A Capture-Recapture-based Ascertainment Probability Weighting Method for Effect Estimation With Under-ascertained Outcomes.

Outcome under-ascertainment, characterized by the incomplete identification or reporting of cases, poses a substantial challenge in epidemiologic research. While capture-recapture methods can estimate unknown case numbers, their role in estimating exposure effects in observational studies is not well established. This paper presents an ascertainment probability weighting framework that integrates capture-recapture and propensity score weighting. We propose a nonparametric estimator of effects on binary outcomes that combines exposure propensity scores with data from two conditionally independent outcome measurements to simultaneously adjust for confounding and under-ascertainment. Demonstrating its practical application, we apply the method to estimate the relationship between health care work and coronavirus disease 2019 testing in a Swedish region. We find that ascertainment probability weighting greatly influences the estimated association compared to conventional inverse probability weighting, underscoring the importance of accounting for under-ascertainment in studies with limited outcome data coverage. We conclude with practical guidelines for the method's implementation, discussing its strengths, limitations, and suitable scenarios for application.

Survival of Critically Ill COVID-19 Patients in Sweden During the First Two and a Half Years of the Pandemic.

OBJECTIVES: Some studies have examined survival trends among critically ill COVID-19 patients, but most were case reports, small cohorts, and had relatively short follow-up periods. We aimed to examine the survival trend among critically ill COVID-19 patients during the first two and a half years of the pandemic and investigate potential predictors across different variants of concern periods. DESIGN: Prospective cohort study. SETTING: Swedish ICUs, between March 6, 2020, and December 31, 2022. PATIENTS: Adult COVID-19 ICU patients of 18 years old or older from the Swedish Intensive Care Register (SIR) that were linked to multiple other national registers. MEASUREMENT AND MAIN RESULTS: Survival probability and predictors of COVID-19 death were estimated using Kaplan-Meier and Cox regression analysis. Of 8975 patients, 2927 (32.6%) died. The survival rate among COVID-19 critically ill patients appears to have changed over time, with a worse survival in the Omicron period overall. The adjusted hazard ratios (aHRs) comparing older and younger ages were consistently strong but slightly attenuated in the Omicron period. After adjustment, the aHR of death was significantly higher for men, older age (40+ yr), low income, and with comorbid chronic heart disease, chronic lung disease, impaired immune disease, chronic renal disease, stroke, and cancer, and for those requiring invasive or noninvasive respiratory supports, who developed septic shock or had organ failures (p < 0.05). In contrast, foreign-born patients, those with booster vaccine, and those who had taken steroids had better survival (aHR = 0.87; 95% CI, 0.80-0.95; 0.74, 0.65-0.84, and 0.91, 0.84-0.98, respectively). Observed associations were similar across different variant periods. CONCLUSIONS: In this nationwide Swedish cohort covering over two and a half years of the pandemic, ICU survival rates changed over time. Older age was a strong predictor across all periods. Furthermore, most other mortality predictors remained consistent across different variant periods.

Impact of the early COVID-19 pandemic on adult mental health-related dispensed medications, hospitalizations and specialist outpatient visits in Norway and Sweden: Interrupted time series analysis.

AIMS: Norway and Sweden had different early pandemic responses that may have impacted mental health management. The aim was to assess the impact of the early COVID-19 pandemic on mental health-related care. METHODS: We used national registries in Norway and Sweden (1 January 2018-31 December 2020) to define 2 cohorts: (i) general adult population; and (ii) mental health adult population. Interrupted times series regression analyses evaluated step and slope changes compared to prepandemic levels for monthly rates of medications (antidepressants, antipsychotics, anxiolytics, hypnotics/sedatives, lithium, opioid analgesics, psychostimulants), hospitalizations (for anxiety, bipolar, depressive/mood, eating and schizophrenia/delusional disorders) and specialist outpatient visits. RESULTS: In Norway, immediate reductions occurred in the general population for medications (-12% antidepressants to -7% hypnotics/sedatives) except for antipsychotics; and hospitalizations (-33% anxiety disorders to -17% bipolar disorders). Increasing slope change occurred for all medications except psychostimulants (+1.1%/month hypnotics/sedatives to +1.7%/month antidepressants); and hospitalization for anxiety disorders (+5.5%/month), depressive/mood disorders (+1.7%/month) and schizophrenia/delusional disorders (+2%/month). In Sweden, immediate reductions occurred for antidepressants (-7%) and opioids (-10%) and depressive/mood disorder hospitalizations (-11%) only with increasing slope change in psychostimulant prescribing of (0.9%/month). In contrast to Norway, increasing slope changes occurred in specialist outpatient visits for depressive/mood disorders, eating disorders and schizophrenia/delusional disorders (+1.5, +1.9 and +2.3%/month, respectively). Similar changes occurred in the pre-existing mental health cohorts. CONCLUSION: Differences in early COVID-19 policy response may have contributed to differences in adult mental healthcare provision in Norway and Sweden.

Impact of chronic oral glucocorticoid treatment on mortality in patients with COVID-19: analysis of a population-based cohort.

OBJECTIVES: While glucocorticoid (GC) treatment initiated for COVID-19 reduces mortality, it is unclear whether GC treatment prior to COVID-19 affects mortality. Long-term GC use raises infection and thromboembolic risks. We investigated if patients with oral GC use prior to COVID-19 had increased mortality overall and by selected causes. DESIGN: Population-based observational cohort study. SETTINGS: Population-based register data in Sweden. PARTICIPANTS: All patients infected with COVID-19 in Sweden from January 2020 to November 2021 (n=1 200 153). OUTCOME MEASURES: Any prior oral GC use was defined as ≥1 GC prescription during 12 months before index. High exposure was defined as ≥2 GC prescriptions with a cumulative prednisolone dose ≥750 mg or equivalent during 6 months before index. GC users were compared with COVID-19 patients who had not received GCs within 12 months before index. We used Cox proportional hazard models and 1:2 propensity score matching to estimate HRs and 95% CIs, controlling for the same confounders in all analyses. RESULTS: 3378 deaths occurred in subjects with any prior GC exposure (n=48 806; 6.9%) and 14 850 among non-exposed (n=1 151 347; 1.3%). Both high (HR 1.98, 95% CI 1.87 to 2.09) and any exposure (1.58, 1.52 to 1.65) to GCs were associated with overall death. Deaths from pulmonary embolism, sepsis and COVID-19 were associated with high GC exposure and, similarly but weaker, with any exposure. High exposure to GCs was associated with increased deaths caused by stroke and myocardial infarction. CONCLUSION: Patients on oral GC treatment prior to COVID-19 have increased mortality, particularly from pulmonary embolism, sepsis and COVID-19.

Drug utilisation in children and adolescents before and after the start of the COVID-19 pandemic: Interrupted time-series analyses in three European countries.

BACKGROUND: The COVID-19 pandemic has affected children and adolescents in several ways, including worsened mental health, improvement of asthma, and increases in diabetes ketoacidosis. Less is known about how medication use in children and adolescents has been affected by the pandemic. OBJECTIVES: To explore how the COVID-19 pandemic affected drug utilisation in children and adolescents in Norway, Sweden, and Italy, by child age. METHODS: We conducted a longitudinal drug utilisation study among all children and adolescents (<18 years old) in Norway and Sweden and a nationwide paediatric database covering 3% of the paediatric population in Italy. We conducted an interrupted time-series analysis from January 2018 to December 2021, with March 2020 as the interruption point. Dispensing or prescription rates of antidepressants, anxiolytics, sleep medications, attention-deficit/hyperactivity disorder (ADHD) medications, insulin, and asthma medications were examined. RESULTS: The study population in January 2018 consisted of 3,455,521 children and adolescents (136,188 from Italy, 1,160,431 from Norway, and 2,158,902 from Sweden). For sleep medications and insulin, there were only minor changes in level or trend in some age groups after March 2020. For asthma medications, the pandemic was associated with an immediate decrease in dispensing in Norway and Sweden (range of change in level: -19.2 to -3.7 dispensings per 1000 person-months), and an increasing trend in all countries afterward (range of change in trend: 0.3-6.4 dispensings per 1000 person-months), especially for the youngest age groups. Among adolescents, the pandemic was associated with an increased trend for ADHD medications, antidepressants, and anxiolytics in Norway and Sweden, but not in Italy. CONCLUSIONS: The increasing trend of psychotropic medication dispensing, especially among adolescents after the start of the pandemic, is concerning and should be investigated further. Aside from a temporary effect on asthma medication dispensing, the pandemic did not greatly affect the dispensing of the medications investigated.

COVID-19 Outcomes and Vaccinations in Swedish Solid Organ Transplant Recipients 2020-2021: A Nationwide Multi-Register Comparative Cohort Study.

Increased COVID-19-related morbidity and mortality have been reported in solid organ transplant recipients (SOTRs). Most studies are underpowered for rigorous matching. We report infections, hospitalization, ICU care, mortality from COVID-19, and pertinent vaccination data in Swedish SOTRs 2020-2021. We conducted a nationwide cohort study, encompassing all Swedish residents. SOTRs were identified with ICD-10 codes and immunosuppressant prescriptions. Comparison cohorts were weighted based on a propensity score built from potential confounders (age, sex, comorbidities, socioeconomic factors, and geography), which achieved a good balance between SOTRs and non-SOTR groups. We included 10,372,033 individuals, including 9073 SOTRs. Of the SARS-CoV-2 infected, 47.3% of SOTRs and 19% of weighted comparator individuals were hospitalized. ICU care was given to 8% of infected SOTRs and 2% of weighted comparators. The case fatality rate was 7.7% in SOTRs, 6.2% in the weighted comparison cohort, and 1.3% in the unweighted comparison cohort. SOTRs had an increased risk of contracting COVID-19 (HR = 1.15 p < 0.001), being hospitalized (HR = 2.89 p < 0.001), receiving ICU care (HR = 4.59 p < 0.001), and dying (HR = 1.42 p < 0.001). SOTRs had much higher morbidity and mortality than the general population during 2020-2021. Also compared with weighted comparators, SOTRs had an increased risk of contracting COVID-19, being hospitalized, receiving ICU care, and dying. In Sweden, SOTRs were vaccinated earlier than weighted comparators. Lung transplant recipients had the worst outcomes. Excess mortality among SOTRs was concentrated in the second half of 2021.

Increased risk of hospitalization, intensive care and death due to COVID-19 in patients with adrenal insufficiency: A Swedish nationwide study.

BACKGROUND: Patients with adrenal insufficiency (AI) have excess morbidity and mortality related to infectious disorders. Whether patients with AI have increased morbidity and mortality from COVID-19 is unknown. METHODS: In this linked Swedish national register-based cohort study, patients with primary and secondary AI diagnosis were identified and followed from 1 January 2020 to 28 February 2021. They were compared with a control cohort from the general population matched 10:1 for age and sex. The following COVID-19 outcomes were studied: incidence of COVID-19 infection, rates of hospitalization, intensive care admission and death. Hazard ratios (HR) with 95% confidence intervals (95% CI) adjusted for socioeconomic factors and comorbidities were estimated using Cox regression analysis. RESULTS: We identified 5430 patients with AI and 54,300 matched controls: There were 47.6% women, mean age was 57.1 (standard deviation 18.1) years, and the frequency of COVID-19 infection was similar, but the frequency of hospitalization (2.1% vs. 0.8%), intensive care (0.3% vs. 0.1%) and death (0.8% vs. 0.2%) for COVID-19 was higher in AI patients than matched controls. After adjustment for socioeconomic factors and comorbidities, the HR (95% CI) was increased for hospitalization (1.96, 1.59-2.43), intensive care admission (2.76, 1.49-5.09) and death (2.29, 1.60-3.28). CONCLUSION: Patients with AI have a similar incidence of COVID-19 infection to a matched control population, but a more than twofold increased risk of developing a severe infection or a fatal outcome. They should therefore be prioritized for vaccination, antiviral therapy and other appropriate treatment to mitigate hospitalization and death.

The sociodemographic patterning of sick leave and determinants of longer sick leave after mild and severe COVID-19: a nationwide register-based study in Sweden.

BACKGROUND: Studies on sociodemographic differences in sick leave after coronavirus disease 2019 (COVID-19) are limited and research on COVID-19 long-term health consequences has mainly addressed hospitalized individuals. The aim of this study was to investigate the social patterning of sick leave and determinants of longer sick leave after COVID-19 among mild and severe cases. METHODS: The study population, from the Swedish multi-register observational study SCIFI-PEARL, included individuals aged 18-64 years in the Swedish population, gainfully employed, with a first positive polymerase chain reaction (PCR) test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from 1 January 2020 until 31 August 2021 (n = 661 780). Using logistic regression models, analyses were adjusted for sociodemographic factors, vaccination, prior sick leave, comorbidities and stratified by hospitalization. RESULTS: In total, 37 420 (5.7%) individuals were on sick leave due to COVID-19 in connection with their first positive COVID-19 test. Individuals on sick leave were more often women, older, had lower income and/or were born outside Sweden. These differences were similar across COVID-19 pandemic phases. The highest proportion of sick leave was seen in the oldest age group (10.3%) with an odds ratio of 4.32 (95% confidence interval 4.18-4.47) compared with the youngest individuals. Among individuals hospitalized due to COVID-19, the sociodemographic pattern was less pronounced, and in some models, even reversed. The intersectional analysis revealed considerable variability in sick leave between sociodemographic groups (range: 1.5-17.0%). CONCLUSION: In the entire Swedish population of gainfully employed individuals, our findings demonstrated evident sociodemographic differences in sick leave due to COVID-19. In the hospitalized group, the social patterning was different and less pronounced.

Machine learning-driven development of a disease risk score for COVID-19 hospitalization and mortality: a Swedish and Norwegian register-based study.

Aims: To develop a disease risk score for COVID-19-related hospitalization and mortality in Sweden and externally validate it in Norway. Method: We employed linked data from the national health registries of Sweden and Norway to conduct our study. We focused on individuals in Sweden with confirmed SARS-CoV-2 infection through RT-PCR testing up to August 2022 as our study cohort. Within this group, we identified hospitalized cases as those who were admitted to the hospital within 14 days of testing positive for SARS-CoV-2 and matched them with five controls from the same cohort who were not hospitalized due to SARS-CoV-2. Additionally, we identified individuals who died within 30 days after being hospitalized for COVID-19. To develop our disease risk scores, we considered various factors, including demographics, infectious, somatic, and mental health conditions, recorded diagnoses, and pharmacological treatments. We also conducted age-specific analyses and assessed model performance through 5-fold cross-validation. Finally, we performed external validation using data from the Norwegian population with COVID-19 up to December 2021. Results: During the study period, a total of 124,560 individuals in Sweden were hospitalized, and 15,877 individuals died within 30 days following COVID-19 hospitalization. Disease risk scores for both hospitalization and mortality demonstrated predictive capabilities with ROC-AUC values of 0.70 and 0.72, respectively, across the entire study period. Notably, these scores exhibited a positive correlation with the likelihood of hospitalization or death. In the external validation using data from the Norwegian COVID-19 population (consisting of 53,744 individuals), the disease risk score predicted hospitalization with an AUC of 0.47 and death with an AUC of 0.74. Conclusion: The disease risk score showed moderately good performance to predict COVID-19-related mortality but performed poorly in predicting hospitalization when externally validated.

Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network.

Objective: Developing accurate phenotype definitions is critical in obtaining reliable and reproducible background rates in safety research. This study aims to illustrate the differences in background incidence rates by comparing definitions for a given outcome. Materials and Methods: We used 16 data sources to systematically generate and evaluate outcomes for 13 adverse events and their overall background rates. We examined the effect of different modifications (inpatient setting, standardization of code set, and code set changes) to the computable phenotype on background incidence rates. Results: Rate ratios (RRs) of the incidence rates from each computable phenotype definition varied across outcomes, with inpatient restriction showing the highest variation from 1 to 11.93. Standardization of code set RRs ranges from 1 to 1.64, and code set changes range from 1 to 2.52. Discussion: The modification that has the highest impact is requiring inpatient place of service, leading to at least a 2-fold higher incidence rate in the base definition. Standardization showed almost no change when using source code variations. The strength of the effect in the inpatient restriction is highly dependent on the outcome. Changing definitions from broad to narrow showed the most variability by age/gender/database across phenotypes and less than a 2-fold increase in rate compared to the base definition. Conclusion: Characterization of outcomes across a network of databases yields insights into sensitivity and specificity trade-offs when definitions are altered. Outcomes should be thoroughly evaluated prior to use for background rates for their plausibility for use across a global network.

Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study.

OBJECTIVE: To investigate the effectiveness of primary covid-19 vaccination (first two doses and first booster dose within the recommended schedule) against post-covid-19 condition (PCC). DESIGN: Population based cohort study. SETTING: Swedish Covid-19 Investigation for Future Insights-a Population Epidemiology Approach using Register Linkage (SCIFI-PEARL) project, a register based cohort study in Sweden. PARTICIPANTS: All adults (≥18 years) with covid-19 first registered between 27 December 2020 and 9 February 2022 (n=589 722) in the two largest regions of Sweden. Individuals were followed from a first infection until death, emigration, vaccination, reinfection, a PCC diagnosis (ICD-10 diagnosis code U09.9), or end of follow-up (30 November 2022), whichever came first. Individuals who had received at least one dose of a covid-19 vaccine before infection were considered vaccinated. MAIN OUTCOME MEASURE: The primary outcome was a clinical diagnosis of PCC. Vaccine effectiveness against PCC was estimated using Cox regressions adjusted for age, sex, comorbidities (diabetes and cardiovascular, respiratory, and psychiatric disease), number of healthcare contacts during 2019, socioeconomic factors, and dominant virus variant at time of infection. RESULTS: Of 299 692 vaccinated individuals with covid-19, 1201 (0.4%) had a diagnosis of PCC during follow-up, compared with 4118 (1.4%) of 290 030 unvaccinated individuals. Covid-19 vaccination with any number of doses before infection was associated with a reduced risk of PCC (adjusted hazard ratio 0.42, 95% confidence interval 0.38 to 0.46), with a vaccine effectiveness of 58%. Of the vaccinated individuals, 21 111 received one dose only, 205 650 received two doses, and 72 931 received three or more doses. Vaccine effectiveness against PCC for one dose, two doses, and three or more doses was 21%, 59%, and 73%, respectively. CONCLUSIONS: The results of this study suggest a strong association between covid-19 vaccination before infection and reduced risk of receiving a diagnosis of PCC. The findings highlight the importance of primary vaccination against covid-19 to reduce the population burden of PCC.

Risk and outcomes of COVID-19 in patients with oxygen-dependent chronic respiratory failure- a national cohort study.

BACKGROUND: We aimed to evaluate cumulative occurrence and impact of COVID-19 in patients with chronic respiratory failure (CRF) treated with long-term oxygen therapy (LTOT). MATERIAL AND METHODS: Data were obtained from the SCIFI-PEARL study on the entire Swedish population and on patients with oxygen-dependent CRF and no COVID-19 diagnosis before start of LTOT. Analyses were performed for three time periods; pre-alpha (Jan-Dec 2020), alpha (Jan-Mar 2021) and delta/omicron (Apr 2021-May 2022). Cumulative incidence of laboratory-verified COVID-19 was compared between patients with CRF and the general population. Risk factors for severe (hospitalised) to critical (intensive care, or death ≤30 days after infection) COVID-19, and the impact of COVID-19 on one-year mortality, were analysed using multivariable Cox regression. RESULTS: Cumulative incidence of COVID-19 was higher in patients with CRF than in the general population during the pre-alpha period (6.4%/4.9%, p = 0.002), but less common during the alpha and delta/omicron periods (2.9%/3.8% and 7.8%/15.5%, p < 0.0001 for both). The risk of severe/critical COVID-19 was much higher in CRF patients during all periods (4.9%/0.5%, 3.8%/0.2% and 15.5%/0.5%, p < 0.0001 for all). Risk factors for COVID-19 infection in people with CRF were higher age, cardiovascular and renal disease, and COVID-19 was associated with increased one-year mortality following infection in the pre-alpha (HR 1.79; [95% CI] 1.27-2.53) and alpha periods (1.43; 1.03-1.99). CONCLUSION: Patients with CRF had higher risk of severe/critical COVID-19 than the general population. COVID-19 infection was associated with excess one-year mortality.

Regular Inhaled Corticosteroids Use May Protect Against Severe COVID-19 Outcome in COPD.

Purpose: Population-based studies provide conflicting evidence about how inhaled corticosteroids (ICS) impact COVID-19 outcomes among COPD patients. We investigated whether regular ICS exposure affects risk, severity, or survival in SARS-CoV-2 infection, using a nationwide linked Swedish population register database. Patients and Methods: During January-December 2020, we studied two defined Swedish adult populations - Whole population [≥40 years] (N = 5243479), and COPD subpopulation [≥40 years] (N = 133372), in three study cohorts, respectively: 1. Overall cohort (index date 1 Jan 2020), 2. COVID-19 diagnosed sub-cohort (index date = diagnosis date), and 3. COVID-19 hospitalized sub-cohort (index date = admission date). Regular exposure was defined as ≥3 ICS prescriptions in the year before index. Hazard ratios (HRs) for outcomes (COVID-19 onset, hospitalization, ICU admission, or death) related to ICS exposure were estimated using Cox regression. Confounding was controlled by propensity score methods applying Average Treatment effect in the Treated (ATT) weighting. Results: Regular ICS use was associated with only very slightly increased onset of COVID-19, hospitalization, ICU admission, and death in the overall whole population cohort and in the overall COPD subpopulation cohort, except for ICU admission (marginally non-significant HRs, up to 1.13); and no clear increase in the diagnosed sub-cohorts. However, in the COVID-19 hospitalized COPD sub-cohort, ICS therapy showed reduced risks against progression to ICU admission and death, significant for death (HR 0.82 95% CI [0.67-0.99]). Conclusion: For COPD patients, ICS therapy offers some protection against progression to ICU admission and death among COVID-19 hospitalized patients. Our findings alleviate concerns about increased risks of COVID-19 by ICS treatment and provide evidence supporting the continuation of ICS therapy for COPD patients.

Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review.

Aim: To perform a systematic review on the use of Artificial Intelligence (AI) techniques for predicting COVID-19 hospitalization and mortality using primary and secondary data sources. Study eligibility criteria: Cohort, clinical trials, meta-analyses, and observational studies investigating COVID-19 hospitalization or mortality using artificial intelligence techniques were eligible. Articles without a full text available in the English language were excluded. Data sources: Articles recorded in Ovid MEDLINE from 01/01/2019 to 22/08/2022 were screened. Data extraction: We extracted information on data sources, AI models, and epidemiological aspects of retrieved studies. Bias assessment: A bias assessment of AI models was done using PROBAST. Participants: Patients tested positive for COVID-19. Results: We included 39 studies related to AI-based prediction of hospitalization and death related to COVID-19. The articles were published in the period 2019-2022, and mostly used Random Forest as the model with the best performance. AI models were trained using cohorts of individuals sampled from populations of European and non-European countries, mostly with cohort sample size <5,000. Data collection generally included information on demographics, clinical records, laboratory results, and pharmacological treatments (i.e., high-dimensional datasets). In most studies, the models were internally validated with cross-validation, but the majority of studies lacked external validation and calibration. Covariates were not prioritized using ensemble approaches in most of the studies, however, models still showed moderately good performances with Area under the Receiver operating characteristic Curve (AUC) values >0.7. According to the assessment with PROBAST, all models had a high risk of bias and/or concern regarding applicability. Conclusions: A broad range of AI techniques have been used to predict COVID-19 hospitalization and mortality. The studies reported good prediction performance of AI models, however, high risk of bias and/or concern regarding applicability were detected.

Incidence and Characteristics in Children with Post-COVID-19 Condition in Sweden.

This cohort study of health data from 2 regions in Sweden examines incidence rates of post­COVID-19 among children and compares incidence rates by demographic and clinical characteristics.

Pre- and post-vaccination characteristics and risk factors for COVID-19 outcomes in a Swedish population-based cohort of COPD patients.

Rationale: Evidence on risk factors for Coronavirus disease 2019 (COVID-19) outcomes among patients with COPD in relation to COVID-19 vaccination remains limited. The objectives of the present study were to characterise determinants of COVID-19 infection, hospitalisation, intensive care unit (ICU) admission and death in COPD patients in their unvaccinated state compared to when vaccinated. Methods: We included all COPD patients in the Swedish National Airway Register (SNAR). Events of COVID-19 infection (test and/or healthcare encounter), hospitalisation, ICU admission and death were identified from 1 January 2020 to 30 November 2021. Using adjusted Cox regression, associations between baseline sociodemographics, comorbidities, treatments, clinical measurements and COVID-19 outcomes, during unvaccinated and vaccinated follow-up time, were analysed. Results: The population-based COPD cohort included 87 472 patients, among whom 6771 (7.7%) COVID-19 infections, 2897 (3.3%) hospitalisations, 233 (0.3%) ICU admissions and 882 (1.0%) COVID-19 deaths occurred. During unvaccinated follow-up, risk of COVID-19 hospitalisation and death increased with age, male sex, lower education, non-married status and being foreign-born. Comorbidities increased risk of several outcomes, e.g. respiratory failure for infection and hospitalisation (adjusted hazard ratios (HR) 1.78, 95% CI 1.58-2.02 and 2.51, 2.16-2.91, respectively), obesity for ICU admission (3.52, 2.29-5.40) and cardiovascular disease for mortality (2.80, 2.16-3.64). Inhaled COPD therapy was associated with infection, hospitalisation and death. COPD severity was also associated with COVID-19, especially hospitalisation and death. Although the risk factor panorama was similar, COVID-19 vaccination attenuated HRs for some risk factors. Conclusion: This study provides population-based evidence on predictive risk factors for COVID-19 outcomes and highlights the positive implications of COVID-19 vaccination for COPD patients.

Serially Combining Epidemiological Designs Does Not Improve Overall Signal Detection in Vaccine Safety Surveillance.

INTRODUCTION: Vaccine safety surveillance commonly includes a serial testing approach with a sensitive method for 'signal generation' and specific method for 'signal validation.' The extent to which serial testing in real-world studies improves or hinders overall performance in terms of sensitivity and specificity remains unknown. METHODS: We assessed the overall performance of serial testing using three administrative claims and one electronic health record database. We compared type I and II errors before and after empirical calibration for historical comparator, self-controlled case series (SCCS), and the serial combination of those designs against six vaccine exposure groups with 93 negative control and 279 imputed positive control outcomes. RESULTS: The historical comparator design mostly had fewer type II errors than SCCS. SCCS had fewer type I errors than the historical comparator. Before empirical calibration, the serial combination increased specificity and decreased sensitivity. Type II errors mostly exceeded 50%. After empirical calibration, type I errors returned to nominal; sensitivity was lowest when the methods were combined. CONCLUSION: While serial combination produced fewer false-positive signals compared with the most specific method, it generated more false-negative signals compared with the most sensitive method. Using a historical comparator design followed by an SCCS analysis yielded decreased sensitivity in evaluating safety signals relative to a one-stage SCCS approach. While the current use of serial testing in vaccine surveillance may provide a practical paradigm for signal identification and triage, single epidemiological designs should be explored as valuable approaches to detecting signals.

Genetic susceptibility to airway inflammation and exposure to short-term outdoor air pollution.

BACKGROUND: Air pollution is a large environmental health hazard whose exposure and health effects are unequally distributed among individuals. This is, at least in part, due to gene-environment interactions, but few studies exist. Thus, the current study aimed to explore genetic susceptibility to airway inflammation from short-term air pollution exposure through mechanisms of gene-environment interaction involving the SFTPA, GST and NOS genes. METHODS: Five thousand seven hundred two adults were included. The outcome measure was fraction of exhaled nitric oxide (FeNO), at 50 and 270 ml/s. Exposures were ozone (O3), particulate matter < 10 µm (PM10), and nitrogen dioxide (NO2) 3, 24, or 120-h prior to FeNO measurement. In the SFTPA, GST and NOS genes, 24 single nucleotide polymorphisms (SNPs) were analyzed for interaction effects. The data were analyzed using quantile regression in both single-and multipollutant models. RESULTS: Significant interactions between SNPs and air pollution were found for six SNPs (p < 0.05): rs4253527 (SFTPA1) with O3 and NOx, rs2266637 (GSTT1) with NO2, rs4795051 (NOS2) with PM10, NO2 and NOx, rs4796017 (NOS2) with PM10, rs2248814 (NOS2) with PM10 and rs7830 (NOS3) with NO2. The marginal effects on FeNO for three of these SNPs were significant (per increase of 10 µg/m3):rs4253527 (SFTPA1) with O3 (ß: 0.155, 95%CI: 0.013-0.297), rs4795051 (NOS2) with PM10 (ß: 0.073, 95%CI: 0.00-0.147 (single pollutant), ß: 0.081, 95%CI: 0.004-0.159 (multipollutant)) and NO2 (ß: -0.084, 95%CI: -0.147; -0.020 (3 h), ß: -0.188, 95%CI: -0.359; -0.018 (120 h)) and rs4796017 (NOS2) with PM10 (ß: 0.396, 95%CI: 0.003-0.790). CONCLUSIONS: Increased inflammatory response from air pollution exposure was observed among subjects with polymorphisms in SFTPA1, GSTT1, and NOS genes, where O3 interacted with SFTPA1 and PM10 and NO2/NOx with the GSTT1 and NOS genes. This provides a basis for the further exploration of biological mechanisms as well as the identification of individuals susceptible to the effects of outdoor air pollution.

Association between SARS-CoV-2 vaccination and healthcare contacts for menstrual disturbance and bleeding in women before and after menopause: nationwide, register based cohort study.

OBJECTIVES: To evaluate the risks of any menstrual disturbance and bleeding following SARS-CoV-2 vaccination in women who are premenopausal or postmenopausal. DESIGN: A nationwide, register based cohort study. SETTING: All inpatient and specialised outpatient care in Sweden from 27 December 2020 to 28 February 2022. A subset covering primary care for 40% of the Swedish female population was also included. PARTICIPANTS: 2 946 448 Swedish women aged 12-74 years were included. Pregnant women, women living in nursing homes, and women with history of any menstruation or bleeding disorders, breast cancer, cancer of female genital organs, or who underwent a hysterectomy between 1 January 2015 and 26 December 2020 were excluded. INTERVENTIONS: SARS-CoV-2 vaccination, by vaccine product (BNT162b2, mRNA-1273, or ChAdOx1 nCoV-19 (AZD1222)) and dose (unvaccinated and first, second, and third dose) over two time windows (one to seven days, considered the control period, and 8-90 days). MAIN OUTCOME MEASURES: Healthcare contact (admission to hospital or visit) for menstrual disturbance or bleeding before or after menopause (diagnosed with the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes N91, N92, N93, N95). RESULTS: 2 580 007 (87.6%) of 2 946 448 women received at least one SARS-CoV-2 vaccination and 1 652 472 (64.0%) 2 580 007 of vaccinated women received three doses before the end of follow-up. The highest risks for bleeding in women who were postmenopausal were observed after the third dose, in the one to seven days risk window (hazard ratio 1.28 (95% confidence interval 1.01 to 1.62)) and in the 8-90 days risk window (1.25 (1.04 to 1.50)). The impact of adjustment for covariates was modest. Risk of postmenopausal bleeding suggested a 23-33% increased risk after 8-90 days with BNT162b2 and mRNA-1273 after the third dose, but the association with ChAdOx1 nCoV-19 was less clear. For menstrual disturbance or bleeding in women who were premenopausal, adjustment for covariates almost completely removed the weak associations noted in the crude analyses. CONCLUSIONS: Weak and inconsistent associations were observed between SARS-CoV-2 vaccination and healthcare contacts for bleeding in women who are postmenopausal, and even less evidence was recorded of an association for menstrual disturbance or bleeding in women who were premenopausal. These findings do not provide substantial support for a causal association between SARS-CoV-2 vaccination and healthcare contacts related to menstrual or bleeding disorders.