Risk of COVID-19 hospitalisation by HIV-status and SARS-CoV-2 vaccination status during pre- and post-Omicron era in a national register-based cohort study in Sweden.

BACKGROUND: Data on the outcomes of COVID-19 in people living with HIV (PLHIV), specifically in relation to vaccination status, are lacking during the Omicron era. METHODS: This nationwide registry-based study included all resident in Sweden ≥18 years with a positive SARS-CoV-2 PCR test during January 2021-February 2023. We estimated adjusted odds ratios (adjOR) for COVID-19 hospitalisation and severe COVID-19 (ICU admission and 90-day mortality), categorised by SARS-CoV-2 vaccination status (0-1, 2, and ≥3 doses), and HIV-status. Analyses were then categorised by time periods of pre-Omicron, Omicron during public testing, and Omicron after public testing. RESULTS: 1348 PLHIV and 1 669 389 people without HIV (PWoH) were included. PLHIV were older, more migrant (65 vs. 22%) and male (59 vs. 46%). Of PLHIV, 96% were on antiretroviral treatment and 94% virally suppressed. AdjORs of COVID-19 hospitalisation were similar irrespective of HIV-status, controlled for demographics, calendar month of infection, comorbidities, and income. PLHIV were more likely to be hospitalised than PWoH during Omicron and public testing (adjOR 2.3, 95% CI 1.1-4.2), but not after public testing. The odds of severe COVID-19 were three times higher in PLHIV compared to PWoH vaccinated with 2 doses (adjOR 3.2, 95% CI 1.3-6.9), but not when vaccinated with ≥3 doses (adjOR 0.7, 95% CI 0.2-1.6). Migrant and low nadir CD4+ T-cells were associated with higher odds of hospitalisation in unvaccinated PLHIV. CONCLUSIONS: This nationwide study, including mostly well-treated PLHIV, highlights the importance of vaccination with booster dose/s for effective protection against severe COVID-19 in PLHIV.KEY POINTPeople living with HIV compared to people without HIV did not have higher odds of COVID-19 hospitalisation irrespective of SARS-CoV-2 vaccination status (0-1 dose, 2 doses, ≥3 doses) when adjusting for known risk factors including comorbidities and socioeconomic status.

The Omicron Variant Is Associated with a Reduced Risk of the Post COVID-19 Condition and Its Main Phenotypes Compared to the Wild-Type Virus: Results from the EuCARE-POSTCOVID-19 Study.

Post COVID-19 condition (PCC) is defined as ongoing symptoms at ≥1 month after acute COVID-19. We investigated the risk of PCC in an international cohort according to viral variants. We included 7699 hospitalized patients in six centers (January 2020-June 2023); a subset of participants with ≥1 visit over the year after clinical recovery were analyzed. Variants were observed or estimated using Global Data Science Initiative (GISAID) data. Because patients returning for a post COVID-19 visit may have a higher PCC risk, and because the variant could be associated with the probability of returning, we used weighted logistic regressions. We estimated the proportion of the effect of wild-type (WT) virus vs. Omicron on PCC, which was mediated by Intensive Care Unit (ICU) admission, through a mediation analysis. In total, 1317 patients returned for a post COVID visit at a median of 2.6 (IQR 1.84-3.97) months after clinical recovery. WT was present in 69.6% of participants, followed by the Alpha (14.4%), Delta (8.9%), Gamma (3.9%) and Omicron strains (3.3%). Among patients with PCC, the most common manifestations were fatigue (51.7%), brain fog (32.7%) and respiratory symptoms (37.2%). Omicron vs. WT was associated with a reduced risk of PCC and PCC clusters; conversely, we observed a higher risk with the Delta and Alpha variants vs. WT. In total, 42% of the WT effect vs. Omicron on PCC risk appeared to be mediated by ICU admission. A reduced PCC risk was observed after Omicron infection, suggesting a possible reduction in the PCC burden over time. A non-negligible proportion of the variant effect on PCC risk seems mediated by increased disease severity during the acute disease.

Sociodemographic determinants of COVID-19 vaccination in adolescents in Stockholm, Sweden.

INTRODUCTION: Limited data exists on sociodemographic differences in vaccination coverage against COVID-19 among adolescents. This study investigated the association of sociodemographic factors and vaccination coverage of adolescents aged 12 to 17 years over the period of the general vaccination recommendation in Stockholm County, Sweden. METHOD: We conducted a population-based retrospective cross-sectional study of vaccine uptake of at least one dose of a COVID-19 vaccine up until 31 October 2022. We analysed vaccination coverage by sex, age group, underlying medical conditions, household socioeconomic factors, and vaccination status among adults in the household, using stratified analyses and multivariable modified Poisson regression models. RESULTS: The study cohort consisted of 166,634 adolescents out of which 70.3 % (n = 117,185) received at least one dose of a COVID-19 vaccine. In the fully adjusted model, the strongest predictor for not being vaccinated was if all adults in the household were unvaccinated (adjusted relative risk, aRR, 0.11, 95 % CI 0.10-0.12). Lower household education level and having both parents born outside Sweden were similarly negatively associated with vaccination coverage among adolescents. No association was observed between vaccination coverage and being an adolescent with an underlying medical condition (aRR 1.00, 95 % CI 0.99-1.02). CONCLUSION: Our results emphasise the necessity to address sociodemographic disparities and to engage adolescents at risk through targeted measures with particular emphasis in low-vaccination households in addition to households with lower education and non-Swedish origins in future vaccination program strategies.

Protection from prior natural infection vs. vaccination against SARS-CoV-2-a statistical note to avoid biased interpretation.

Introduction: The fight against SARS-CoV-2 has been a major task worldwide since it was first identified in December 2019. An imperative preventive measure is the availability of efficacious vaccines while there is also a significant interest in the protective effect of a previous SARS-CoV-2 infection on a subsequent infection (natural protection rate). Methods: In order to compare protection rates after infection and vaccination, researchers consider different effect measures such as 1 minus hazard ratio, 1 minus odds ratio, or 1 minus risk ratio. These measures differ in a setting with competing risks. Nevertheless, as there is no unique definition, these metrics are frequently used in studies examining protection rate. Comparison of protection rates via vaccination and natural infection poses several challenges. For instance many publications consider the epidemiological definition, that a reinfection after a SARS-CoV-2 infection is only possible after 90 days, whereas there is no such constraint after vaccination. Furthermore, death is more prominent as a competing event during the first 90 days after infection compared to vaccination. In this work we discuss the statistical issues that arise when investigating protection rates comparing vaccination with infection. We explore different aspects of effect measures and provide insights drawn from different analyses, distinguishing between the first and the second 90 days post-infection or vaccination. Results: In this study, we have access to real-world data of almost two million people from Stockholm County, Sweden. For the main analysis, data of over 52.000 people is considered. The infected group is younger, includes more men, and is less morbid compared to the vaccinated group. After the first 90 days, these differences increased. Analysis of the second 90 days shows differences between analysis approaches and between age groups. There are age-related differences in mortality. Considering the outcome SARS-CoV-2 infection, the effect of vaccination versus infection varies by age, showing a disadvantage for the vaccinated in the younger population, while no significant difference was found in the elderly. Discussion: To compare the effects of immunization through infection or vaccination, we emphasize consideration of several investigations. It is crucial to examine two observation periods: The first and second 90-day intervals following infection or vaccination. Additionally, methods to address imbalances are essential and need to be used. This approach supports fair comparisons, allows for more comprehensive conclusions and helps prevent biased interpretations.

In-hospital mortality during the wild-type, alpha, delta, and omicron SARS-CoV-2 waves: a multinational cohort study in the EuCARE project.

Background: Investigating outcomes of hospitalised COVID-19 patients throughout the pandemic is crucial to understand the impact of different SARS-CoV-2 variants. We compared 28-day in-hospital mortality of Wild-type, Alpha, Delta, and Omicron variant infections. Whether the difference in risk by variant varied by age was also evaluated. Methods: We conducted a cohort study including patients ≥18 years, hospitalised between 2020 and 02-01 and 2022-10-15 with a SARS-CoV-2 positive test, from nine countries. Variant was classified based on sequenced viruses or from national public metadata. Mortality was compared using the cumulative incidence function and subdistribution hazard ratios (SHR) adjusted for age, sex, calendar time, and comorbidities. Results were shown age-stratified due to effect measure modification (P < 0.0001 for interaction between age and variant). Findings: We included 38,585 participants: 19,763 Wild-type, 6387 Alpha, 3640 Delta, and 8795 Omicron. The cumulative incidence of mortality decreased throughout the study period. Among participants ≥70 years, the adjusted SHR (95% confidence interval) for Delta vs. Omicron was 1.66 (1.29-2.13). This estimate was 1.66 (1.17-2.36) for Alpha vs. Omicron, and 1.34 (0.92-1.95) for Wild-type vs. Omicron. These were 1.21 (0.81-1.82), 1.21 (0.68-2.17), and 0.98 (0.53-1.82) among unvaccinated participants. When comparing Omicron sublineages, the aSHR for BA.1 was 1.92 (1.43-2.58) compared to BA.2 and 1.52 (1.11-2.08) compared to BA.5. Interpretation: The herein observed decrease in in-hospital mortality seems to reflect a combined effect of immunity from vaccinations and previous infections, although differences in virulence between SARS-CoV-2 variants may also have contributed. Funding: European Union's Horizon Europe Research and Innovation Programme.

Post-COVID-19 Condition After SARS-CoV-2 Infections During the Omicron Surge vs the Delta, Alpha, and Wild Type Periods in Stockholm, Sweden.

Little is known about the post-COVID-19 condition (PCC) after infections with different SARS-CoV-2 variants. We investigated the risk of PCC diagnosis after primary omicron infections as compared with preceding variants in population-based cohorts in Stockholm, Sweden. When compared with omicron (n = 215 279, 0.2% receiving a PCC diagnosis), the adjusted hazard ratio (95% CI) was 3.26 (2.80-3.80) for delta (n = 52 182, 0.5% PCC diagnosis), 5.33 (4.73-5.99) for alpha (n = 97 978, 1.0% PCC diagnosis), and 6.31 (5.64-7.06) for the wild type (n = 107 920, 1.3% PCC diagnosis). These findings were consistent across all subgroup analyses except among those treated in the intensive care unit.

Outcomes of SARS-CoV-2 Omicron Variant Infections Compared With Seasonal Influenza and Respiratory Syncytial Virus Infections in Adults Attending the Emergency Department: A Multicenter Cohort Study.

BACKGROUND: There is a controversy over the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in an era of less virulent variants and an increasing population immunity. We compared outcomes in adults attending the emergency department (ED) with an Omicron, influenza, or respiratory syncytial virus (RSV) infection. METHODS: Retrospective multicenter cohort study including adults attending the ED in 6 acute care hospitals in Stockholm County, Sweden, with an Omicron, influenza, or RSV infection during 2021-2022 and 2015-2019. During 2021-2022, patients were tested for all 3 viruses by multiplex polymerase chain reaction (PCR) testing. The primary outcome was 30-day all-cause mortality. Secondary outcomes were 90-day all-cause mortality, hospitalization, and intensive care unit (ICU) admission. RESULTS: A total of 6385 patients from 2021-2022 were included in the main analyses: 4833 Omicron, 1099 influenza, and 453 RSV. The 30-day mortality was 7.9% (n = 381) in the Omicron, 2.5% (n = 28) in the influenza, and 6.0% (n = 27) in the RSV cohort. Patients with Omicron had an adjusted 30-day mortality odds ratio (OR) of 2.36 (95% confidence interval [CI] 1.60-3.62) compared with influenza and 1.42 (95% CI .94-2.21) compared with RSV. Among unvaccinated Omicron patients, stronger associations were observed compared with both influenza (OR 5.51 [95% CI 3.41-9.18]) and RSV (OR 3.29 [95% CI 2.01-5.56]). Similar trends were observed for secondary outcomes. Findings were consistent in comparisons with 5709 pre-pandemic influenza 995 RSV patients. CONCLUSIONS: In patients attending the ED, infections with Omicron were both more common and associated with more severe outcomes compared with influenza and RSV, in particular among unvaccinated patients.

Outcomes of Pediatric SARS-CoV-2 Omicron Infection vs Influenza and Respiratory Syncytial Virus Infections.

This cohort study compares outcomes of SARS-CoV-2 Omicron infection with those of influenza or respiratory syncytial virus infection in pediatric patients attending the emergency department.

Multimodal fine-tuning of clinical language models for predicting COVID-19 outcomes.

Clinical prediction models tend only to incorporate structured healthcare data, ignoring information recorded in other data modalities, including free-text clinical notes. Here, we demonstrate how multimodal models that effectively leverage both structured and unstructured data can be developed for predicting COVID-19 outcomes. The models are trained end-to-end using a technique we refer to as multimodal fine-tuning, whereby a pre-trained language model is updated based on both structured and unstructured data. The multimodal models are trained and evaluated using a multicenter cohort of COVID-19 patients encompassing all encounters at the emergency department of six hospitals. Experimental results show that multimodal models, leveraging the notion of multimodal fine-tuning and trained to predict (i) 30-day mortality, (ii) safe discharge and (iii) readmission, outperform unimodal models trained using only structured or unstructured healthcare data on all three outcomes. Sensitivity analyses are performed to better understand how well the multimodal models perform on different patient groups, while an ablation study is conducted to investigate the impact of different types of clinical notes on model performance. We argue that multimodal models that make effective use of routinely collected healthcare data to predict COVID-19 outcomes may facilitate patient management and contribute to the effective use of limited healthcare resources.

Clinical outcomes during and beyond different COVID-19 critical illness variant periods compared with other lower respiratory tract infections.

BACKGROUND: It is yet to be better understood how outcomes during and after the critical illness potentially differ between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants from other lower respiratory tract infections (LRTIs). We aimed to compare outcomes in adults admitted to an intensive care unit (ICU) with coronavirus disease 2019 (COVID-19) during the Wild-type, Alpha, Delta, and Omicron periods with individuals admitted with other LRTI. METHODS: Population-based cohort study in Stockholm, Sweden, using health registries with high coverage, including ICU-admitted adults from 1 January 2016 to 15 September 2022. Outcomes were in-hospital mortality, 180-day post-discharge mortality, 180-day hospital readmission, 180-day days alive and at home (DAAH), and incident diagnoses registered during follow-up. RESULTS: The number of ICU admitted individuals were 1421 Wild-type, 551 Alpha, 190 Delta, 223 Omicron, and 2380 LRTI. In-hospital mortality ranged from 28% (n = 665) in the LRTI cohort to 35% (n = 77) in the Delta cohort. The adjusted cause-specific hazard ratio (CSHR) compared with the LRTI cohort was 1.33 (95% confidence interval [CI] 1.16-1.53) in the Wild-type cohort, 1.53 (1.28-1.82) in the Alpha cohort, 1.70 (1.30-2.24) in the Delta cohort, and 1.59 (1.24-2.02) in the Omicron cohort. Among patients discharged alive from their COVID-19 hospitalization, the post-discharge mortality rates were lower (1-3%) compared with the LRTI cohort (9%), and the risk of hospital readmission was lower (CSHRs ranging from 0.42 to 0.68). Moreover, all COVID-19 cohorts had compared with the LRTI cohort more DAAH after compared with before the critical illness. CONCLUSION: Overall, COVID-19 critical was associated with an increased hazard of in-hospital mortality, but among those discharged alive from the hospital, less severe long-term outcomes were observed compared with other LRTIs.

Nosocomial SARS-CoV-2 Infections and Mortality During Unique COVID-19 Epidemic Waves.

Importance: Quantifying the burden of nosocomial SARS-CoV-2 infections and associated mortality is necessary to assess the need for infection prevention and control measures. Objective: To investigate the occurrence of nosocomial SARS-CoV-2 infections and associated 30-day mortality among patients admitted to hospitals in Region Stockholm, Sweden. Design, Setting, and Participants: A retrospective, matched cohort study divided the period from March 1, 2020, until September 15, 2022, into a prevaccination period, early vaccination and pre-Omicron (period 1), and late vaccination and Omicron (period 2). From among 303 898 patients 18 years or older living in Region Stockholm, 538 951 hospital admissions across all hospitals were included. Hospitalized admissions with nosocomial SARS-CoV-2 infections were matched to as many as 5 hospitalized admissions without nosocomial SARS-CoV-2 by age, sex, length of stay, admission time, and hospital unit. Exposure: Nosocomial SARS-CoV-2 infection defined as the first positive polymerase chain reaction test result at least 8 days after hospital admission or within 2 days after discharge. Main Outcomes and Measures: Primary outcome of 30-day mortality was analyzed using time-to-event analyses with a Cox proportional hazards regression model adjusted for age, sex, educational level, and comorbidities. Results: Among 2193 patients with SARS-CoV-2 infections or reinfections (1107 women [50.5%]; median age, 80 [IQR, 71-87] years), 2203 nosocomial SARS-CoV-2 infections were identified. The incidence rate of nosocomial SARS-CoV-2 infections was 1.57 (95% CI, 1.51-1.64) per 1000 patient-days. In the matched cohort, 1487 hospital admissions with nosocomial SARS-CoV-2 infections were matched to 5044 hospital admissions without nosocomial SARS-CoV-2 infections. Thirty-day mortality was higher in the prevaccination period (adjusted hazard ratio [AHR], 2.97 [95% CI, 2.50-3.53]) compared with period 1 (AHR, 2.08 [95% CI, 1.50-2.88]) or period 2 (AHR, 1.22 [95% CI, 0.92-1.60]). Among patients with nosocomial SARS-CoV-2 infections, 30-day AHR comparing those with 2 or more doses of SARS-CoV-2 vaccination and those with less than 2 doses was 0.64 (95% CI, 0.46-0.88). Conclusions and Relevance: In this matched cohort study, nosocomial SARS-CoV-2 infections were associated with higher 30-day mortality during the early phases of the pandemic and lower mortality during the Omicron variant wave and after the introduction of vaccinations. Mitigation of excess mortality risk from nosocomial transmission should be a strong focus when population immunity is low through implementation of adequate infection prevention and control measures.

EuCARE-hospitalised study protocol: a cohort study of patients hospitalised with COVID-19 in the EuCARE project.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), can lead to hospitalisation, particularly in elderly, immunocompromised, and non-vaccinated or partially vaccinated individuals. Although vaccination provides protection, the duration of this protection wanes over time. Additional doses can restore immunity, but the influence of viral variants, specific sequences, and vaccine-induced immune responses on disease severity remains unclear. Moreover, the efficacy of therapeutic interventions during hospitalisation requires further investigation. The study aims to analyse the clinical course of COVID-19 in hospitalised patients, taking into account SARS-CoV-2 variants, viral sequences, and the impact of different vaccines. The primary outcome is all-cause in-hospital mortality, while secondary outcomes include admission to intensive care unit and length of stay, duration of hospitalisation, and the level of respiratory support required. METHODS: This ongoing multicentre study observes hospitalised adult patients with confirmed SARS-CoV-2 infection, utilising a combination of retrospective and prospective data collection. It aims to gather clinical and laboratory variables from around 35,000 patients, with potential for a larger sample size. Data analysis will involve biostatistical and machine-learning techniques. Selected patients will provide biological material. The study started on October 14, 2021 and is scheduled to end on October 13, 2026. DISCUSSION: The analysis of a large sample of retrospective and prospective data about the acute phase of SARS CoV-2 infection in hospitalised patients, viral variants and vaccination in several European and non-European countries will help us to better understand risk factors for disease severity and the interplay between SARS CoV-2 variants, immune responses and vaccine efficacy. The main strengths of this study are the large sample size, the long study duration covering different waves of COVID-19 and the collection of biological samples that allows future research. TRIAL REGISTRATION: The trial has been registered on ClinicalTrials.gov. The unique identifier assigned to this trial is NCT05463380.

Sociodemographic disparities affect COVID-19 vaccine uptake in non-elderly adults with increased risk of severe COVID-19.

BACKGROUND: There is limited information about sociodemographic disparities in COVID-19 vaccine uptake among non-elderly adults with an increased risk of severe COVID-19. We investigated the COVID-19 vaccine uptake in individuals aged 18-64 years with an increased risk of severe COVID-19 (non-elderly risk group) in Stockholm County, Sweden. METHOD: We used population-based health and sociodemographic registries with high coverage to perform a cohort study of COVID-19 vaccine uptake of one to four doses up until 21 November 2022. The vaccine uptake in the non-elderly risk group was compared with non-risk groups aged 18-64 years (non-elderly non-risk group) and individuals aged ≥65 years (elderly). RESULTS: The uptake of ≥3 vaccine doses was 55%, 64% and 87% in the non-elderly non-risk group (n = 1,005,182), non-elderly risk group (n = 308,904) and elderly (n = 422,604), respectively. Among non-elderly risk group conditions, Down syndrome showed the strongest positive association with receiving three doses (adjusted risk ratio [aRR] 1.62, 95% confidence interval [CI] 1.54-1.71), whereas chronic liver disease showed the strongest negative association (aRR 0.90, 95% CI 0.88-0.92). Higher vaccine uptake among the non-elderly risk group was associated with increasing age, being born in Sweden, higher education, higher income and living in a household where other adults had been vaccinated. Similar trends were observed for the first, second, third and fourth doses. CONCLUSION: These results call for measures to tackle sociodemographic disparities in vaccination programmes during and beyond the COVID-19 pandemic.

Influence of perioperative SARS-CoV-2 infection on mortality in orthopaedic inpatients with surgically treated traumatic fractures.

BACKGROUND: SARS-CoV-2 has had an extensive influence on orthopaedic surgery practice and has been associated with an increased risk of mortality. There is limited evidence of how this pertains to acute orthopaedic surgery with inpatient care. METHODS: A retrospective cohort study on traumatic fracture patients requiring inpatient care between February 25, 2020 and March 25, 2021 was conducted. Patients were grouped by perioperative SARS-CoV-2 infection, defined as a positive SARS-CoV-2 test from 7 days before to 7 days after orthopaedic surgery, and compared using linear regression and Cox proportional hazards model for primary outcome 30-day mortality and secondary outcome hospital length of stay. RESULTS: In total, 5174 adults with a length of stay ≥ 48 h and an orthopaedic procedure due to a registered traumatic fracture were admitted from February 25, 2020 and discharged before March 26, 2021. Among the 5174 patients, 65% (3340/5174) were female, 22% (1146/5174) were 60-74 years and 56% (2897/5174) were 75 years or older. In total, 144 (3%) had a perioperative SARS-CoV-2 infection. Perioperative SARS-CoV-2 infection was associated with an increased 30-day mortality (aOR 4.19 [95% CI 2.67-6.43], p < 0.001). The median (IQR) length of stay after surgery was 13 days (IQR 6-21) for patients with, and 7 days (IQR 2-13) for patients without, perioperative SARS-CoV-2 infection. CONCLUSIONS: Perioperative SARS-CoV-2 infection increased 30-day mortality risk and hospital length of stay for traumatic fracture patients requiring inpatient surgical care. Pre- and postoperative infection were both associated with similar increases in mortality risk.

Association Between Time to Appropriate Antimicrobial Treatment and 30-day Mortality in Patients With Bloodstream Infections: A Retrospective Cohort Study.

BACKGROUND: Effective antimicrobial treatment is key for survival in bloodstream infection (BSI), but the impact of timing of treatment remains unclear. Our aim was to assess the association between time to appropriate antimicrobial treatment and 30-day mortality in BSI patients. METHODS: This was a retrospective cohort study using electronic health record data from a large academic center in Sweden. Adult patients admitted between the years 2012 and 2019, with onset of BSI at the emergency department or general wards, were included. Pathogen-antimicrobial drug combinations were classified as appropriate or inappropriate based on reported in vitro susceptibilities. To avoid immortal time bias, the association between appropriate therapy and mortality was assessed with multivariable logistic regression analysis at pre-specified landmark times. RESULTS: We included 10 628 BSI-episodes, occurring in 9192 unique patients. The overall 30-day mortality was 11.8%. No association in favor of a protective effect between appropriate therapy and mortality was found at the 1, 3 and 6 hours landmark after blood culture collection. At 12 hours, the risk of death increased with inappropriate treatment (adjusted odds ratio 1.17 [95% confidence interval {CI}, 1.01-1.37]) and continued to increase gradually at 24, 48, and 72 hours. Stratifying by high or low SOFA score generated similar odds ratios, with wider confidence intervals. CONCLUSIONS: Delays in appropriate antimicrobial treatment were associated with increased 30-day mortality after 12 hours from blood culture collection, but not at 1, 3, and 6 hours, in BSI. These results indicate a benchmark for providing rapid microbiological diagnostics of blood cultures.

Post COVID-19 condition diagnosis: A population-based cohort study of occurrence, associated factors, and healthcare use by severity of acute infection.

BACKGROUND: The occurrence and healthcare use trajectory of post COVID-19 condition (PCC) is poorly understood. Our aim was to investigate these aspects in SARS-CoV-2-positive individuals with and without a PCC diagnosis. METHODS: We conducted a population-based cohort study of adults in Stockholm, Sweden, with a verified infection from 1 March 2020 to 31 July 2021, stratified by the severity of the acute infection. The outcome was a PCC diagnosis registered any time 90-360 days after a positive test. We performed Cox regression models to assess baseline characteristics associated with the PCC diagnosis. Individuals diagnosed with PCC were then propensity-score matched to individuals without a diagnosis to assess healthcare use beyond the acute infection. RESULTS: Among 204,805 SARS-CoV-2-positive individuals, the proportion receiving a PCC diagnosis was 1% among individuals not hospitalized for their COVID-19 infection, 6% among hospitalized, and 32% among intensive care unit (ICU)-treated individuals. The most common new-onset symptom diagnosis codes among individuals with a PCC diagnosis were fatigue (29%) among nonhospitalized and dyspnea among both hospitalized (25%) and ICU-treated (41%) individuals. Female sex was associated with a PCC diagnosis among nonhospitalized and hospitalized individuals, with interactions between age and sex. Previous mental health disorders and asthma were associated with a PCC diagnosis among nonhospitalized and hospitalized individuals. Among individuals with a PCC diagnosis, the monthly proportion with outpatient care was substantially elevated up to 1 year after acute infection compared to before, with substantial proportions of this care attributed to PCC-related care. CONCLUSION: The differential association of age, sex, comorbidities, and healthcare use with the severity of the acute infection indicates different trajectories and phenotypes of PCC, with incomplete resolution 1 year after infection.

Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis.

OBJECTIVE: To externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19. DESIGN: Two stage individual participant data meta-analysis. SETTING: Secondary and tertiary care. PARTICIPANTS: 46 914 patients across 18 countries, admitted to a hospital with polymerase chain reaction confirmed covid-19 from November 2019 to April 2021. DATA SOURCES: Multiple (clustered) cohorts in Brazil, Belgium, China, Czech Republic, Egypt, France, Iran, Israel, Italy, Mexico, Netherlands, Portugal, Russia, Saudi Arabia, Spain, Sweden, United Kingdom, and United States previously identified by a living systematic review of covid-19 prediction models published in The BMJ, and through PROSPERO, reference checking, and expert knowledge. MODEL SELECTION AND ELIGIBILITY CRITERIA: Prognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor. METHODS: Eight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters. MAIN OUTCOME MEASURES: 30 day mortality or in-hospital mortality. RESULTS: Datasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al's model (0.96, 0.59 to 1.55, 0.21 to 4.28). CONCLUSION: The prognostic value of the included models varied greatly between the data sources. Although the Knight 4C Mortality Score and Wang clinical model appeared most promising, recalibration (intercept and slope updates) is needed before implementation in routine care.

The association between pre-exposure to glucocorticoids and other immunosuppressant drugs with severe COVID-19 outcomes.

OBJECTIVES: Whether preinfection use of immunosuppressant drugs is associated with COVID-19 severity remains unclear. The study was aimed to determine the association between preinfection use of immunosuppressant drugs with COVID-19 outcomes within 1 month after COVID-19 diagnosis. METHODS: This cohort study included individuals aged ≥18 years with underlying conditions associated with an immunocompromised state and diagnosed with COVID-19 between February 2020 and January 2021 at Karolinska University Hospital, Stockholm. Exposure to immunosuppressant drugs was defined based on dose and duration of drugs (glucocorticoids and drugs included in L01 or L04 chapter of Anatomical Therapeutic Chemical classification) before COVID-19 diagnosis. Outcomes included hospital admission, ICU admission, mechanical ventilation, mortality, renal failure, stroke, pulmonary embolism, and cardiac event. ORs were calculated using logistic regression and baseline covariate adjustment for confounding with inverse probability of treatment weights. RESULTS: Of 1067 included individuals, 444 were pre-exposed to immunosuppressive treatments before COVID-19 diagnosis (72 high-dose glucocorticoids, 255 L01 drugs (antineoplastics), 198 L04 (other immunosuppressants) and 78 to multiple drugs). There was no association between pre-exposure and hospital admission (OR 0.83, 95% CI 0.64 to 1.09) because of COVID-19. Pre-exposure to L01 or L04 drugs were not associated with hospital admission (adjusted ORs (aORs): 1.23, 0.86 to 1.76 and 1.31, 0.77 to 2.21) or other outcomes. High-dose glucocorticoids (≥20 mg/day prednisolone equivalent) were associated with hospital admission (aOR 2.50, 1.26 to 4.96), cardiac events (aOR 1.93, 1.08 to 3.46), pulmonary embolism (aOR 2.78, 1.08 to 7.15), and mortality (aOR 3.48, 1.77 to 6.86) due to COVID-19. DISCUSSION: Antineoplastic and other immunosuppressants drugs were not associated with COVID-19 severity whereas high-dose glucocorticoids were associated. Further studies should evaluate the effect of pre-exposure of different dose of glucocorticoids on COVID-19 prognosis.