanjiku F.M. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Nina Orlova, Brian D. Ostasiewski, Nathan P. Palmer, Nicolas Paris, Lav P. Patel, Miguel Pedrera-Jiménez, Emily R. Pfaff, Ashley C. Pfaff, Danielle Pillion, Sara Pizzimenti, Hans U. Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Paula Rubio-Mayo, Paolo Sacchi, Carlos Sáez, Elisa Salamanca, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C.C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Emily R. Schriver, Petra Schubert, Juergen Schuettler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Mohsin Shah, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Andrew M. South, Anastasia Spiridou, Amelia L.M. Tan, Byorn W.L. Tan, Suzana E. Tanni, Deanne M. Taylor, Ana I. Terriza-Torres, Valentina Tibollo, Patric Tippmann, Emma M.S. Toh, Carlo Torti, Enrico M. Trecarichi, Yi-Ju Tseng, Andrew K. Vallejos, Gael Varoquaux, Margaret E. Vella, Guillaume Verdy, Jill-Jênn Vie, Michele Vitacca, Lemuel R. Waitman, Xuan Wang, Demian Wassermann, Griffin M. Weber, Martin Wolkewitz, Scott Wong, Xin Xiong, Ye Ye, Nadir Yehya, William Yuan, Alberto Zambelli, Harrison G. Zhang, Daniela Zo¨ller, Valentina Zuccaro, and Chiara Zucco

Subjects
Post-acute sequelae of SARS-CoV-2, PASC, COVID-19, SARS-CoV-2, Electronic health records, Medicine (General), R5-920
Abstract

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.

Published
2023
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21. BPIFB4 and its longevity-associated haplotype protect from cardiac ischemia in humans and mice

Author

Cattaneo, Monica, Aleksova, Aneta, Malovini, Alberto, Avolio, Elisa, Thomas, Anita, Alvino, Valeria Vincenza, Kilcooley, Michael, Pieronne-Deperrois, Marie, Ouvrard-Pascaud, Antoine, Maciag, Anna, Spinetti, Gaia, Kussauer, Sophie, Lemcke, Heiko, Skorska, Anna, Vasudevan, Praveen, Castiglione, Stefania, Raucci, Angela, David, Robert, Richard, Vincent, Beltrami, Antonio Paolo, Madeddu, Paolo, and Puca, Annibale Alessandro

Published
2023
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22. International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium

Author

Brat, Gabriel A, Weber, Griffin M, Gehlenborg, Nils, Avillach, Paul, Palmer, Nathan P, Chiovato, Luca, Cimino, James, Waitman, Lemuel R, Omenn, Gilbert S, Malovini, Alberto, Moore, Jason H, Beaulieu-Jones, Brett K, Tibollo, Valentina, Murphy, Shawn N, Yi, Sehi L’, Keller, Mark S, Bellazzi, Riccardo, Hanauer, David A, Serret-Larmande, Arnaud, Gutierrez-Sacristan, Alba, Holmes, John J, Bell, Douglas S, Mandl, Kenneth D, Follett, Robert W, Klann, Jeffrey G, Murad, Douglas A, Scudeller, Luigia, Bucalo, Mauro, Kirchoff, Katie, Craig, Jean, Obeid, Jihad, Jouhet, Vianney, Griffier, Romain, Cossin, Sebastien, Moal, Bertrand, Patel, Lav P, Bellasi, Antonio, Prokosch, Hans U, Kraska, Detlef, Sliz, Piotr, Tan, Amelia LM, Ngiam, Kee Yuan, Zambelli, Alberto, Mowery, Danielle L, Schiver, Emily, Devkota, Batsal, Bradford, Robert L, Daniar, Mohamad, Daniel, Christel, Benoit, Vincent, Bey, Romain, Paris, Nicolas, Serre, Patricia, Orlova, Nina, Dubiel, Julien, Hilka, Martin, Jannot, Anne Sophie, Breant, Stephane, Leblanc, Judith, Griffon, Nicolas, Burgun, Anita, Bernaux, Melodie, Sandrin, Arnaud, Salamanca, Elisa, Cormont, Sylvie, Ganslandt, Thomas, Gradinger, Tobias, Champ, Julien, Boeker, Martin, Martel, Patricia, Esteve, Loic, Gramfort, Alexandre, Grisel, Olivier, Leprovost, Damien, Moreau, Thomas, Varoquaux, Gael, Vie, Jill-Jênn, Wassermann, Demian, Mensch, Arthur, Caucheteux, Charlotte, Haverkamp, Christian, Lemaitre, Guillaume, Bosari, Silvano, Krantz, Ian D, South, Andrew, Cai, Tianxi, and Kohane, Isaac S

Subjects
Health Services and Systems, Health Sciences, Good Health and Well Being, Databases, Outcomes research, Viral infection, Health services and systems
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.

Published
2020

23. Health-related quality of life and clinical complexity of a real-life cohort of patients with advanced HR+/HER2– breast cancer treated with CDK4/6 inhibitors and endocrine therapy

Author

Barbara Tagliaferri, Ludovica Mollica, Raffella Palumbo, Claudia Leli, Alberto Malovini, Matteo Terzaghi, Erica Quaquarini, Cristina Teragni, Stefano Maccarone, Andrea Premoli, and Federico Sottotetti

Subjects
breast cancer, cdk4/6 inhibitors, clinical complexity, comorbidities, polypharmacy, quality of life, real-life population, Therapeutics. Pharmacology, RM1-950
Abstract

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/

Published
2023
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26. The prognostic role of variations in tumour markers (CEA, CA15.3) in patients with metastatic breast cancer treated with CDK4/6 inhibitors

Author

Federico Sottotetti, Elisa Ferraris, Barbara Tagliaferri, Raffaella Palumbo, Erica Quaquarini, Cristina Teragni, Emanuela Balletti, Claudia Leli, Andrea Premoli, Ludovica Mollica, Silvia Puglisi, Silvia Sardi, Alberto Malovini, Paolo Pedrazzoli, and Antonio Bernardo

Subjects
breast cancer, cdk4/6 inhibitors, tumour markers, Therapeutics. Pharmacology, RM1-950
Abstract

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/

Published
2022
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27. SurvMaximin: Robust federated approach to transporting survival risk prediction models

Author

Wang, Xuan, Zhang, Harrison G., Xiong, Xin, Hong, Chuan, Weber, Griffin M., Brat, Gabriel A., Bonzel, Clara-Lea, Luo, Yuan, Duan, Rui, Palmer, Nathan P., Hutch, Meghan R., Gutiérrez-Sacristán, Alba, Bellazzi, Riccardo, Chiovato, Luca, Cho, Kelly, Dagliati, Arianna, Estiri, Hossein, García-Barrio, Noelia, Griffier, Romain, Hanauer, David A., Ho, Yuk-Lam, Holmes, John H., Keller, Mark S., Klann MEng, Jeffrey G., L'Yi, Sehi, Lozano-Zahonero, Sara, Maidlow, Sarah E., Makoudjou, Adeline, Malovini, Alberto, Moal, Bertrand, Moore, Jason H., Morris, Michele, Mowery, Danielle L., Murphy, Shawn N, Neuraz, Antoine, Yuan Ngiam, Kee, Omenn, Gilbert S., Patel, Lav P., Pedrera-Jiménez, Miguel, Prunotto, Andrea, Jebathilagam Samayamuthu, Malarkodi, Sanz Vidorreta, Fernando J, Schriver, Emily R., Schubert, Petra, Serrano-Balazote, Pablo, South, Andrew M., Tan, Amelia L.M., Tan, Byorn W.L., Tibollo, Valentina, Tippmann, Patric, Visweswaran, Shyam, Xia, Zongqi, Yuan, William, Zöller, Daniela, Kohane, Isaac S., Avillach, Paul, Guo, Zijian, and Cai, Tianxi

Published
2022
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28. International electronic health record-derived post-acute sequelae profiles of COVID-19 patients

Author

Harrison G. Zhang, Arianna Dagliati, Zahra Shakeri Hossein Abad, Xin Xiong, Clara-Lea Bonzel, Zongqi Xia, Bryce W. Q. Tan, Paul Avillach, Gabriel A. Brat, Chuan Hong, Michele Morris, Shyam Visweswaran, Lav P. Patel, Alba Gutiérrez-Sacristán, David A. Hanauer, John H. Holmes, Malarkodi Jebathilagam Samayamuthu, Florence T. Bourgeois, Sehi L’Yi, Sarah E. Maidlow, Bertrand Moal, Shawn N. Murphy, Zachary H. Strasser, Antoine Neuraz, Kee Yuan Ngiam, Ne Hooi Will Loh, Gilbert S. Omenn, Andrea Prunotto, Lauren A. Dalvin, Jeffrey G. Klann, Petra Schubert, Fernando J. Sanz Vidorreta, Vincent Benoit, Guillaume Verdy, Ramakanth Kavuluru, Hossein Estiri, Yuan Luo, Alberto Malovini, Valentina Tibollo, Riccardo Bellazzi, Kelly Cho, Yuk-Lam Ho, Amelia L. M. Tan, Byorn W. L. Tan, Nils Gehlenborg, Sara Lozano-Zahonero, Vianney Jouhet, Luca Chiovato, Bruce J. Aronow, Emma M. S. Toh, Wei Gen Scott Wong, Sara Pizzimenti, Kavishwar B. Wagholikar, Mauro Bucalo, The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Tianxi Cai, Andrew M. South, Isaac S. Kohane, and Griffin M. Weber

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

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.

Published
2022
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29. International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

Author

Griffin M. Weber, Chuan Hong, Zongqi Xia, Nathan P. Palmer, Paul Avillach, Sehi L’Yi, Mark S. Keller, Shawn N. Murphy, Alba Gutiérrez-Sacristán, Clara-Lea Bonzel, Arnaud Serret-Larmande, Antoine Neuraz, Gilbert S. Omenn, Shyam Visweswaran, Jeffrey G. Klann, Andrew M. South, Ne Hooi Will Loh, Mario Cannataro, Brett K. Beaulieu-Jones, Riccardo Bellazzi, Giuseppe Agapito, Mario Alessiani, Bruce J. Aronow, Douglas S. Bell, Vincent Benoit, Florence T. Bourgeois, Luca Chiovato, Kelly Cho, Arianna Dagliati, Scott L. DuVall, Noelia García Barrio, David A. Hanauer, Yuk-Lam Ho, John H. Holmes, Richard W. Issitt, Molei Liu, Yuan Luo, Kristine E. Lynch, Sarah E. Maidlow, Alberto Malovini, Kenneth D. Mandl, Chengsheng Mao, Michael E. Matheny, Jason H. Moore, Jeffrey S. Morris, Michele Morris, Danielle L. Mowery, Kee Yuan Ngiam, Lav P. Patel, Miguel Pedrera-Jimenez, Rachel B. Ramoni, Emily R. Schriver, Petra Schubert, Pablo Serrano Balazote, Anastasia Spiridou, Amelia L. M. Tan, Byorn W. L. Tan, Valentina Tibollo, Carlo Torti, Enrico M. Trecarichi, Xuan Wang, The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Isaac S. Kohane, Tianxi Cai, and Gabriel A. Brat

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

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.

Published
2022
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31. Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort studyResearch in context

Author

Byorn W.L. Tan, Bryce W.Q. Tan, Amelia L.M. Tan, Emily R. Schriver, Alba Gutiérrez-Sacristán, Priyam Das, William Yuan, Meghan R. Hutch, Noelia García Barrio, Miguel Pedrera Jimenez, Noor Abu-el-rub, Michele Morris, Bertrand Moal, Guillaume Verdy, Kelly Cho, Yuk-Lam Ho, Lav P. Patel, Arianna Dagliati, Antoine Neuraz, Jeffrey G. Klann, Andrew M. South, Shyam Visweswaran, David A. Hanauer, Sarah E. Maidlow, Mei Liu, Danielle L. Mowery, Ashley Batugo, Adeline Makoudjou, Patric Tippmann, Daniela Zöller, Gabriel A. Brat, Yuan Luo, Paul Avillach, Riccardo Bellazzi, Luca Chiovato, Alberto Malovini, Valentina Tibollo, Malarkodi Jebathilagam Samayamuthu, Pablo Serrano Balazote, Zongqi Xia, Ne Hooi Will Loh, Lorenzo Chiudinelli, Clara-Lea Bonzel, Chuan Hong, Harrison G. Zhang, Griffin M. Weber, Isaac S. Kohane, Tianxi Cai, Gilbert S. Omenn, John H. Holmes, Kee Yuan Ngiam, James R. Aaron, Giuseppe Agapito, Adem Albayrak, Giuseppe Albi, Mario Alessiani, Anna Alloni, Danilo F. Amendola, François Angoulvant, Li L.L.J. Anthony, Bruce J. Aronow, Fatima Ashraf, Andrew Atz, Vidul Ayakulangara Panickan, Paula S. Azevedo, James Balshi, Brett K. Beaulieu-Jones, Brendin R. Beaulieu-Jones, Douglas S. Bell, Antonio Bellasi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Blanco-Martínez, Martin Boeker, John Booth, Silvano Bosari, Florence T. Bourgeois, Robert L. Bradford, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Emily Bucholz, Anita Burgun, Mario Cannataro, Aldo Carmona, Anna Maria Cattelan, Charlotte Caucheteux, Julien Champ, Jin Chen, Krista Y. Chen, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Mohamad Daniar, Christel Daniel, Batsal Devkota, Audrey Dionne, Rui Duan, Julien Dubiel, Scott L. DuVall, Loic Esteve, Hossein Estiri, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Noelia García-Barrio, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Tomás González González, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Pietro H. Guzzi, Larry Han, Christian Haverkamp, Derek Y. Hazard, Bing He, Darren W. Henderson, Martin Hilka, Jacqueline P. Honerlaw, Kenneth M. Huling, Richard W. Issitt, Anne Sophie Jannot, Vianney Jouhet, Ramakanth Kavuluru, Mark S. Keller, Chris J. Kennedy, Kate F. Kernan, Daniel A. Key, Katie Kirchoff, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Sehi L'Yi, Trang T. Le, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Qi Long, Sara Lozano-Zahonero, Kristine E. Lynch, Sadiqa Mahmood, Simran Makwana, Kenneth D. Mandl, Chengsheng Mao, Anupama Maram, Monika Maripuri, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Diego R. Mazzotti, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Taha Mohseni Ahooyi, Jason H. Moore, Cinta Moraleda, Jeffrey S. Morris, Karyn L. Moshal, Sajad Mousavi, Douglas A. Murad, Shawn N. Murphy, Thomas P. Naughton, Carlos Tadeu Breda Neto, Jane Newburger, Wanjiku F.M. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Nina Orlova, Brian D. Ostasiewski, Nathan P. Palmer, Nicolas Paris, Miguel Pedrera-Jiménez, Ashley C. Pfaff, Emily R. Pfaff, Danielle Pillion, Sara Pizzimenti, Tanu Priya, Hans U. Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Paula Rubio-Mayo, Paolo Sacchi, Carlos Sáez, Elisa Salamanca, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C.C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Petra Schubert, Juergen Schuettler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Mohsin Shah, Zahra Shakeri Hossein Abad, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Francesca Sperotto, Anastasia Spiridou, Zachary H. Strasser, Suzana E. Tanni, Deanne M. Taylor, Ana I. Terriza-Torres, Emma M.S. Toh, Carlo Torti, Enrico M. Trecarichi, Andrew K. Vallejos, Gael Varoquaux, Margaret E. Vella, Jill-Jênn Vie, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Xuan Wang, Demian Wassermann, Martin Wolkewitz, Scott Wong, Xin Xiong, Ye Ye, Nadir Yehya, Joany M. Zachariasse, Janet J. Zahner, Alberto Zambelli, Valentina Zuccaro, and Chiara Zucco

Subjects
COVID-19, Acute kidney injury, SARS-CoV-2, Chronic kidney disease, Electronic health records, Medicine (General), R5-920
Abstract

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

Published
2023
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32. International electronic health record-derived post-acute sequelae profiles of COVID-19 patients

Author

Zhang, Harrison G., Dagliati, Arianna, Shakeri Hossein Abad, Zahra, Xiong, Xin, Bonzel, Clara-Lea, Xia, Zongqi, Tan, Bryce W. Q., Avillach, Paul, Brat, Gabriel A., Hong, Chuan, Morris, Michele, Visweswaran, Shyam, Patel, Lav P., Gutiérrez-Sacristán, Alba, Hanauer, David A., Holmes, John H., Samayamuthu, Malarkodi Jebathilagam, Bourgeois, Florence T., L’Yi, Sehi, Maidlow, Sarah E., Moal, Bertrand, Murphy, Shawn N., Strasser, Zachary H., Neuraz, Antoine, Ngiam, Kee Yuan, Loh, Ne Hooi Will, Omenn, Gilbert S., Prunotto, Andrea, Dalvin, Lauren A., Klann, Jeffrey G., Schubert, Petra, Vidorreta, Fernando J. Sanz, Benoit, Vincent, Verdy, Guillaume, Kavuluru, Ramakanth, Estiri, Hossein, Luo, Yuan, Malovini, Alberto, Tibollo, Valentina, Bellazzi, Riccardo, Cho, Kelly, Ho, Yuk-Lam, Tan, Amelia L. M., Tan, Byorn W. L., Gehlenborg, Nils, Lozano-Zahonero, Sara, Jouhet, Vianney, Chiovato, Luca, Aronow, Bruce J., Toh, Emma M. S., Wong, Wei Gen Scott, Pizzimenti, Sara, Wagholikar, Kavishwar B., Bucalo, Mauro, Cai, Tianxi, South, Andrew M., Kohane, Isaac S., and Weber, Griffin M.

Published
2022
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41. Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data.

Author

Jeffrey G. Klann, Hossein Estiri, Griffin M. Weber, Bertrand Moal, Paul Avillach, Chuan Hong, Amelia L. M. Tan, Brett K. Beaulieu-Jones, Victor M. Castro, Thomas Maulhardt, Alon Geva, Alberto Malovini, Andrew M. South, Shyam Visweswaran, Michele Morris, Malarkodi J. Samayamuthu, Gilbert S. Omenn, Kee Yuan Ngiam, Kenneth D. Mandl, Martin Boeker, Karen L. Olson, Danielle L. Mowery, Robert W. Follett, David A. Hanauer, Riccardo Bellazzi, Jason H. Moore, Ne-Hooi Will Loh, Douglas S. Bell, Kavishwar B. Wagholikar, Luca Chiovato, Valentina Tibollo, Siegbert Rieg, Anthony L. L. J. Li, Vianney Jouhet, Emily Schriver, Zongqi Xia, Meghan Hutch, Yuan Luo 0001, Isaac S. Kohane, Gabriel A. Brat, and Shawn N. Murphy

Published
2021
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44. Transfer Learning for Urban Landscape Clustering and Correlation with Health Indexes

Author

Bellazzi, Riccardo, Caldarone, Alessandro Aldo, Pala, Daniele, Franzini, Marica, Malovini, Alberto, Larizza, Cristiana, Casella, Vittorio, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Pagán, José, editor, Mokhtari, Mounir, editor, Aloulou, Hamdi, editor, Abdulrazak, Bessam, editor, and Cabrera, María Fernanda, editor

Published
2019
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48. Changes in laboratory value improvement and mortality rates over the course of the pandemic: an international retrospective cohort study of hospitalised patients infected with SARS-CoV-2

Author

Ramakanth Kavuluru, Xuan Wang, Paul Avillach, Florence Bourgeois, Kee Yuan Ngiam, Gabriel A Brat, Isaac Kohane, Yuk-Lam Ho, Yuan Luo, Harrison G Zhang, T Cai, Kelly Cho, Vincent Benoit, Antoine Neuraz, Chuan Hong, Sehi L'Yi, Griffin Weber, Bryce W Q Tan, Alba Gutiérrez-Sacristán, Clara-Lea Bonzel, Nathan P Palmer, Alberto Malovini, Valentina Tibollo, Meghan R Hutch, Molei Liu, Riccardo Bellazzi, Luca Chiovato, Fernando J Sanz Vidorreta, Trang T Le, William Yuan, Bertrand Moal, Michele Morris, David A Hanauer, Sarah Maidlow, Kavishwar Wagholikar, Shawn Murphy, Hossein Estiri, Adeline Makoudjou, Patric Tippmann, Jeffery Klann, Robert W Follett, Nils Gehlenborg, Gilbert S Omenn, Zongqi Xia, Arianna Dagliati, Shyam Visweswaran, Lav P Patel, Danielle L Mowery, Emily R Schriver, Malarkodi Jebathilagam Samayamuthu, Sara Lozano-Zahonero, Daniela Zöller, Amelia L M Tan, Byorn W L Tan, John H Holmes, Petra Schubert, Brett K. Beaulieu-Jones, Miguel Pedrera-Jiménez, Noelia García-Barrio, Pablo Serrano-Balazote, and Andrew South

Subjects
Medicine
Published
2022
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49. A Process Mining Pipeline to Characterize COVID-19 Patients' Trajectories and Identify Relevant Temporal Phenotypes From EHR Data

Author

Arianna Dagliati, Roberto Gatta, Alberto Malovini, Valentina Tibollo, Lucia Sacchi, Fidelia Cascini, Luca Chiovato, and Riccardo Bellazzi

Subjects
healthcare dynamics, digital health, precision medicine, temporal phenotypes, COVID-19, Electronic Health Record (EHR), Public aspects of medicine, RA1-1270
Abstract

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.

Published
2022
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