Ethnic minority representation in UK COVID-19 trials: systematic review and meta-analysis.

BACKGROUND: The COVID-19 pandemic has highlighted health disparities affecting ethnic minority communities. There is growing concern about the lack of diversity in clinical trials. This study aimed to assess the representation of ethnic groups in UK-based COVID-19 randomised controlled trials (RCTs). METHODS: A systematic review and meta-analysis were undertaken. A search strategy was developed for MEDLINE (Ovid) and Google Scholar (1st January 2020-4th May 2022). Prospective COVID-19 RCTs for vaccines or therapeutics that reported UK data separately with a minimum of 50 participants were eligible. Search results were independently screened, and data extracted into proforma. Percentage of ethnic groups at all trial stages was mapped against Office of National Statistics (ONS) statistics. Post hoc DerSimonian-Laird random-effects meta-analysis of percentages and a meta-regression assessing recruitment over time were conducted. Due to the nature of the review question, risk of bias was not assessed. Data analysis was conducted in Stata v17.0. A protocol was registered (PROSPERO CRD42021244185). RESULTS: In total, 5319 articles were identified; 30 studies were included, with 118,912 participants. Enrolment to trials was the only stage consistently reported (17 trials). Meta-analysis showed significant heterogeneity across studies, in relation to census-expected proportions at study enrolment. All ethnic groups, apart from Other (1.7% [95% CI 1.1-2.8%] vs ONS 1%) were represented to a lesser extent than ONS statistics, most marked in Black (1% [0.6-1.5%] vs 3.3%) and Asian (5.8% [4.4-7.6%] vs 7.5%) groups, but also apparent in White (84.8% [81.6-87.5%] vs 86%) and Mixed 1.6% [1.2-2.1%] vs 2.2%) groups. Meta-regression showed recruitment of Black participants increased over time (p = 0.009). CONCLUSIONS: Asian, Black and Mixed ethnic groups are under-represented or incorrectly classified in UK COVID-19 RCTs. Reporting by ethnicity lacks consistency and transparency. Under-representation in clinical trials occurs at multiple levels and requires complex solutions, which should be considered throughout trial conduct. These findings may not apply outside of the UK setting.

Weight management strategies in Middle-Aged Women (MAW): Development and validation of a questionnaire based on the Oxford Food and Activity Behaviors Taxonomy (OxFAB-MAW) in a Portuguese sample.

Background: The Oxford Food and Activity Behaviors (OxFAB) taxonomy systematize the cognitive-behavioral strategies adopted by individuals who are attempting to manage their weight. The present study aimed to (1) develop a questionnaire based on the OxFAB taxonomy, specifically adapted for middle-aged women-the OxFAB-MAW-stage of life and sex, which present a high incidence of obesity, (2) assess the psychometric properties of this tool, and (3) evaluate the discriminative power of the OxFAB-MAW (normal weight vs. obesity). Methods: Overall, 1,367 Portuguese middle-aged women between 45 and 65 years (M = 52.3, SD = 5.15) filled in a sociodemographic, health, and menopause-related questionnaire, as well as the OxFAB-MAW. Results: Confirmatory factor analysis demonstrated an acceptable model fit (comparative fit index = 0.928, Tucker-Lewis index = 0.913, root mean square error of approximation = 0.072, and standardized root mean square residual = 0.054). Five domains with one item were grouped into other domains, and the Weight Management Aids domain was also removed. The OxFAB-MAW showed factorial, convergent, discriminant, and external validity, as well as composite reliability. Conclusion: The OxFAB-MAW questionnaire is a valid, reliable, and theory-driven tool for assessing weight management strategies in middle-aged women, being able to discriminate between clinical and non-clinical groups (normal weight vs. obesity) in several domains. This instrument can be used to gather valid and reliable data, useful in both research and clinical settings (especially focused on structuring interventions and preventive obesity programs within this specific life cycle stage).

The impact of obesity on severe disease and mortality in people with SARS-CoV-2: A systematic review and meta-analysis.

Background: Obesity accompanied by excess ectopic fat storage has been postulated as a risk factor for severe disease in people with SARS-CoV-2 through the stimulation of inflammation, functional immunologic deficit and a pro-thrombotic disseminated intravascular coagulation with associated high rates of venous thromboembolism. Methods: Observational studies in COVID-19 patients reporting data on raised body mass index at admission and associated clinical outcomes were identified from MEDLINE, Embase, Web of Science and the Cochrane Library up to 16 May 2020. Mean differences and relative risks (RR) with 95% confidence intervals (CIs) were aggregated using random effects models. Results: Eight retrospective cohort studies and one cohort prospective cohort study with data on of 4,920 patients with COVID-19 were eligible. Comparing BMI ≥ 25 vs <25 kg/m2, the RRs (95% CIs) of severe illness and mortality were 2.35 (1.43-3.86) and 3.52 (1.32-9.42), respectively. In a pooled analysis of three studies, the RR (95% CI) of severe illness comparing BMI > 35 vs <25 kg/m2 was 7.04 (2.72-18.20). High levels of statistical heterogeneity were partly explained by age; BMI ≥ 25 kg/m2 was associated with an increased risk of severe illness in older age groups (≥60 years), whereas the association was weaker in younger age groups (<60 years). Conclusions: Excess adiposity is a risk factor for severe disease and mortality in people with SARS-CoV-2 infection. This was particularly pronounced in people 60 and older. The increased risk of worse outcomes from SARS-CoV-2 infection in people with excess adiposity should be taken into account when considering individual and population risks and when deciding on which groups to target for public health messaging on prevention and detection measures. Systematic review registration: PROSPERO 2020: CRD42020179783.

The impact of the COVID-19 pandemic on glycaemic control in people with diabetes: A systematic review and meta-analysis.

AIM: To identify, appraise and synthesize the available evidence on the impact of the coronavirus disease 2019 (COVID-19) pandemic and lockdown (LD) on glycaemic control in people with diabetes. MATERIALS AND METHODS: We searched multiple databases up to 2 February 2021 for studies reporting HbA1c, time in range (TIR), average or fasting glucose, severe hypoglycaemia and diabetic ketoacidosis. Data were pooled using random effects meta-analysis and are presented as mean difference (MD) with 95% confidence intervals (CI). This review was preregistered on PROSPERO (CRD42020179319). RESULTS: We include 59 studies; 44 (n = 15 464) were included in quantitative syntheses and 15 were narratively synthesized. Pooled data were grouped by diabetes type. Results from 28 studies (n = 5048 type 1 diabetes [T1D] and combined diabetes participants) showed that TIR increased during LD compared with before LD (MD 2.74%, 95% CI 1.80% to 3.69%). Data from 10 studies (n = 1294 T1D participants) showed that TIR increased after LD compared with before LD (MD 5.14%, 95% CI 3.12% to 7.16%). Pooled results from 12 studies (n = 4810 T1D and type 2 diabetes participants) resulted in average glucose decreasing after LD compared with before LD (MD -6.86 mg/dl, 95% CI -8.54 to -5.18). Results for other outcomes, including HbA1c, were not statistically significantly different. CONCLUSIONS: The COVID-19 pandemic was associated with small improvements across multiple outcomes of glycaemic control, although there was insufficient evidence to suggest that this led to changes in HbA1c. Most evidence came from people with access to diabetes technologies in high-income countries; more research is needed in less advantaged populations.

Heated tobacco products for smoking cessation and reducing smoking prevalence.

BACKGROUND: Heated tobacco products (HTPs) are designed to heat tobacco to a high enough temperature to release aerosol, without burning it or producing smoke. They differ from e-cigarettes because they heat tobacco leaf/sheet rather than a liquid. Companies who make HTPs claim they produce fewer harmful chemicals than conventional cigarettes. Some people report stopping smoking cigarettes entirely by switching to using HTPs, so clinicians need to know whether they are effective for this purpose and relatively safe. Also, to regulate HTPs appropriately, policymakers should understand their impact on health and on cigarette smoking prevalence. OBJECTIVES: To evaluate the effectiveness and safety of HTPs for smoking cessation and the impact of HTPs on smoking prevalence.  SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group's Specialised Register, CENTRAL, MEDLINE, and six other databases for relevant records to January 2021, together with reference-checking and contact with study authors and relevant groups. SELECTION CRITERIA: We included randomised controlled trials (RCTs) in which people who smoked cigarettes were randomised to switch to exclusive HTP use or a control condition. Eligible outcomes were smoking cessation, adverse events, and selected biomarkers.  RCTs conducted in clinic or in an ambulatory setting were deemed eligible when assessing safety, including those randomising participants to exclusively use HTPs, smoke cigarettes, or attempt abstinence from all tobacco. Time-series studies were also eligible for inclusion if they examined the population-level impact of heated tobacco on smoking prevalence or cigarette sales as an indirect measure. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking at the longest follow-up point available, adverse events, serious adverse events, and changes in smoking prevalence or cigarette sales. Other outcomes included biomarkers of harm and exposure to toxicants/carcinogens (e.g. NNAL and carboxyhaemoglobin (COHb)). We used a random-effects Mantel-Haenszel model to calculate risk ratios (RR) with 95% confidence intervals (CIs) for dichotomous outcomes. For continuous outcomes, we calculated mean differences on the log-transformed scale (LMD) with 95% CIs. We pooled data across studies using meta-analysis where possible. MAIN RESULTS: We included 13 completed studies, of which 11 were RCTs assessing safety (2666 participants) and two were time-series studies. We judged eight RCTs to be at unclear risk of bias and three at high risk. All RCTs were funded by tobacco companies. Median length of follow-up was 13 weeks. No studies reported smoking cessation outcomes.  There was insufficient evidence for a difference in risk of adverse events between smokers randomised to switch to heated tobacco or continue smoking cigarettes, limited by imprecision and risk of bias (RR 1.03, 95% CI 0.92 to 1.15; I2 = 0%; 6 studies, 1713 participants). There was insufficient evidence to determine whether risk of serious adverse events differed between groups due to very serious imprecision and risk of bias (RR 0.79, 95% CI 0.33 to 1.94; I2 = 0%; 4 studies, 1472 participants). There was moderate-certainty evidence for lower NNAL and COHb at follow-up in heated tobacco than cigarette smoking groups, limited by risk of bias (NNAL: LMD -0.81, 95% CI -1.07 to -0.55; I2 = 92%; 10 studies, 1959 participants; COHb: LMD -0.74, 95% CI -0.92 to -0.52; I2 = 96%; 9 studies, 1807 participants). Evidence for additional biomarkers of exposure are reported in the main body of the review. There was insufficient evidence for a difference in risk of adverse events in smokers randomised to switch to heated tobacco or attempt abstinence from all tobacco, limited by risk of bias and imprecision (RR 1.12, 95% CI 0.86 to 1.46; I2 = 0%; 2 studies, 237 participants). Five studies reported that no serious adverse events occurred in either group (533 participants). There was moderate-certainty evidence, limited by risk of bias, that urine concentrations of NNAL at follow-up were higher in the heated tobacco use compared with abstinence group (LMD 0.50, 95% CI 0.34 to 0.66; I2 = 0%; 5 studies, 382 participants). In addition, there was very low-certainty evidence, limited by risk of bias, inconsistency, and imprecision, for higher COHb in the heated tobacco use compared with abstinence group for intention-to-treat analyses (LMD 0.69, 95% CI 0.07 to 1.31; 3 studies, 212 participants), but lower COHb in per-protocol analyses (LMD -0.32, 95% CI -1.04 to 0.39; 2 studies, 170 participants). Evidence concerning additional biomarkers is reported in the main body of the review. Data from two time-series studies showed that the rate of decline in cigarette sales accelerated following the introduction of heated tobacco to market in Japan. This evidence was of very low-certainty as there was risk of bias, including possible confounding, and cigarette sales are an indirect measure of smoking prevalence. AUTHORS' CONCLUSIONS: No studies reported on cigarette smoking cessation, so the effectiveness of heated tobacco for this purpose remains uncertain. There was insufficient evidence for differences in risk of adverse or serious adverse events between people randomised to switch to heated tobacco, smoke cigarettes, or attempt tobacco abstinence in the short-term. There was moderate-certainty evidence that heated tobacco users have lower exposure to toxicants/carcinogens than cigarette smokers and very low- to moderate-certainty evidence of higher exposure than those attempting abstinence from  all tobacco. Independently funded research on the effectiveness and safety of HTPs is needed.  The rate of decline in cigarette sales accelerated after the introduction of heated tobacco to market in Japan but, as data were observational, it is possible other factors caused these changes. Moreover, falls in cigarette sales may not translate to declining smoking prevalence, and changes in Japan may not generalise elsewhere. To clarify the impact of rising heated tobacco use on smoking prevalence, there is a need for time-series studies that examine this association.

Interventions for preventing weight gain after smoking cessation.

BACKGROUND: Most people who stop smoking gain weight. This can discourage some people from making a quit attempt and risks offsetting some, but not all, of the health advantages of quitting. Interventions to prevent weight gain could improve health outcomes, but there is a concern that they may undermine quitting. OBJECTIVES: To systematically review the effects of: (1) interventions targeting post-cessation weight gain on weight change and smoking cessation (referred to as 'Part 1') and (2) interventions designed to aid smoking cessation that plausibly affect post-cessation weight gain (referred to as 'Part 2'). SEARCH METHODS: Part 1 - We searched the Cochrane Tobacco Addiction Group's Specialized Register and CENTRAL; latest search 16 October 2020. Part 2 - We searched included studies in the following 'parent' Cochrane reviews: nicotine replacement therapy (NRT), antidepressants, nicotine receptor partial agonists, e-cigarettes, and exercise interventions for smoking cessation published in Issue 10, 2020 of the Cochrane Library. We updated register searches for the review of nicotine receptor partial agonists. SELECTION CRITERIA: Part 1 - trials of interventions that targeted post-cessation weight gain and had measured weight at any follow-up point or smoking cessation, or both, six or more months after quit day. Part 2 - trials included in the selected parent Cochrane reviews reporting weight change at any time point. DATA COLLECTION AND ANALYSIS: Screening and data extraction followed standard Cochrane methods. Change in weight was expressed as difference in weight change from baseline to follow-up between trial arms and was reported only in people abstinent from smoking. Abstinence from smoking was expressed as a risk ratio (RR). Where appropriate, we performed meta-analysis using the inverse variance method for weight, and Mantel-Haenszel method for smoking. MAIN RESULTS: Part 1: We include 37 completed studies; 21 are new to this update. We judged five studies to be at low risk of bias, 17 to be at unclear risk and the remainder at high risk.  An intermittent very low calorie diet (VLCD) comprising full meal replacement provided free of charge and accompanied by intensive dietitian support significantly reduced weight gain at end of treatment compared with education on how to avoid weight gain (mean difference (MD) -3.70 kg, 95% confidence interval (CI) -4.82 to -2.58; 1 study, 121 participants), but there was no evidence of benefit at 12 months (MD -1.30 kg, 95% CI -3.49 to 0.89; 1 study, 62 participants). The VLCD increased the chances of abstinence at 12 months (RR 1.73, 95% CI 1.10 to 2.73; 1 study, 287 participants). However, a second study  found that no-one completed the VLCD intervention or achieved abstinence. Interventions aimed at increasing acceptance of weight gain reported mixed effects at end of treatment, 6 months and 12 months with confidence intervals including both increases and decreases in weight gain compared with no advice or health education. Due to high heterogeneity, we did not combine the data. These interventions increased quit rates at 6 months (RR 1.42, 95% CI 1.03 to 1.96; 4 studies, 619 participants; I2 = 21%), but there was no evidence at 12 months (RR 1.25, 95% CI 0.76 to 2.06; 2 studies, 496 participants; I2 = 26%). Some pharmacological interventions tested for limiting post-cessation weight gain (PCWG) reduced weight gain at the end of treatment (dexfenfluramine, phenylpropanolamine, naltrexone). The effects of ephedrine and caffeine combined, lorcaserin, and chromium were too imprecise to give useful estimates of treatment effects. There was very low-certainty evidence that personalized weight management support reduced weight gain at end of treatment (MD -1.11 kg, 95% CI -1.93 to -0.29; 3 studies, 121 participants; I2 = 0%), but no evidence in the longer-term 12 months (MD -0.44 kg, 95% CI -2.34 to 1.46; 4 studies, 530 participants; I2 = 41%). There was low to very low-certainty evidence that detailed weight management education without personalized assessment, planning and feedback did not reduce weight gain and may have reduced smoking cessation rates (12 months: MD -0.21 kg, 95% CI -2.28 to 1.86; 2 studies, 61 participants; I2 = 0%; RR for smoking cessation 0.66, 95% CI 0.48 to 0.90; 2 studies, 522 participants; I2 = 0%). Part 2: We include 83 completed studies, 27 of which are new to this update. There was low certainty that exercise interventions led to minimal or no weight reduction compared with standard care at end of treatment (MD -0.25 kg, 95% CI -0.78 to 0.29; 4 studies, 404 participants; I2 = 0%). However, weight was reduced at 12 months (MD -2.07 kg, 95% CI -3.78 to -0.36; 3 studies, 182 participants; I2 = 0%). Both bupropion and fluoxetine limited weight gain at end of treatment (bupropion MD -1.01 kg, 95% CI -1.35 to -0.67; 10 studies, 1098 participants; I2 = 3%); (fluoxetine MD -1.01 kg, 95% CI -1.49 to -0.53; 2 studies, 144 participants; I2 = 38%; low- and very low-certainty evidence, respectively). There was no evidence of benefit at 12 months for bupropion, but estimates were imprecise (bupropion MD -0.26 kg, 95% CI -1.31 to 0.78; 7 studies, 471 participants; I2 = 0%). No studies of fluoxetine provided data at 12 months. There was moderate-certainty that NRT reduced weight at end of treatment (MD -0.52 kg, 95% CI -0.99 to -0.05; 21 studies, 2784 participants; I2 = 81%) and moderate-certainty that the effect may be similar at 12 months (MD -0.37 kg, 95% CI -0.86 to 0.11; 17 studies, 1463 participants; I2 = 0%), although the estimates are too imprecise to assess long-term benefit. There was mixed evidence of the effect of varenicline on weight, with high-certainty evidence that weight change was very modestly lower at the end of treatment (MD -0.23 kg, 95% CI -0.53 to 0.06; 14 studies, 2566 participants; I2 = 32%); a low-certainty estimate gave an imprecise estimate of higher weight at 12 months (MD 1.05 kg, 95% CI -0.58 to 2.69; 3 studies, 237 participants; I2 = 0%). AUTHORS' CONCLUSIONS: Overall, there is no intervention for which there is moderate certainty of a clinically useful effect on long-term weight gain. There is also no moderate- or high-certainty evidence that interventions designed to limit weight gain reduce the chances of people achieving abstinence from smoking.

Association between smoking, e-cigarette use and severe COVID-19: a cohort study.

BACKGROUND: Smoking is a risk factor for most respiratory infections, but it may protect against SARS-CoV-2 infection. The objective was to assess whether smoking and e-cigarette use were associated with severe COVID-19. METHODS: This cohort ran from 24 January 2020 until 30 April 2020 at the height of the first wave of the SARS-CoV-2 epidemic in England. It comprised 7 869 534 people representative of the population of England with smoking status, demographic factors and diseases recorded by general practitioners in the medical records, which were linked to hospital and death data. The outcomes were COVID-19-associated hospitalization, intensive care unit (ICU) admission and death. The associations between smoking and the outcomes were assessed with Cox proportional hazards models, with sequential adjustment for confounding variables and indirect causal factors (body mass index and smoking-related disease). RESULTS: Compared with never smokers, people currently smoking were at lower risk of COVID-19 hospitalization, adjusted hazard ratios (HRs) were 0.64 (95% confidence intervals 0.60 to 0.69) for <10 cigarettes/day, 0.49 (0.41 to 0.59) for 10-19 cigarettes/day, and 0.61 (0.49 to 0.74) for ≥20 cigarettes/day. For ICU admission, the corresponding HRs were 0.31 (0.24 to 0.40), 0.15 (0.06 to 0.36), and 0.35 (0.17 to 0.74) and death were: 0.79 (0.70 to 0.89), 0.66 (0.48 to 0.90), and 0.77 (0.54 to 1.09) respectively. Former smokers were at higher risk of severe COVID-19: HRs: 1.07 (1.03 to 1.11) for hospitalization, 1.17 (1.04 to 1.31) for ICU admission, and 1.17 (1.10 to 1.24) for death. All-cause mortality was higher for current smoking than never smoking, HR 1.42 (1.36 to 1.48). Among e-cigarette users, the adjusted HR for e-cigarette use and hospitalization with COVID-19 was 1.06 (0.88 to 1.28), for ICU admission was 1.04 (0.57 to 1.89, and for death was 1.12 (0.81 to 1.55). CONCLUSIONS: Current smoking was associated with a reduced risk of severe COVID-19 but the association with e-cigarette use was unclear. All-cause mortality remained higher despite this possible reduction in death from COVID-19 during an epidemic of SARS-CoV-2. Findings support investigating possible protective mechanisms of smoking for SARS-CoV-2 infection, including the ongoing trials of nicotine to treat COVID-19.

Risks of infection, hospital and ICU admission, and death from COVID-19 in people with asthma: systematic review and meta-analyses.

OBJECTIVES: To determine if and to what degree asthma may predispose to worse COVID-19 outcomes in order to inform treatment and prevention decisions, including shielding and vaccine prioritisation. DESIGN: Systematic review and meta-analysis. SETTING: Electronic databases were searched (October 2020) for clinical studies reporting at least one of the following stratified by asthma status: risk of infection with SARS-CoV-2; hospitalisation, intensive care unit (ICU) admission or mortality with COVID-19. PARTICIPANTS: Adults and children who tested positive for or were suspected to have COVID-19. MAIN OUTCOME MEASURES: Main outcome measures were the following stratified by asthma status: risk of infection with SARS-CoV-2; hospitalisation, ICU admission or mortality with COVID-19. We pooled odds ratios (ORs) and presented these with 95% confidence intervals (CI). Certainty was assessed using GRADE (Grading of Recommendations, Assessment, Development and Evaluations). RESULTS: 30 (n=112 420) studies were included (12 judged high quality, 15 medium, 3 low). Few provided indication of asthma severity. Point estimates indicated reduced risks in people with asthma for all outcomes, but in all cases the evidence was judged to be of very low certainty and 95% CIs all included no difference and the possibility of increased risk (death: OR 0.90, 95% CI 0.72 to 1.13, I2=58%; hospitalisation: OR 0.95, 95% CI 0.71 to 1.26; ICU admission: OR 0.96, 95% CI 0.75 to 1.24). Findings on hospitalisation are also limited by substantial unexplained statistical heterogeneity. Within people with asthma, allergic asthma was associated with less COVID-19 risk and concurrent chronic obstructive pulmonary disease was associated with increased risk. In some studies, corticosteroids were associated with increased risk, but this may reflect increased risk in people with more severe asthma. CONCLUSIONS: Though absence of evidence of a clear association between asthma and worse outcomes from COVID-19 should not be interpreted as evidence of absence, the data reviewed indicate that risks from COVID-19 in people with asthma, as a whole, may be less than originally anticipated.

Risks of and From SARS-CoV-2 Infection and COVID-19 in People With Diabetes: A Systematic Review of Reviews.

BACKGROUND: This review was commissioned by the World Health Organization and presents a summary of the latest research evidence on the impact of coronavirus disease 2019 (COVID-19) on people with diabetes (PWD). PURPOSE: To review the evidence regarding the extent to which PWD are at increased risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and/or of suffering its complications, including associated mortality. DATA SOURCES: We searched the Cochrane COVID-19 Study Register, Embase, MEDLINE, and LitCOVID on 3 December 2020. STUDY SELECTION: Systematic reviews synthesizing data on PWD exposed to SARS-CoV-2 infection, reporting data on confirmed SARS-CoV-2 infection, admission to hospital and/or to intensive care unit (ICU) with COVID-19, and death with COVID-19 were used. DATA EXTRACTION: One reviewer appraised and extracted data; data were checked by a second. DATA SYNTHESIS: Data from 112 systematic reviews were narratively synthesized and displayed using effect direction plots. Reviews provided consistent evidence that diabetes is a risk factor for severe disease and death from COVID-19. Fewer data were available on ICU admission, but where available, these data also signaled increased risk. Within PWD, higher blood glucose levels both prior to and during COVID-19 illness were associated with worse COVID-19 outcomes. Type 1 diabetes was associated with worse outcomes than type 2 diabetes. There were no appropriate data for discerning whether diabetes was a risk factor for acquiring SARS-CoV-2 infection. LIMITATIONS: Due to the nature of the review questions, the majority of data contributing to included reviews come from retrospective observational studies. Reviews varied in the extent to which they assessed risk of bias. CONCLUSIONS: There are no data on whether diabetes predisposes to infection with SARS-CoV-2. Data consistently show that diabetes increases risk of severe COVID-19. As both diabetes and worse COVID-19 outcomes are associated with socioeconomic disadvantage, their intersection warrants particular attention.

Association between pre-existing respiratory disease and its treatment, and severe COVID-19: a population cohort study.

BACKGROUND: Previous studies suggested that the prevalence of chronic respiratory disease in patients hospitalised with COVID-19 was lower than its prevalence in the general population. The aim of this study was to assess whether chronic lung disease or use of inhaled corticosteroids (ICS) affects the risk of contracting severe COVID-19. METHODS: In this population cohort study, records from 1205 general practices in England that contribute to the QResearch database were linked to Public Health England's database of SARS-CoV-2 testing and English hospital admissions, intensive care unit (ICU) admissions, and deaths for COVID-19. All patients aged 20 years and older who were registered with one of the 1205 general practices on Jan 24, 2020, were included in this study. With Cox regression, we examined the risks of COVID-19-related hospitalisation, admission to ICU, and death in relation to respiratory disease and use of ICS, adjusting for demographic and socioeconomic status and comorbidities associated with severe COVID-19. FINDINGS: Between Jan 24 and April 30, 2020, 8 256 161 people were included in the cohort and observed, of whom 14 479 (0·2%) were admitted to hospital with COVID-19, 1542 (<0·1%) were admitted to ICU, and 5956 (0·1%) died. People with some respiratory diseases were at an increased risk of hospitalisation (chronic obstructive pulmonary disease [COPD] hazard ratio [HR] 1·54 [95% CI 1·45-1·63], asthma 1·18 [1·13-1·24], severe asthma 1·29 [1·22-1·37; people on three or more current asthma medications], bronchiectasis 1·34 [1·20-1·50], sarcoidosis 1·36 [1·10-1·68], extrinsic allergic alveolitis 1·35 [0·82-2·21], idiopathic pulmonary fibrosis 1·59 [1·30-1·95], other interstitial lung disease 1·66 [1·30-2·12], and lung cancer 2·24 [1·89-2·65]) and death (COPD 1·54 [1·42-1·67], asthma 0·99 [0·91-1·07], severe asthma 1·08 [0·98-1·19], bronchiectasis 1·12 [0·94-1·33], sarcoidosis 1·41 [0·99-1·99), extrinsic allergic alveolitis 1·56 [0·78-3·13], idiopathic pulmonary fibrosis 1·47 [1·12-1·92], other interstitial lung disease 2·05 [1·49-2·81], and lung cancer 1·77 [1·37-2·29]) due to COVID-19 compared with those without these diseases. Admission to ICU was rare, but the HR for people with asthma was 1·08 (0·93-1·25) and severe asthma was 1·30 (1·08-1·58). In a post-hoc analysis, relative risks of severe COVID-19 in people with respiratory disease were similar before and after shielding was introduced on March 23, 2020. In another post-hoc analysis, people with two or more prescriptions for ICS in the 150 days before study start were at a slightly higher risk of severe COVID-19 compared with all other individuals (ie, no or one ICS prescription): HR 1·13 (1·03-1·23) for hospitalisation, 1·63 (1·18-2·24) for ICU admission, and 1·15 (1·01-1·31) for death. INTERPRETATION: The risk of severe COVID-19 in people with asthma is relatively small. People with COPD and interstitial lung disease appear to have a modestly increased risk of severe disease, but their risk of death from COVID-19 at the height of the epidemic was mostly far lower than the ordinary risk of death from any cause. Use of inhaled steroids might be associated with a modestly increased risk of severe COVID-19. FUNDING: National Institute for Health Research Oxford Biomedical Research Centre and the Wellcome Trust.

Asthma and COVID-19: review of evidence on risks and management considerations.

BACKGROUND: Respiratory illnesses typically present increased risks to people with asthma (PWA). However, data on the risks of COVID-19 to PWA have presented contradictory findings, with implications for asthma management. OBJECTIVE: To assess the risks and management considerations of COVID-19 in people with asthma (PWA). METHOD: We conducted a rapid literature review. We searched PubMed, medRxiv, LitCovid, TRIP, Google and Google Scholar for terms relating to asthma and COVID-19, and for systematic reviews related to specific management questions within our review, in April 2020. References were screened and data were extracted by one reviewer. RESULTS: We extracted data from 139 references. The evidence available is limited, with some sources suggesting an under-representation of PWA in hospitalised cases and others showing an increased risk of worse outcomes in PWA, which may be associated with disease severity. Consensus broadly holds that asthma medications should be continued as usual. Almost all aspects of asthma care will be disrupted during the pandemic due not only to limits in face-to-face care but also to the fact that many of the diagnostic tools used in asthma are considered aerosol-generating procedures. Self-management and remote interventions may be of benefit for asthma care during this time but have not been tested in this context. CONCLUSIONS: Evidence on COVID-19 and asthma is limited and continuing to emerge. More research is needed on the possible associations between asthma and COVID-19 infection and severity, as well as on interventions to support asthma care in light of constraints and disruptions to healthcare systems. We found no evidence regarding health inequalities, and this urgently needs to be addressed in the literature as the burdens of asthma and of COVID-19 are not equally distributed across the population.

Diabetes and COVID-19: Risks, Management, and Learnings From Other National Disasters.

Evidence relating to the impact of COVID-19 in people with diabetes (PWD) is limited but continuing to emerge. PWD appear to be at increased risk of more severe COVID-19 infection, though evidence quantifying the risk is highly uncertain. The extent to which clinical and demographic factors moderate this relationship is unclear, though signals are emerging that link higher BMI and higher HbA1c to worse outcomes in PWD with COVID-19. As well as posing direct immediate risks to PWD, COVID-19 also risks contributing to worse diabetes outcomes due to disruptions caused by the pandemic, including stress and changes to routine care, diet, and physical activity. Countries have used various strategies to support PWD during this pandemic. There is a high potential for COVID-19 to exacerbate existing health disparities, and research and practice guidelines need to take this into account. Evidence on the management of long-term conditions during national emergencies suggests various ways to mitigate the risks presented by these events.