ABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. Methods: The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. Predictors were selected out of twelve candidate predictors based on three reliable methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. Results: In total 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation data. The same predictors were selected with the ABE and ABESS variable selection method. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding model discrimination in the validation cohort was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). A patient’s probability of developing REST symptoms \hat{y} = exp(S) / (1 + exp(S)) can be calculated with S = −4.947 + 0.349 × number of acute COVID-19 symptoms + 0.339 × severity of acute COVID-19 ward + 1.737 × severity of acute COVID-19 intensive or intermediate care + 0.128 × feeling of stress at home + 0.013 × age at presentation + 0.352 × female sex + 0.346 × presence of at least one cardiovascular risk factor − 0.097 × responsible for childcare/family member + 0.022 × body mass index, with feeling of stress at home ranges from 1 (no stress) to 10 (maximum stress) and responsibility for childcare/family member ranges from 1 (no responsibility/not applicable) to 6 (full responsibility). Conclusion: The proposed model is reliable to identify COVID-19 infected patients at risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended.
Subject(s)
COVID-19ABSTRACT
Background Women are overrepresented amongst individuals suffering from post-acute sequelae of SARS-CoV-2 infection (PASC). Biological (sex) as well as sociocultural (gender) differences between women and men might account for this imbalance, yet their impact on PASC is unknown. Methods and Findings By using Bayesian models comprising >200 co-variates, we assessed the impact of social context in addition to biological data on PASC in a multi-centre prospective cohort study of 2927 (46% women) individuals in Switzerland. Women more often reported at least one persistent symptom than men (43.5% vs 32.0% of men, p<0.001) six (IQR 5–9) months after SARS-CoV-2 infection. Adjusted models showed that women with personality traits stereotypically attributed to women were most often affected by PASC (OR 2.50[1.25-4.98], p<0.001), in particular when they were living alone (OR 1.84[1.25-2.74]), had an increased stress level (OR 1.06[1.03-1.09]), had undergone higher education (OR 1.30[1.08-1.54]), preferred pre-pandemic physical greeting over verbal greeting (OR 1.71[1.44-2.03]), and had experienced an increased number of symptoms during index infection (OR 1.27[1.22-1.33]). Conclusion Besides gender- and sex-sensitive biological parameters, sociocultural variables play an important role in producing sex differences in PASC. Our results indicate that predictor variables of PASC can be easily identified without extensive diagnostic testing and are targets of interventions aiming at stress coping and social support.
Subject(s)
COVID-19ABSTRACT
Purpose: The primary aim of this study was to assess the outcome of elderly ICU patients treated during the spring and autumn COVID-19 surges in Europe.Methods: A prospective European observation study (The COVIP study) in ICU patients aged 70 years and older admitted with COVID-19 disease from March to December 2020. An electronic Case Record Form was used to register a number of parameters including: SOFA score, Clinical Frailty Scale, comorbidities, usual ICU procedures including pharmacotherapy, limitation of care, ICU length of stay and survival at 30 days. The study was registered at ClinicalTrials.gov (ID: NCT04321265).Results: In total 2711 patients were included, 1325 from the first and 1291 from the second surge and 94 in between. Median age was 74 and 75 years in surge 1 and surge 2 respectively. SOFA score was higher in the first surge (median 6 versus 5, p<0.0001). The PaO2/FiO2 ratio at admission was higher during surge 1 and more patients received mechanical ventilation (78% versus 68%, p<0.0001). More patients were given corticosteroids in surge 2 (93 vs 38%, p<0.0001). 30 days survival was lower in the second surge (57.4% vs 49.3%) with adjusted HR of 1.43 (1.18-1.74).Conclusion: An unexpected, but significant, increase in 30-day mortality was observed during the second surge in our cohort of elderly ICU patients. The reason for this is unknown, however, practice changed and this might not be supported by sufficient evidence in this elderly population with COVID-19.Trial Registration: NCT04321265Funding Statement: The support of the study in France by a grant from Fondation Assistance Publique-Hôpitaux de Paris pour la recherche is greatly appreciated. In Norway, the study was supported by a grant from the Health Region West. In addition, the study was supported by a grant from the European Open Science Cloud (EOSC). EOSCsecretariat.eu has received funding from the European Union's Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant agreement number 831644.Declaration of Interests: The authors declare that they have no competing interests. JCS reports grants (full departmental disclosure) from Orion Pharma, Abbott Nutrition International, B. Braun Medical AG, CSEM AG, Edwards Lifesciences Services GmbH, Kenta Biotech Ltd, Maquet Critical Care AB, Omnicare Clinical Research AG, Nestle, Pierre Fabre Pharma AG, Pfizer , Bard Medica S.A., Abbott AG, Anandic Medical Systems, Pan Gas AG Healthcare, Bracco, Hamilton Medical AG, Fresenius Kabi, Getinge Group Maquet AG, Dräger AG, Teleflex Medical GmbH, Glaxo Smith Kline, Merck Sharp and Dohme AG, Eli Lilly and Company, Baxter, Astellas, Astra Zeneca, CSL Behring, Novartis, Covidien, Philips Medical, Phagenesis Ltd, Prolong Pharmaceuticals and Nycomed outside the submitted work. The money went into departmental funds. No personal financial gain applied.Ethics Approval Statement: The study was organised by the Very old Intensive care Patients (VIP) project 10,11 within the European Society of Intensive Care Medicine (ESICM) who also endorsed the study (www.vipstudy.org). Due to variations in requirement for ethical consent, some countries could recruit patients without upfront informed consent while others had to obtain it. The study deliberately allowed for coenrolment of study patients to other COVID-19 studies. The study adhered to the European Union General Data Privacy Regulation (GDPR) directive.