Factors associated with the worsening of COVID-19 symptoms among cohorts in community- or home-isolation care in southern Thailand

Introduction

This study aimed to investigate factors associated with time-to-referral due to worsening symptoms in patients with laboratory-confirmed COVID-19 in southern Thailand. While underlying diseases have been evaluated to assess COVID-19 severity, the influence of vaccinations and treatments is also crucial.

Methods

A cohort of 8,638 patients quarantined in home or community isolation with laboratory-confirmed COVID-19 was analyzed. Survival analysis and the Cox proportional hazard ratio were employed to assess factors influencing time-toreferral.

Results

Age ≥ 60 years, neurologic disorders, cardiovascular disease, and human immunodeficiency virus infection were identified as significant risk factors for severe COVID-19 referral. Patients who received full- or booster-dose vaccinations had a lower risk of experiencing severe symptoms compared to unvaccinated patients. Notably, individuals vaccinated during the Omicron-dominant period had a substantially lower time-to-referral than those unvaccinated during the Delta-dominant period. Moreover, patients vaccinated between 1 and 6 months prior to infection had a significantly lower risk of time-to-referral than the reference group.

Discussion

These findings demonstrate early intervention in high-risk COVID-19 patients and the importance of vaccination efficacy to reduce symptom severity. The study provides valuable insights for guiding future epidemic management strategies and optimising patient care during infectious disease outbreaks.

Predicting hospital mortality in cardiac care unit patients: external validation of the M-CARS

Background

Resource availability for cardiac patients particularly specialized intensive care unit is often limited in Asian developing countries. Risk score specifically developed for cardiac patients admitted to cardiac care unit (CCU) are scarce or not widely validated. The Mayo Cardiac Intensive Care Unit Admission Risk score (M-CARS) has shown excellent performance in predicting in-hospital mortality in US population. However, the M-CARS has not yet been validated in the Asian population where characteristics of cardiac patients may be substantially different. In addition, the value of the M-CARS in predicting intermediate-term mortality is unknown.

Purpose

We sought to validate the M-CARS for in-hospital and 1-year all-cause mortality in consecutive patients admitted to the cardiac care unit.

Methods

Consecutive patients admitted to the CCU of a tertiary care center between July 2015 and December 2019 were included into the present study. Patients who were transferred from the other in-hospital wards were excluded from the study. Missing data were handled with multiple imputation using multivariable imputation by chained equations. Seven variables including cardiac arrest, cardiogenic shock, respiratory failure, Braden skin score, BUN, anion gap and RDW were used to calculate the M-CARS in the imputed data. Patients were stratified into 3 groups according to the M-CARS (<2, 2–6, >6). In-hospital mortality was compared among groups with different M-CARS. Kaplan-Meier curves were used to demonstrate 1-year all-cause mortality among groups. Discrimination was assessed with C-statistic.

Results

Of 1709 patients included in the present study, 72% was male with mean age of 64.3 years. Prevalence of diabetes, chronic kidney disease, cardiogenic shock and respiratory failure prior to or within 1 hour of CCU admission were 22.4%, 13.6%, 8.1% and 1.8% respectively. Majority of patients (68.2%) had ACS as principal diagnosis.

Ninety-three patients died during the index hospital admission (mortality rate of 5.44%). The in-hospital mortality rate in patients with M-CARS of <2, 2–6 and ≥6 was 1%, 8.7% and 21.4% respectively. The Kaplan-Meier estimate of 1-year mortality in the group with M-CARS ≥6 was 54.8% while it was 6.3% in those with M-CARS <2. C-statistic of M-CARS for in-hospital mortality was 0.865 (95% CI 0.825–0.899) whereas it was slightly lower for 1-year all-cause mortality (c-statistic 0.840, 95% CI 0.801–0.874). Calibration for in-hospital mortality was satisfactory in the group with M-CARS ≤6 whereas actual mortality was underestimated in M-CARS >6.

Conclusions

The M-CARS had excellent and clearly useful discrimination with satisfactory calibration in our external validation study. M-CARS identified high-risk patients in CCU (M-CARS ≥6) who had very high risk for mortality. M-CARS may be helpful for physicians in risk stratifying and allocating health-care resource for cardiac patients.

Funding Acknowledgement

Type of funding sources: None.

Predicting mortality in cardiac care unit patients: external validation of the Mayo cardiac intensive care unit admission risk score

AIMS

The Mayo Cardiac Intensive Care Unit Admission Risk Score (M-CARS) had excellent performance in predicting in-hospital mortality in the US population. We sought to validate the M-CARS for in-hospital and post-discharge mortality in Asian patients admitted to the cardiac care unit (CCU).

METHODS AND RESULTS

Patients admitted to the CCU of a tertiary care centre between July 2015 and December 2019 were included into the study. Patients with intra-hospital transfer to the CCU due to intensive care unit overflow, postoperative cardiac surgery, or for monitoring after elective procedures were excluded. Cardiac arrest, cardiogenic shock, respiratory failure, Braden skin score, blood urea nitrogen, anion gap, and red cell distribution width, were used to calculate the M-CARS. Patients were stratified into three groups, according to the M-CARS (<2, 2-6, >6). Of 1988 patients in the study, 30.1% were female with a median age of 65 years. Prevalence of cardiogenic shock and respiratory failure at admission were 2.8% and 4.5%, respectively. One hundred and seventeen patients died during the admission (mortality rate of 5.9%). The in-hospital mortality rate in patients with M-CARS of <2, 2-6, and >6 was 1.1%, 9.8%, and 35.5%, respectively. C-statistic of M-CARS for in-hospital mortality was 0.840 (95% CI 0.805-0.873); whereas, it was 0.727 (95% CI 0.690-0.761) for 1-year post-discharge mortality. Calibration plot showed good agreement between predicted and observed in-hospital mortality in the majority of patients.

CONCLUSIONS

The M-CARS was useful in our study, in terms of discrimination and calibration. M-CARS identified high-risk patients in CCU, who had unacceptably high mortality rate during hospital stay and thereafter.