Lowering Barriers to Health Risk Assessments in Promoting Personalized Health Management.

This study investigates the feasibility of accurately predicting adverse health events without relying on costly data acquisition methods, such as laboratory tests, in the era of shifting healthcare paradigms towards community-based health promotion and personalized preventive healthcare through individual health risk assessments (HRAs). We assessed the incremental predictive value of four categories of predictor variables-demographic, lifestyle and family history, personal health device, and laboratory data-organized by data acquisition costs in the prediction of the risks of mortality and five chronic diseases. Machine learning methodologies were employed to develop risk prediction models, assess their predictive performance, and determine feature importance. Using data from the National Sample Cohort of the Korean National Health Insurance Service (NHIS), which includes eligibility, medical check-up, healthcare utilization, and mortality data from 2002 to 2019, our study involved 425,148 NHIS members who underwent medical check-ups between 2009 and 2012. Models using demographic, lifestyle, family history, and personal health device data, with or without laboratory data, showed comparable performance. A feature importance analysis in models excluding laboratory data highlighted modifiable lifestyle factors, which are a superior set of variables for developing health guidelines. Our findings support the practicality of precise HRAs using demographic, lifestyle, family history, and personal health device data. This approach addresses HRA barriers, particularly for healthy individuals, by eliminating the need for costly and inconvenient laboratory data collection, advancing accessible preventive health management strategies.

The Risk of Type 2 Diabetes Mellitus according to Changes in Obesity Status in Late Middle-Aged Adults: A Nationwide Cohort Study of Korea.

BACKGRUOUND: Although obesity is a well-known risk factor of type 2 diabetes mellitus (T2DM), there is scant data on discriminating the contribution of previous obesity and recent weight gain on developing T2DM. METHODS: We analyzed the Korean National Health Insurance Service-Health Screening Cohort data from 2002 to 2015 where Korean residents underwent biennial health checkups. Participants were classified into four groups according to their obesity status (body mass index [BMI] ≥25 kg/m2) before and after turning 50 years old: maintaining normal (MN), becoming obese (BO), becoming normal (BN), and maintaining obese (MO). Cox proportional hazards regression model was used to estimate the risk of T2DM factoring in the covariates age, sex, BMI, presence of impaired fasting glucose or hypertension, family history of diabetes, and smoking status. RESULTS: A total of 118,438 participants (mean age, 52.5±1.1 years; men, 45.2%) were prospectively evaluated for incident T2DM. A total of 7,339 (6.2%) participants were diagnosed with T2DM during a follow-up period of 4.8±2.6 years. Incidence rates of T2DM per 1,000 person-year were 9.20 in MN, 14.81 in BO, 14.42 in BN, 21.38 in MO. After factoring in covariates, participants in the groups BN (adjusted hazard ratio [aHR], 1.15; 95% confidence interval [CI], 1.04 to 1.27) and MO (aHR, 1.14; 95% CI, 1.06 to 1.24) were at increased risk of developing T2DM compared to MN, whereas BO (hazard ratio, 1.06; 95% CI, 0.96 to 1.17) was not. CONCLUSION: Having been obese before 50 years old increased the risk of developing T2DM in the future, but becoming obese after 50 did not. Therefore, it is important to maintain normal weight from early adulthood to prevent future metabolic perturbations.

Association of Dexmedetomidine With New-Onset Atrial Fibrillation in Patients With Critical Illness.

Importance: Dexmedetomidine is a widely used sedative in the intensive care unit (ICU) and has unique properties that may be associated with reduced occurrence of new-onset atrial fibrillation (NOAF). Objective: To investigate whether the use of dexmedetomidine is associated with the incidence of NOAF in patients with critical illness. Design, Setting, and Participants: This propensity score-matched cohort study was conducted using the Medical Information Mart for Intensive Care-IV database, which includes records of patients admitted to the ICU at Beth Israel Deaconess Medical Center in Boston dating 2008 through 2019. Included patients were those aged 18 years or older and hospitalized in the ICU. Data were analyzed from March through May 2022. Exposure: Patients were divided into 2 groups according to dexmedetomidine exposure: those who received dexmedetomidine within 48 hours after ICU admission (dexmedetomidine group) and those who never received dexmedetomidine (no dexmedetomidine group). Main Outcomes and Measures: The primary outcome was the occurrence of NOAF within 7 days of ICU admission, as defined by the nurse-recorded rhythm status. Secondary outcomes were ICU length of stay, hospital length of stay, and in-hospital mortality. Results: This study included 22 237 patients before matching (mean [SD] age, 65.9 [16.7] years; 12 350 male patients [55.5%]). After 1:3 propensity score matching, the cohort included 8015 patients (mean [SD] age, 61.0 [17.1] years; 5240 males [65.4%]), among whom 2106 and 5909 patients were in the dexmedetomidine and no dexmedetomidine groups, respectively. Use of dexmedetomidine was associated with a decreased risk of NOAF (371 patients [17.6%] vs 1323 patients [22.4%]; hazard ratio, 0.80; 95% CI, 0.71-0.90). Although patients in the dexmedetomidine group had longer median (IQR) length of stays in the ICU (4.0 [2.7-6.9] days vs 3.5 [2.5-5.9] days; P < .001) and hospital (10.0 [6.6-16.3] days vs 8.8 [5.9-14.0] days; P < .001), dexmedetomidine was associated with decreased risk of in-hospital mortality (132 deaths [6.3%] vs 758 deaths [12.8%]; hazard ratio, 0.43; 95% CI, 0.36-0.52). Conclusions and Relevance: This study found that dexmedetomidine was associated with decreased risk of NOAF in patients with critical illness, suggesting that it may be necessary and warranted to evaluate this association in future clinical trials.

Burnout and peritraumatic distress of healthcare workers in the COVID-19 pandemic.

BACKGROUND: To evaluate the current status of emotional exhaustion and peritraumatic distress of healthcare workers (HCWs) in the COVID-19 pandemic, and identify factors associated with their mental health status. METHODS: An online survey involving 1068 of consented HCWs that included nurses, physicians, and public health officers was conducted in May 2020. Descriptive statistics and multivariate regression analyses were performed on the collected data. RESULTS: Although no significant difference in peritraumatic distress was observed among the surveyed HCWs, the workers' experience of emotional exhaustion varied according to work characteristics. Respondents who were female, older, living with a spouse, and/or full-time workers reported higher levels of emotional exhaustion. Public health officers and other medical personnel who did not have direct contact with confirmed patients and full-time workers had a higher level of peritraumatic distress. Forced involvement in work related to COVID-19, worry about stigma, worry about becoming infected, and perceived sufficiency of organizational support negatively predict emotional exhaustion and peritraumatic distress. CONCLUSIONS: Job-related and emotional stress of HCWs should not be neglected. Evidence-based interventions and supports are required to protect HCWs from mental illness and to promote mental health of those involved in the response to the COVID-19 pandemic.

Factors Associated With the Work Intention of Hospital Workers' in South Korea During the Early Stages of the COVID-19 Outbreak.

OBJECTIVE: This study aims to explore factors associated with the work intention of hospital workers in the early stages of the coronavirus disease (COVID-19) outbreak in South Korea. METHODS: An online self-reported survey was conducted in a tertiary hospital. Respondents were asked to report their perceived threat and perceived risk of infection, evaluation of hospital response, demographics, and job-related factors. Descriptive statistics and multivariate regression analyses were performed. RESULTS: A total of 441 employees participated in this study. Of respondents, 60% were willing to accept their work during an infectious disease outbreak and 12.5% were unwilling to accept the work. In addition, 8% of respondents reported that they had considered quitting their job, 54.4% reported that their job was dangerous, and 50.1% of respondents perceived the severity of COVID-19 as high. Perceived threat and effectiveness of hospital response were associated with hospital employees' intention to work. CONCLUSIONS: Hospital workers are at the front line of the COVID-19 outbreak. This study highlighted hospital workers' perceived effectiveness of organizational response to the outbreak, and perceived threats were found to be important factors for whether they continued to work or not in the fight against the outbreak.