Engineering a Mobile Platform to Promote Sleep in the Pediatric Primary Care Setting

COVID-19 mortality in the UK Biobank cohort: revisiting and evaluating risk factors

Most studies of severe/fatal COVID-19 risk have used routine/hospitalisation data without detailed pre-morbid characterisation. Using the community-based UK Biobank cohort, we investigate risk factors for COVID-19 mortality in comparison with non-COVID-19 mortality. We investigated demographic, social (education, income, housing, employment), lifestyle (smoking, drinking, body mass index), biological (lipids, cystatin C, vitamin D), medical (comorbidities, medications) and environmental (air pollution) data from UK Biobank (N = 473,550) in relation to 459 COVID-19 and 2626 non-COVID-19 deaths to 21 September 2020. We used univariate, multivariable and penalised regression models. Age (OR = 2.76 [2.18-3.49] per S.D. [8.1 years], p = 2.6 × 10-17), male sex (OR = 1.47 [1.26-1.73], p = 1.3 × 10-6) and Black versus White ethnicity (OR = 1.21 [1.12-1.29], p = 3.0 × 10-7) were independently associated with and jointly explanatory of (area under receiver operating characteristic curve, AUC = 0.79) increased risk of COVID-19 mortality. In multivariable regression, alongside demographic covariates, being a healthcare worker, current smoker, having cardiovascular disease, hypertension, diabetes, autoimmune disease, and oral steroid use at enrolment were independently associated with COVID-19 mortality. Penalised regression models selected income, cardiovascular disease, hypertension, diabetes, cystatin C, and oral steroid use as jointly contributing to COVID-19 mortality risk; Black ethnicity, hypertension and oral steroid use contributed to COVID-19 but not non-COVID-19 mortality. Age, male sex and Black ethnicity, as well as comorbidities and oral steroid use at enrolment were associated with increased risk of COVID-19 death. Our results suggest that previously reported associations of COVID-19 mortality with body mass index, low vitamin D, air pollutants, renin-angiotensin-aldosterone system inhibitors may be explained by the aforementioned factors.

The impact of COVID-19 on rheumatology patients in a large UK centre using an innovative data collection technique: prevalence and effect of social shielding

OBJECTIVES

We sought to gain insight into the prevalence of COVID-19 and the impact stringent social distancing (shielding) has had on a large cohort of rheumatology (RD) follow-up patients from a single large UK centre.

METHODS

We linked COVID-19-related deaths, screening and infection rates to our RD population (1.2.20-1.5.20) and audited active rheumatology follow-up patients through survey data communicated via a linked mobile phone SMS message. We assessed epidemiology, effect of stringent social distancing (shielding) and quality of life (HRQoL) by Short Form 12 (SF12).

RESULTS

There were 10,387 active follow-up patients, 7911 had linked mobile numbers. 12/10,387 RD patients died from COVID-19 (0.12%); local population 4131/7,415,149 (0.12%). For patients with mobile phones, 1693/7911 (21%) responded and of these, 1605 completed the SF12. Inflammatory arthritis predominated 1174/1693 (69%); 792/1693 (47%) were shielding. Advice on shielding/distancing was followed by 1372/1693(81%). 61/1693 (4%) reported COVID-19 (24/61 shielding); medication distribution was similar in COVID and non-COVID patients. Mental SF12 (MCS) but not physical (PCS) component scores were lower in COVID (60) vs. non-COVID (1545), mean differences: MCS, - 3.3; 95% CI - 5.2 to - 1.4, P < 0.001; PCS, - 0.4; 95% CI, - 2.1 to 1.3). In 1545 COVID-negative patients, those shielding had lower MCS (- 2.1; 95% CI - 2.8 to - 1.4) and PCS (- 3.1, 95% CI - 3.7 to - 2.5), both P < 0.001.

CONCLUSIONS

Our full RD cohort had no excess of COVID deaths compared to the general local population. Our survey data suggest that shielding adversely affects both mental and physical health in RD. These data broaden our understanding of shielding, indicating need for further study.

Observational Study of Chlorpromazine in Hospitalized Patients with COVID-19

Introduction

Chlorpromazine has been suggested as being potentially useful in patients with coronavirus disease 2019 (COVID-19) on the grounds of its potential antiviral and anti-inflammatory effects.

Objective

The aim of this study was to examine the association between chlorpromazine use and mortality among adult patients hospitalized for COVID-19.

Methods

We conducted an observational, multicenter, retrospective study at Assistance Publique-Hôpitaux de Paris (AP-HP) Greater Paris University hospitals. Study baseline was defined as the date of first prescription of chlorpromazine during hospitalization for COVID-19. The primary endpoint was death. Among patients who had not been hospitalized in intensive care units (ICUs), we compared this endpoint between those who received chlorpromazine and those who did not, in time-to-event analyses adjusted for patient characteristics, clinical markers of disease severity, and other psychotropic medications. The primary analysis used a Cox regression model with inverse probability weighting. Multiple sensitivity analyses were performed.

Results

Of the 14,340 adult inpatients hospitalized outside ICUs for COVID-19, 55 patients (0.4%) received chlorpromazine. Over a mean follow-up of 14.3 days (standard deviation [SD] 18.2), death occurred in 13 patients (23.6%) who received chlorpromazine and 1289 patients (9.0%) who did not. In the primary analysis, there was no significant association between chlorpromazine use and mortality (hazard ratio [HR] 2.01, 95% confidence interval [CI] 0.75–5.40; p = 0.163). Sensitivity analyses included a Cox regression in a 1:5 ratio matched analytic sample that showed a similar result (HR 1.67, 95% CI 0.91–3.06; p = 0.100) and a multivariable Cox regression that indicated a significant positive association (HR 3.10, 95% CI 1.31–7.34; p = 0.010).

Conclusion

Our results suggest that chlorpromazine prescribed at a mean daily dose of 70.8 mg (SD 65.3) was not associated with reduced mortality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40261-021-01001-0.