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.

Impact of housing conditions on changes in youth's mental health following the initial national COVID-19 lockdown: a cohort study.

We aimed to investigate if declines in youth's mental health during lockdown were dependent on housing condition among 7445 youth (median age ~ 20 years) from the Danish National Birth Cohort (DNBC), with data collected at 18 years of age and again three weeks into the first national lockdown (April 2020). We examined associations between housing conditions (access to outdoor spaces, urbanicity, household density, and household composition) and changes in mental health (mental well-being, Quality of Life (QoL) and loneliness). We report results from multivariate linear and logistic regression models. Youth without access to outdoor spaces experienced greater declines in mental well-being (vs. garden; mean difference: - 0·75 (95% CI - 1·14, - 0·36)), and correspondingly greater odds of onset of low mental well-being (vs. garden; OR: 1·72 (95% CI 1·20, 2·48)). Youth in higher density households vs. below median or living alone vs. with parents only also had greater odds of onset of low mental well-being (OR: 1·26 (95% CI 1·08, 1·46) and OR: 1·62 (95% CI 1·17, 2·23), respectively). Living in denser households (vs. below median; OR: 1·18 (95% CI 1·06, 1·33), as well as living alone (vs. with parents; OR: 1·38 (95% CI 1·04, 1·82) was associated with onset of low QoL. Living alone more than doubled odds of onset of loneliness compared to living with parents, OR: 2·12 (95% CI 1·59, 2·82). Youth living alone, in denser households, and without direct access to outdoor spaces may be especially vulnerable to mental health declines.

'Standing together - at a distance': Documenting changes in mental-health indicators in Denmark during the COVID-19 pandemic.

Aims: There is a need to document the mental-health effects of the COVID-19 pandemic and its associated societal lockdowns. We initiated a large mixed-methods data collection, focusing on crisis-specific worries and mental-health indicators during the lockdown in Denmark. Methods: The study incorporated five data sources, including quantitative surveys and qualitative interviews. The surveys included a time series of cross-sectional online questionnaires starting on 20 March 2020, in which 300 (3×100) Danish residents were drawn every three days from three population groups: the general population (N=1046), families with children (N=1032) and older people (N=1059). These data were analysed by trend analysis. Semi-structured interviews were conducted with 32 people aged 24-83 throughout Denmark to provide context to the survey results and to gain insight into people's experiences of the lockdown. Results: Absolute level of worries, quality of life and social isolation were relatively stable across all population groups during the lockdown, although there was a slight deterioration in older people's overall mental health. Many respondents were worried about their loved ones' health (74-76%) and the potential long-term economic consequences of the pandemic (61-66%). The qualitative interviews documented significant variation in people's experiences, suggesting that the lockdown's effect on everyday life had not been altogether negative. Conclusions: People in Denmark seem to have managed the lockdown without alarming changes in their mental health. However, it is important to continue investigating the effects of the pandemic and various public-health measures on mental health over time and across national contexts.