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    Heterogeneity and temporal variation in the management of COVID-19: a multinational drug utilization study including 71,921 hospitalized patients from China, South Korea, Spain, and the United States of America
    Prats-Uribe, A ; Sena, A ; Hui Lai, LY ; Ahmed, W-U-R ; Alghoul, H ; Alser, O ; Alshammari, T ; Areia, C ; Carter, W ; Casajust, P ; Dawoud, D ; Golozar, A ; Jonnagaddala, J ; Mehta, P ; Gong, M ; Morales, D ; Nyberg, F ; Posada, J ; Recalde, M ; Roel, E ; Shah, K ; H. Shah, N ; Schilling, L ; Subbian, V ; Vizcaya, D ; Williams, A ; Zhang, L ; Zhang, Y ; Zhu, H ; Liu, L ; Rijnbeek, P ; Hripcsak, G ; Lane, JCE ; Burn, E ; Reich, C ; Suchard, M ; Duarte-Salles, T ; Kostka, K ; Ryan, P ; Prieto-Alhambra, D ( 2020)

    Objectives

    A plethora of medicines have been repurposed or used as adjunctive therapies for COVID-19. We characterized the utilization of medicines as prescribed in routine practice amongst patients hospitalized for COVID-19 in South Korea, China, Spain, and the USA.

    Design

    International network cohort

    Setting

    Hospital electronic health records from Columbia University Irving Medical Centre (NYC, USA), Stanford (CA, USA), Tufts (MA, USA), Premier (USA), Optum EHR (USA), department of veterans affairs (USA), NFHCRD (Honghu, China) and HM Hospitals (Spain); and nationwide claims from HIRA (South Korea)

    Participants

    patients hospitalized for COVID-19 from January to June 2020

    Main outcome measures

    Prescription/dispensation of any medicine on or 30 days after hospital admission date

    Analyses

    Number and percentage of users overall and over time

    Results

    71,921 people were included: 304 from China, 2,089 from Spain, 7,599 from South Korea, and 61,929 from the USA. A total of 3,455 medicines were identified. Common repurposed medicines included hydroxychloroquine (<2% in NFHCRD to 85.4% in HM), azithromycin (4.9% in NFHCRD to 56.5% in HM), lopinavir/ritonavir (<3% in all US but 34.9% in HIRA and 56.5% in HM), and umifenovir (0% in all except 78.3% in NFHCRD). Adjunctive medicines were used with great variability, with the ten most used treatments being (in descending order): bemiparin, enoxaparin, heparin, ceftriaxone, aspirin, vitamin D, famotidine, vitamin C, dexamethasone, and metformin. Hydroxychloroquine and azithromycin increased rapidly in use in March-April but declined steeply in May-June.

    Conclusions

    Multiple medicines were used in the first months of COVID-19 pandemic, with substantial geographic and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed medicines. Antithrombotics, antibiotics, H2 receptor antagonists and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of COVID-19.

    What is already known in this topic

    Drug repurposing is a common approach in the clinical management of novel diseases and conditions for which there are no available pharmacotherapies Hydroxychloroquine was widely used in the management of COVID-19 patients during the early phases of the pandemic Recent NIH (and other) guidelines recommend the use of concomitant therapies including immune-based, antithrombotic, antibiotic and other treatments

    What this study adds

    This study demonstrates great variability and extensive drug repurposing and utilization in the management of COVID-19 patients. A wide range of adjunctive treatments has been used, including antithrombotics, antibiotics, H2 receptor antagonists, and systemic corticosteroids. Emerging clinical data on the safety and efficacy of hydroxychloroquine and azithromycin impacted their rise and rapid decline in use internationally Conversely, the use of corticosteroids grew only in more recent months, with little use in the early stages of the pandemic (January to April)
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    Risk of depression, suicidal ideation, suicide and psychosis with hydroxychloroquine treatment for rheumatoid arthritis: a multi-national network cohort study
    Lane, JCE ; Weaver, J ; Kostka, K ; Duarte-Salles, T ; Abrahao, MT ; Alghoul, H ; Alser, O ; Alshammari, T ; Areia, C ; Biedermann, P ; Biedermann, P ; Banda, J ; Burn, E ; Casajust, P ; Fišer, K ; Hardin, J ; Hester, L ; Hripcsak, G ; Kaas-Hansen, BS ; Khosla, S ; Kolovos, S ; Lynch, K ; Makadia, R ; Mehta, P ; Morales, D ; Morgan-Stewart, H ; Mosseveld, M ; Newby, D ; Nyberg, F ; Ostropolets, A ; Park, RW ; Prats-Uribe, A ; Rao, G ; Reich, C ; Rijnbeek, P ; Sena, A ; Shoaibi, A ; Spotnitz, M ; Subbian, V ; Suchard, M ; Vizcaya, D ; Wen, H ; de Wilde, M ; Xie, J ; You, SC ; Zhang, L ; Lovestone, S ; Ryan, P ; Prieto-Alhambra, D ( 2020)

    ABSTRACT

    Objectives

    Concern has been raised in the rheumatological community regarding recent regulatory warnings that hydroxychloroquine used in the COVID-19 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation, or psychosis associated with hydroxychloroquine as used for rheumatoid arthritis (RA).

    Methods

    New user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and US). RA patients aged 18+ and initiating hydroxychloroquine were compared to those initiating sulfasalazine (active comparator) and followed up in the short (30-day) and long term (on treatment). Study outcomes included depression, suicide/suicidal ideation, and hospitalization for psychosis. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate database-specific calibrated hazard ratios (HR), with estimates pooled where I 2 <40%.

    Results

    918,144 and 290,383 users of hydroxychloroquine and sulfasalazine, respectively, were included. No consistent risk of psychiatric events was observed with short-term hydroxychloroquine (compared to sulfasalazine) use, with meta-analytic HRs of 0.96 [0.79-1.16] for depression, 0.94 [0.49-1.77] for suicide/suicidal ideation, and 1.03 [0.66-1.60] for psychosis. No consistent long-term risk was seen, with meta-analytic HRs 0.94 [0.71-1.26] for depression, 0.77 [0.56-1.07] for suicide/suicidal ideation, and 0.99 [0.72-1.35] for psychosis.

    Conclusions

    Hydroxychloroquine as used to treat RA does not appear to increase the risk of depression, suicide/suicidal ideation, or psychosis compared to sulfasalazine. No effects were seen in the short or long term. Use at higher dose or for different indications needs further investigation.

    TRIAL REGISTRATION

    Registered with EU PAS; Reference number EUPAS34497 ( http://www.encepp.eu/encepp/viewResource.htm?id=34498 ). The full study protocol and analysis source code can be found at https://github.com/ohdsi-studies/Covid19EstimationHydroxychloroquine .

    WHAT IS ALREADY KNOWN ON THIS TOPIC

    Recent regulatory warnings have raised concerns of potential psychiatric side effects of hydroxychloroquine at the doses used to treat COVID-19, generating concern in the rheumatological community Serious psychiatric adverse events such as suicide, acute psychosis, and depressive episodes have been identified by the US Food and Drug Administration (FDA) adverse events reporting system and at case report level

    WHAT THIS STUDY ADDS

    This is the largest study on the neuro-psychiatric safety of hydroxychloroquine to date, including >900,000 users treated for their RA in country-level or private health care systems in Germany, the UK, and the US We find no association between the use of hydroxychloroquine and the risk of depression, suicide/suicidal ideation, or severe psychosis compared to sulfasalazine

    HOW MIGHT THIS IMPACT ON CLINICAL PRACTICE

    Our data shows no association between hydroxychloroquine treatment for RA and risk of depression, suicide or psychosis compared to sulfasalazine. These findings do not support stopping or switching hydroxychloroquine treatment as used for RA due to recent concerns based on COVID-19 treated patients.
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    Seek COVER: Development and validation of a personalized risk calculator for COVID-19 outcomes in an international network
    Williams, R ; Markus, A ; Yang, C ; Salles, TD ; DuVall, S ; Falconer, T ; Jonnagaddala, J ; Kim, C ; Rho, Y ; Williams, A ; Alberga, A ; An, MH ; Aragón, M ; Areia, C ; Burn, E ; Choi, YH ; Drakos, I ; Fernandes Abrahão, MT ; Fernández-Bertolín, S ; Hripcsak, G ; Kaas-Hansen, BS ; Kandukuri, P ; Kors, J ; Kostka, K ; Liaw, S-T ; Lynch, K ; Machnicki, G ; Matheny, M ; Morales, D ; Nyberg, F ; Park, RW ; Prats-Uribe, A ; Pratt, N ; Rao, G ; Reich, C ; Rivera, M ; Seinen, T ; Shoaibi, A ; Spotnitz, M ; Steyerberg, E ; Suchard, M ; You, SC ; Zhang, L ; Zhou, L ; Ryan, P ; Prieto-Alhambra, D ; Reps, J ; Rijnbeek, P ( 2020)

    Objective

    To develop and externally validate COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission (COVER-H), requiring intensive services (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis.

    Methods

    We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries. We developed and validated 3 scores using 6,869,127 patients with a general practice, emergency room, or outpatient visit with diagnosed influenza or flu-like symptoms any time prior to 2020. The scores were validated on patients with confirmed or suspected COVID-19 diagnosis across five databases from South Korea, Spain and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death iii) death in the 30 days after index date.

    Results

    Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved high performance in influenza. When transported to COVID-19 cohorts, the AUC ranges were, COVER-H: 0.69-0.81, COVER-I: 0.73-0.91, and COVER-F: 0.72-0.90. Calibration was overall acceptable.

    Conclusions

    A 9-predictor model performs well for COVID-19 patients for predicting hospitalization, intensive services and fatality. The models could aid in providing reassurance for low risk patients and shield high risk patients from COVID-19 during de-confinement to reduce the virus’ impact on morbidity and mortality.
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    Deep phenotyping of 34,128 patients hospitalised with COVID-19 and a comparison with 81,596 influenza patients in America, Europe and Asia: an international network study.
    Burn, E ; You, SC ; Sena, A ; Kostka, K ; Abedtash, H ; Abrahao, MTF ; Alberga, A ; Alghoul, H ; Alser, O ; Alshammari, TM ; Aragon, M ; Areia, C ; Banda, JM ; Cho, J ; Culhane, AC ; Davydov, A ; DeFalco, FJ ; Duarte-Salles, T ; DuVall, SL ; Falconer, T ; Fernandez-Bertolin, S ; Gao, W ; Golozar, A ; Hardin, J ; Hripcsak, G ; Huser, V ; Jeon, H ; Jing, Y ; Jung, CY ; Kaas-Hansen, BS ; Kaduk, D ; Kent, S ; Kim, Y ; Kolovos, S ; Lane, J ; Lee, H ; Lynch, KE ; Makadia, R ; Matheny, ME ; Mehta, P ; Morales, DR ; Natarajan, K ; Nyberg, F ; Ostropolets, A ; Park, RW ; Park, J ; Posada, JD ; Prats-Uribe, A ; Rao, GA ; Reich, C ; Rho, Y ; Rijnbeek, P ; Schilling, LM ; Schuemie, M ; Shah, NH ; Shoaibi, A ; Song, S ; Spotnitz, M ; Suchard, MA ; Swerdel, J ; Vizcaya, D ; Volpe, S ; Wen, H ; Williams, AE ; Yimer, BB ; Zhang, L ; Zhuk, O ; Prieto-Alhambra, D ; Ryan, P ( 2020-06-28)
    Background In this study we phenotyped individuals hospitalised with coronavirus disease 2019 (COVID-19) in depth, summarising entire medical histories, including medications, as captured in routinely collected data drawn from databases across three continents. We then compared individuals hospitalised with COVID-19 to those previously hospitalised with influenza. Methods We report demographics, previously recorded conditions and medication use of patients hospitalised with COVID-19 in the US (Columbia University Irving Medical Center [CUIMC], Premier Healthcare Database [PHD], UCHealth System Health Data Compass Database [UC HDC], and the Department of Veterans Affairs [VA OMOP]), in South Korea (Health Insurance Review & Assessment [HIRA]), and Spain (The Information System for Research in Primary Care [SIDIAP] and HM Hospitales [HM]). These patients were then compared with patients hospitalised with influenza in 2014-19. Results 34,128 (US: 8,362, South Korea: 7,341, Spain: 18,425) individuals hospitalised with COVID-19 were included. Between 4,811 (HM) and 11,643 (CUIMC) unique aggregate characteristics were extracted per patient, with all summarised in an accompanying interactive website (http://evidence.ohdsi.org/Covid19CharacterizationHospitalization/). Patients were majority male in the US (CUIMC: 52%, PHD: 52%, UC HDC: 54%, VA OMOP: 94%,) and Spain (SIDIAP: 54%, HM: 60%), but were predominantly female in South Korea (HIRA: 60%). Age profiles varied across data sources. Prevalence of asthma ranged from 4% to 15%, diabetes from 13% to 43%, and hypertensive disorder from 24% to 70% across data sources. Between 14% and 33% were taking drugs acting on the renin-angiotensin system in the 30 days prior to hospitalisation. Compared to 81,596 individuals hospitalised with influenza in 2014-19, patients admitted with COVID-19 were more typically male, younger, and healthier, with fewer comorbidities and lower medication use. Conclusions We provide a detailed characterisation of patients hospitalised with COVID-19. Protecting groups known to be vulnerable to influenza is a useful starting point to minimize the number of hospital admissions needed for COVID-19. However, such strategies will also likely need to be broadened so as to reflect the particular characteristics of individuals hospitalised with COVID-19.
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    Safety of hydroxychloroquine, alone and in combination with azithromycin, in light of rapid wide-spread use for COVID-19: a multinational, network cohort and self-controlled case series study
    C.E.Lane, J ; Weaver, J ; Kostka, K ; Duarte-Salles, T ; Abrahao, MT ; Alghoul, H ; Alser, O ; Alshammari, T ; Biedermann, P ; Burn, E ; Casajust, P ; Conover, M ; Culhane, A ; Davydov, A ; DuVall, S ; Dymshyts, D ; Fernandez-Bertolin, S ; Fišter, K ; Hardin, J ; Hester, L ; Hripcsak, G ; Kent, S ; Khosla, S ; Kolovos, S ; Lambert, C ; van der Lei, J ; Londhe, A ; Lynch, K ; Makadia, R ; Margulis, A ; Matheny, M ; Mehta, P ; Morales, D ; Morgan-Stewart, H ; Mosseveld, M ; Newby, D ; Nyberg, F ; Ostropolets, A ; Park, RW ; Prats-Uribe, A ; Rao, G ; Reich, C ; Reps, J ; Rijnbeek, P ; Kumaran Sathappan, SM ; Schuemie, M ; Seager, S ; Sena, A ; Shoaibi, A ; Spotnitz, M ; Suchard, M ; Swerdel, J ; Torre, C ; Vizcaya, D ; Wen, H ; de Wilde, M ; You, SC ; Zhang, L ; Zhuk, O ; Ryan, P ; Prieto-Alhambra, D ( 2020)

    ABSTRACT

    Background

    Hydroxychloroquine has recently received Emergency Use Authorization by the FDA and is currently prescribed in combination with azithromycin for COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin.

    Methods

    New user cohort studies were conducted including 16 severe adverse events (SAEs). Rheumatoid arthritis patients aged 18+ and initiating hydroxychloroquine were compared to those initiating sulfasalazine and followed up over 30 days. Self-controlled case series (SCCS) were conducted to further establish safety in wider populations. Separately, SAEs associated with hydroxychloroquine- azithromycin (compared to hydroxychloroquine-amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, Netherlands, Spain, UK, and USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (CalHRs) according to drug use. Estimates were pooled where I2<40%.

    Results

    Overall, 956,374 and 310,350 users of hydroxychloroquine and sulfasalazine, and 323,122 and 351,956 users of hydroxychloroquine-azithromycin and hydroxychloroquine-amoxicillin were included. No excess risk of SAEs was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. SCCS confirmed these findings. However, when azithromycin was added to hydroxychloroquine, we observed an increased risk of 30-day cardiovascular mortality (CalHR2.19 [1.22- 3.94]), chest pain/angina (CalHR 1.15 [95% CI 1.05-1.26]), and heart failure (CalHR 1.22 [95% CI 1.02- 1.45])

    Conclusions

    Short-term hydroxychloroquine treatment is safe, but addition of azithromycin may induce heart failure and cardiovascular mortality, potentially due to synergistic effects on QT length. We call for caution if such combination is to be used in the management of Covid-19.

    Trial registration number

    Registered with EU PAS; Reference number EUPAS34497 ( http://www.encepp.eu/encepp/viewResource.htm?id=34498 ). The full study protocol and analysis source code can be found at https://github.com/ohdsi-studies/Covid19EstimationHydroxychloroquine .

    Funding sources

    This research received partial support from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) and Senior Research Fellowship (DPA), US National Institutes of Health, Janssen Research & Development, IQVIA, and by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea [grant number: HI16C0992]. Personal funding included Versus Arthritis [21605] (JL), MRC-DTP [MR/K501256/1] (JL), MRC and FAME (APU). The European Health Data & Evidence Network has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 806968. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. No funders had a direct role in this study. The views and opinions expressed are those of the authors and do not necessarily reflect those of the Clinician Scientist Award programme, NIHR, NHS or the Department of Health, England.
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    Keystone-designed perforator island flaps for reconstruction after chest keloid excision: A retrospective case series
    Huang, J ; Dong, R ; Wang, X ; Yu, N ; Zhao, R ; Bai, M ; Zhang, H ; Wang, Y ; Long, X (WILEY, 2021-03)
    OBJECTIVE: We retrospectively evaluated the efficacy and safety of keystone-designed perforator island flaps for chest keloid reconstruction. METHODS: We reviewed consecutive patients who received keystone flap reconstruction after chest keloid resection between January 2017 and February 2018. The patient demographic data, defect size, flap size, complications, and recurrence were recorded. RESULTS: Thirty-eight patients were evaluated in this retrospective case series. After keloid resection, dimension of wound defects was 5.5-9.5 cm × 9.5-12.5 cm, with an average dimension of 7.3 cm × 10.7 cm. The dimension of keystone flaps was between 6-10 cm × 20-34.5 cm, with an average dimension of 7.5 cm × 25.5 cm. The flaps healed smoothly without any complication. There was no keloid recurrence with 15 months of follow-up. 89.4% of the patients had good outcome with no apparent scarring, and 10.6% patients had satisfactory outcome with localized scarring. CONCLUSIONS: Keystone-designed perforator island flap is an effective and reliable method for reconstruction following chest keloid resection.
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    Characteristics and outcomes of 627 044 COVID-19 patients with and without obesity in the United States, Spain, and the United Kingdom
    Recalde, M ; Roel, E ; Pistillo, A ; Sena, A ; Prats-Uribe, A ; Ahmed, W-U-R ; Alghoul, H ; Alshammari, T ; Alser, O ; Areia, C ; Burn, E ; Casajust, P ; Dawoud, D ; DuVall, S ; Falconer, T ; Fernández-Bertolín, S ; Golozar, A ; Gong, M ; Lai, LYH ; Lane, JCE ; Lynch, K ; Matheny, M ; Mehta, P ; Morales, D ; Natarjan, K ; Nyberg, F ; Posada, J ; Reich, C ; Schilling, L ; Shah, K ; Shah, N ; Subbian, V ; Zhang, L ; Zhu, H ; Ryan, P ; Prieto-Alhambra, D ; Kostka, K ; Duarte-Salles, T (Cold Spring Harbor Laboratory, 2020)

    Background

    COVID-19 may differentially impact people with obesity. We aimed to describe and compare the demographics, comorbidities, and outcomes of obese patients with COVID-19 to those of non-obese patients with COVID-19, or obese patients with seasonal influenza.

    Methods

    We conducted a cohort study based on outpatient/inpatient care, and claims data from January to June 2020 from the US, Spain, and the UK. We used six databases standardized to the OMOP common data model. We defined two cohorts of patients diagnosed and/or hospitalized with COVID-19. We created corresponding cohorts for patients with influenza in 2017-2018. We followed patients from index date to 30 days or death. We report the frequency of socio-demographics, prior comorbidities, and 30-days outcomes (hospitalization, events, and death) by obesity status.

    Findings

    We included 627 044 COVID-19 (US: 502 650, Spain: 122 058, UK: 2336) and 4 549 568 influenza (US: 4 431 801, Spain: 115 224, UK: 2543) patients. The prevalence of obesity was higher among hospitalized COVID-19 (range: 38% to 54%) than diagnosed COVID-19 (30% to 47%), or diagnosed (15% to 47%) or hospitalized (27% to 48%) influenza patients. Obese hospitalized COVID-19 patients were more often female and younger than non-obese COVID-19 patients or obese influenza patients. Obese COVID-19 patients were more likely to have prior comorbidities, present with cardiovascular and respiratory events during hospitalization, require intensive services, or die compared to non-obese COVID-19 patients. Obese COVID-19 patients were more likely to require intensive services or die compared to obese influenza patients, despite presenting with fewer comorbidities.

    Interpretation

    We show that obesity is more common amongst COVID-19 than influenza patients, and that obese patients present with more severe forms of COVID-19 with higher hospitalization, intensive services, and fatality than non-obese patients. These data are instrumental for guiding preventive strategies of COVID-19 infection and complications.

    Funding

    The European Health Data & Evidence Network has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 806968. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This research received partial support from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), US National Institutes of Health, US Department of Veterans Affairs, Janssen Research & Development, and IQVIA. The University of Oxford received funding related to this work from the Bill & Melinda Gates Foundation (Investment ID INV-016201 and INV-019257). APU has received funding from the Medical Research Council (MRC) [MR/K501256/1, MR/N013468/1] and Fundación Alfonso Martín Escudero (FAME) (APU). VINCI [VA HSR RES 13-457] (SLD, MEM, KEL). JCEL has received funding from the Medical Research Council (MR/K501256/1) and Versus Arthritis (21605). No funders had a direct role in this study. The views and opinions expressed are those of the authors and do not necessarily reflect those of the Clinician Scientist Award programme, NIHR, Department of Veterans Affairs or the United States Government, NHS, or the Department of Health, England.

    Research in context

    Evidence before this study

    Previous evidence suggests that obese individuals are a high risk population for COVID-19 infection and complications. We searched PubMed for articles published from December 2019 until June 2020, using terms referring to SARS-CoV-2 or COVID-19 combined with terms for obesity. Few studies reported obesity and most of them were limited by small sample sizes and restricted to hospitalized patients. Further, they used different definitions for obesity (i.e. some reported together overweight and obesity, others only reported obesity with BMI>40kg/m 2 ). To date, no study has provided detailed information on the characteristics of obese COVID-19 patients, such as the prevalence of comorbidities or COVID-19 related outcomes. In addition, despite the fact that COVID-19 has been often compared to seasonal influenza, there are no studies assessing whether obese patients with COVID-19 differ from obese patients with seasonal influenza.

    Added value of this study

    We report the largest cohort of obese patients with COVID-19 and provide information on more than 29 000 aggregate characteristics publicly available. Our findings were consistent across the participating databases and countries. We found that the prevalence of obesity is higher among COVID-19 compared to seasonal influenza patients. Obese patients with COVID-19 are more commonly female and have worse outcomes than non-obese patients. Further, they have worse outcomes than obese patients with influenza, despite presenting with fewer comorbidities.

    Implications of all the available evidence

    Our results show that individuals with obesity present more comorbidities and worse outcomes for COVID-19 than non-obese patients. These findings may be useful in guiding clinical practice and future preventative strategies for obese individuals, as well as provide useful data to support subsequent association studies focussed on obesity and COVID-19.
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    Epidemiological and Clinical Characteristics of COVID-19 Patients with Cancers: A Systematic Review and Meta-Analysis of Global Data
    Kong, X ; Qi, Y ; Huang, J ; Zhao, Y ; Zhan, Y ; Qin, X ; Qi, Z ; Atanda, AJ ; Zhang, L ; Wang, J ; Fang, Y ; Jia, P ; Golozar, A ; Zhang, L ; Jiang, Y (Cold Spring Harbor Laboratory, 2020)

    Summary

    Background:

    Data on the prevalence of cancer in coronavirus disease 2019 (COVID-19)-infected patients and the severe illness incidence and mortality of COVID-19 patients with cancers remains unclear.

    Methods

    We systematically searched PubMed, Embase, Cochrane Library, and Web of Science, from database inception to July 15, 2020, for studies of patients with COVID-19 infection that had available comorbidity information on cancer. The primary endpoint was the pooled prevalence of cancer in COVID-19 patients and the secondary endpoint was the outcomes of COVID-19-infected cancer patients with incidence of severe illness and death rate. We calculated the pooled prevalence and corresponding 95% confidence intervals (95% CIs) using a random-effects model, and performed meta-regression analyses to explore heterogeneity. Subgroup analyses were conducted based on continent, country, age, sample size and study design.

    Findings

    A total of 107 eligible global studies were included in the systematic review. 90 studies with 94,845 COVID-19 patients in which 4,106 patients with cancer morbidity were included in the meta-analysis for prevalence of cancer morbidity among COVID-19 patients. 21 studies with 70,969 COVID-19 patients in which 3,351 patients with cancer morbidity who had severe illness or death during the studies. The overall prevalence of cancer among the COVID-19 patients was 0.07 (95% CI 0.05∽0.09). The cancer prevalence in COVID-19 patients of Europe (0.22, 95% CI 0.17∽0.28) was higher than that in Asia Pacific (0.04, 95% CI 0.03∽0.06) and North America (0.05, 95% CI 0.04∽0.06). The prevalence of COVID-19-infected cancer patients over 60 years old was 0.10 (95% CI 0.07∽0.14), higher than that of patients equal and less than 60 years old (0.05, 95% CI 0.03∽0.06). The pooled prevalence of severe illness among COVID-19 patients with cancers was 0.35 (95% CI 0.27∽0.43) and the pooled death rate of COVID-19 patients with cancers was 0.18 (95% CI 0.14∽0.18). The pooled incidence of severe illness of COVID-19 patients with cancers from Asia Pacific, Europe, and North America were 0.38(0.24, 0.52), 0.36(0.17, 0.55), and 0.26(0.20, 0.31), respectively; and the pooled death rate from Asia Pacific, Europe, and North America were 0.17(0.10, 0.24), 0.26(0.13, 0.39), and 0.19(0.13, 0.25), respectively.

    Interpretation

    To our knowledge, this study is the most comprehensive and up-to-date metaanalysis assessing the prevalence of cancer among COVID-19 patients, severe illness incidence and mortality rate. The prevalence of cancer varied significantly in geographical continents and age. The COVID-19 patients with cancer were at-risk for severe illness and a high death rate. The European COVID-19 patients had the highest cancer prevalence among the three continents examined and were also the most likely to progress to severe illness and death. Although the Asia Pacific COVID-19 patients had the lowest cancer prevalence, their severe illness rate was similar to that of European’s.

    Research in context

    Evidence before this study

    Coronavirus disease (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a newly discovered coronavirus, which leads to respiratory illness and can be transmitted from person to person. As the infection has become widespread, concern for the influence of COVID-19 on patients with cancer has grown. Previous studies suggest that patients with a history of active malignancy might be at increased risk for COVID-19, developing COVID-19-related complications and having a poorer prognosis. Until now, however, few studies explored the following two questions: 1) what is the estimated prevalence of cancer patients with COVID-19 infection; and 2) do COVID-19-infected cancer-patients have distinct clinical courses and worse outcomes compared with COVID-19-infected patients without cancers. The latter is based on the former to further explore the characteristics of clinical outcomes of such patients. The clarification of these two questions will greatly help to understand the relationship between COVID-19 and cancer in terms of clinical epidemiology, and thus facilitate the formulation of targeted and relevant public health policies.

    Added value of this study

    To our knowledge, this systematic review and meta-analysis of 107 studies is the most comprehensive and up-to-date assessing the prevalence of cancer among COVID-19 patients, the incidence of severe illness and mortality rate of COVID-19 patients with cancers. We provided a relatively accurate overall cancer prevalence among the all COVID-19 patients (7%), stratified by geographical continent, country, age, study sample size, and study design type. We also presented the pooled severe illness and mortality rates stratified by continent. European COVID-19-infected cancer patients seemed the most likely to both develop cancer and progress to severe illness and death.

    Implications of all the available evidence

    Our findings have reinforced important considerations of clinical care and emphasized the urgent unmet needs for COVID-19 patients with cancers using the pooled prevalence, incidence of severe illness, and death rates as evidence. Also, after comparing the cancer prevalence, incidence of severe illness, and death rate of COVID-19 patients from different continents, European population may require stronger control measures than the Asia Pacific and North American populations. In the future, as more data will be available, it will be interesting to further investigate the differences of sociodemographic and climcopathological features between COVID-19-infected patients with cancer and without cancer.
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    Can we trust the prediction model? Demonstrating the importance of external validation by investigating the COVID-19 Vulnerability (C-19) Index across an international network of observational healthcare datasets
    Reps, J ; Kim, C ; Williams, R ; Markus, A ; Yang, C ; Salles, TD ; Falconer, T ; Jonnagaddala, J ; Williams, A ; Fernández-Bertolín, S ; DuVall, S ; Kostka, K ; Rao, G ; Shoaibi, A ; Ostropolets, A ; Spotnitz, M ; Zhang, L ; Casajust, P ; Steyerberg, E ; Nyberg, F ; Kaas-Hansen, BS ; Choi, YH ; Morales, D ; Liaw, S-T ; Fernandes Abrahão, MT ; Areia, C ; Matheny, M ; Aragón, M ; Park, RW ; Hripcsak, G ; Reich, C ; Suchard, M ; You, SC ; Ryan, P ; Prieto-Alhambra, D ; Rijnbeek, P (Cold Spring Harbor Laboratory, 2020)

    Background

    SARS-CoV-2 is straining healthcare systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate between patients requiring hospitalization and those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision making during the pandemic. However, the model is at high risk of bias according to the Prediction model Risk Of Bias ASsessment Tool and has not been externally validated.

    Methods

    We followed the OHDSI framework for external validation to assess the reliability of the C-19 model. We evaluated the model on two different target populations: i) 41,381 patients that have SARS-CoV-2 at an outpatient or emergency room visit and ii) 9,429,285 patients that have influenza or related symptoms during an outpatient or emergency room visit, to predict their risk of hospitalization with pneumonia during the following 0 to 30 days. In total we validated the model across a network of 14 databases spanning the US, Europe, Australia and Asia.

    Findings

    The internal validation performance of the C-19 index was a c-statistic of 0.73 and calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data the model obtained c-statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US and South Korean datasets respectively. The calibration was poor with the model under-estimating risk. When validated on 12 datasets containing influenza patients across the OHDSI network the c-statistics ranged between 0.40-0.68.

    Interpretation

    The results show that the discriminative performance of the C-19 model is low for influenza cohorts, and even worse amongst COVID-19 patients in the US, Spain and South Korea. These results suggest that C-19 should not be used to aid decision making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.
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    Renin-angiotensin system blockers and susceptibility to COVID-19: a multinational open science cohort study.
    Morales, DR ; Conover, MM ; You, SC ; Pratt, N ; Kostka, K ; Duarte-Salles, T ; Fernández-Bertolín, S ; Aragón, M ; DuVall, SL ; Lynch, K ; Falconer, T ; van Bochove, K ; Sung, C ; Matheny, ME ; Lambert, CG ; Nyberg, F ; Alshammari, TM ; Williams, AE ; Park, RW ; Weaver, J ; Sena, AG ; Schuemie, MJ ; Rijnbeek, PR ; Williams, RD ; Lane, JCE ; Prats-Uribe, A ; Zhang, L ; Areia, C ; Krumholz, HM ; Prieto-Alhambra, D ; Ryan, PB ; Hripcsak, G ; Suchard, MA (Cold Spring Harbor Laboratory, 2020-06-12)
    INTRODUCTION: Angiotensin converting enzyme inhibitors (ACEs) and angiotensin receptor blockers (ARBs) could influence infection risk of coronavirus disease (COVID-19). Observational studies to date lack pre-specification, transparency, rigorous ascertainment adjustment and international generalizability, with contradictory results. METHODS: Using electronic health records from Spain (SIDIAP) and the United States (Columbia University Irving Medical Center and Department of Veterans Affairs), we conducted a systematic cohort study with prevalent ACE, ARB, calcium channel blocker (CCB) and thiazide diuretic (THZ) use to determine relative risk of COVID-19 diagnosis and related hospitalization outcomes. The study addressed confounding through large-scale propensity score adjustment and negative control experiments. RESULTS: Following over 1.1 million antihypertensive users identified between November 2019 and January 2020, we observed no significant difference in relative COVID-19 diagnosis risk comparing ACE/ARB vs CCB/THZ monotherapy (hazard ratio: 0.98; 95% CI 0.84 - 1.14), nor any difference for mono/combination use (1.01; 0.90 - 1.15). ACE alone and ARB alone similarly showed no relative risk difference when compared to CCB/THZ monotherapy or mono/combination use. Directly comparing ACE vs. ARB demonstrated a moderately lower risk with ACE, non-significant for monotherapy (0.85; 0.69 - 1.05) and marginally significant for mono/combination users (0.88; 0.79 - 0.99). We observed, however, no significant difference between drug- classes for COVID-19 hospitalization or pneumonia risk across all comparisons. CONCLUSION: There is no clinically significant increased risk of COVID-19 diagnosis or hospitalization with ACE or ARB use. Users should not discontinue or change their treatment to avoid COVID-19.