Non-laboratory-based risk assessment model for case detection of diabetes mellitus and pre-diabetes in primary care.

INTRODUCTION: More than half of diabetes mellitus (DM) and pre-diabetes (pre-DM) cases remain undiagnosed, while existing risk assessment models are limited by focusing on diabetes mellitus only (omitting pre-DM) and often lack lifestyle factors such as sleep. This study aimed to develop a non-laboratory risk assessment model to detect undiagnosed diabetes mellitus and pre-diabetes mellitus in Chinese adults. METHODS: Based on a population-representative dataset, 1,857 participants aged 18-84 years without self-reported diabetes mellitus, pre-diabetes mellitus, and other major chronic diseases were included. The outcome was defined as a newly detected diabetes mellitus or pre-diabetes by a blood test. The risk models were developed using logistic regression (LR) and interpretable machine learning (ML) methods. Models were validated using area under the receiver-operating characteristic curve (AUC-ROC), precision-recall curve (AUC-PR), and calibration plots. Two existing diabetes mellitus risk models were included for comparison. RESULTS: The prevalence of newly diagnosed diabetes mellitus and pre-diabetes mellitus was 15.08%. In addition to known risk factors (age, BMI, WHR, SBP, waist circumference, and smoking status), we found that sleep duration, and vigorous recreational activity time were also significant risk factors of diabetes mellitus and pre-diabetes mellitus. Both LR (AUC-ROC = 0.812, AUC-PR = 0.448) and ML models (AUC-ROC = 0.822, AUC-PR = 0.496) performed well in the validation sample with the ML model showing better discrimination and calibration. The performance of the models was better than the two existing models. CONCLUSIONS: Sleep duration and vigorous recreational activity time are modifiable risk factors of diabetes mellitus and pre-diabetes in Chinese adults. Non-laboratory-based risk assessment models that incorporate these lifestyle factors can enhance case detection of diabetes mellitus and pre-diabetes.

Clinical Audit on Chronic Obstructive Pulmonary Disease (COPD) Management in Primary Care: A Quality Improvement Project from Hong Kong.

Objective: To enhance the quality of COPD management in primary care via a two-phase clinical audit in Hong Kong. Methods: COPD patients aged 40 or above and had attended any of the 73 public primary care clinics under the Hospital Authority of Hong Kong (HAHK) for follow up (FU) during the audit period were included. Performance of six evidence-based audit criteria on COPD care was reviewed in phase 1 from 1st April 2017 to 31st March 2018. Service gaps were identified and a series of quality improvement strategies were executed in the one-year implementation phase. The outcome of the service enhancement was assessed in phase 2 from 1st April 2019 to 31st March 2020. Student's t-test and the chi-square test were used to examine the statistically significant differences between the two phases. Results: Totally 10,385 COPD cases were identified in phase 1, the majority were male (87.7%) and the mean age was 75.3±9.9 years. Among the 3102 active smokers, 1788 (57.6%) were referred to receive the smoking cessation counselling and 1578 (50.9%) actually attended it. A total of 4866 cases (46.9%) received seasonal influenza vaccine (SIV) and 4227 cases (40.7%) received pneumococcal vaccine (PCV). A total of 1983 patients (19.1%) had spirometry test done before and 1327 patients (12.8%) had history of hospital admission due to acute exacerbation of COPD (AECOPD). After the proactive implementation phase, performance on all criteria was significantly improved in phase 2, with a marked increase in the SIV and PCV uptake rate and spirometry performance rate. Most importantly, a significant reduction in AECOPD rate leading to hospital admission had been achieved (9.6%, P<0.00001). Conclusion: COPD care at all public primary care clinics of HAHK had been significantly improved for all audit criteria via the systematic team approach, which, in turn, reduced the hospital admission rate and helped relieve the burden of the health care system.