The indirect impact of the COVID-19 pandemic on people with type 2 diabetes mellitus and without COVID-19 infection: Systematic review and meta-analysis.

BACKGROUND: The effect directly from the coronavirus disease 2019 (COVID-19) infection on health and fatality has received considerable attention, particularly among people with type 2 diabetes mellitus (T2DM). However, evidence on the indirect impact of disrupted healthcare services during the pandemic on people with T2DM is limited. This systematic review aims to assess the indirect impact of the pandemic on the metabolic management of T2DM people without a history of COVID-19 infection. METHODS: PubMed, Web of Science, and Scopus were systematically searched for studies that compared diabetes-related health outcomes between pre-pandemic and during-pandemic periods in people with T2DM and without the COVID-19 infection and published from January 1, 2020, to July 13, 2022. A meta-analysis was performed to estimate the overall effect on the diabetes indicators, including hemoglobin A1c (HbA1c), lipid profiles, and weight control, with different effect models according to the heterogeneity. RESULTS: Eleven observational studies were included in the final review. No significant changes in HbA1c levels [weighted mean difference (WMD), 0.06 (95% CI -0.12 to 0.24)] and body weight index (BMI) [0.15 (95% CI -0.24 to 0.53)] between the pre-pandemic and during-pandemic were found in the meta-analysis. Four studies reported lipid indicators; most reported insignificant changes in low-density lipoprotein (LDL, n = 2) and high-density lipoprotein (HDL, n = 3); two studies reported an increase in total cholesterol and triglyceride. CONCLUSIONS: This review did not find significant changes in HbA1c and BMI among people with T2DM after data pooling, but a possible worsening in lipids parameters during the COVID-19 pandemic. There were limited data on long-term outcomes and healthcare utilization, which warrants further research. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022360433.

Long-term spill-over impact of COVID-19 on health and healthcare of people with non-communicable diseases: a study protocol for a population-based cohort and health economic study.

INTRODUCTION: The COVID-19 pandemic has a significant spill-over effect on people with non-communicable diseases (NCDs) over the long term, beyond the direct effect of COVID-19 infection. Evaluating changes in health outcomes, health service use and costs can provide evidence to optimise care for people with NCDs during and after the pandemic, and to better prepare outbreak responses in the future. METHODS AND ANALYSIS: This is a population-based cohort study using electronic health records of the Hong Kong Hospital Authority (HA) CMS, economic modelling and serial cross-sectional surveys on health service use. This study includes people aged ≥18 years who have a documented diagnosis of diabetes mellitus, hypertension, cardiovascular disease, cancer, chronic respiratory disease or chronic kidney disease with at least one attendance at the HA hospital or clinic between 1 January 2010 and 31 December 2019, and without COVID-19 infection. Changes in all-cause mortality, disease-specific outcomes, and health services use rates and costs will be assessed between pre-COVID-19 and-post-COVID-19 pandemic or during each wave using an interrupted time series analysis. The long-term health economic impact of healthcare disruptions during the COVID-19 pandemic will be studied using microsimulation modelling. Multivariable Cox proportional hazards regression and Poisson/negative binomial regression will be used to evaluate the effect of different modes of supplementary care on health outcomes. ETHICS AND DISSEMINATION: The study was approved by the institutional review board of the University of Hong Kong, the HA Hong Kong West Cluster (reference number UW 21-297). The study findings will be disseminated through peer-reviewed publications and international conferences.

Development and validation of a diabetes mellitus and prediabetes risk prediction function for case finding in primary care in Hong Kong: a cross-sectional study and a prospective study protocol paper.

INTRODUCTION: Diabetes mellitus (DM) is a major non-communicable disease with an increasing prevalence. Undiagnosed DM is not uncommon and can lead to severe complications and mortality. Identifying high-risk individuals at an earlier disease stage, that is, pre-diabetes (pre-DM), is crucial in delaying progression. Existing risk models mainly rely on non-modifiable factors to predict only the DM risk, and few apply to Chinese people. This study aims to develop and validate a risk prediction function that incorporates modifiable lifestyle factors to detect DM and pre-DM in Chinese adults in primary care. METHODS AND ANALYSIS: A cross-sectional study to develop DM/Pre-DM risk prediction functions using data from the Hong Kong's Population Health Survey (PHS) 2014/2015 and a 12-month prospective study to validate the functions in case finding of individuals with DM/pre-DM. Data of 1857 Chinese adults without self-reported DM/Pre-DM will be extracted from the PHS 2014/2015 to develop DM/Pre-DM risk models using logistic regression and machine learning methods. 1014 Chinese adults without a known history of DM/Pre-DM will be recruited from public and private primary care clinics in Hong Kong. They will complete a questionnaire on relevant risk factors and blood tests on Oral Glucose Tolerance Test (OGTT) and haemoglobin A1C (HbA1c) on recruitment and, if the first blood test is negative, at 12 months. A positive case is DM/pre-DM defined by OGTT or HbA1c in any blood test. Area under receiver operating characteristic curve, sensitivity, specificity, positive predictive value and negative predictive value of the models in detecting DM/pre-DM will be calculated. ETHICS AND DISSEMINATION: Ethics approval has been received from The University of Hong Kong/Hong Kong Hospital Authority Hong Kong West Cluster (UW19-831) and Hong Kong Hospital Authority Kowloon Central/Kowloon East Cluster (REC(KC/KE)-21-0042/ER-3). The study results will be submitted for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: US ClinicalTrial.gov: NCT04881383; HKU clinical trials registry: HKUCTR-2808; Pre-results.