Abstract
Objectives
To investigate the clinical nature of acute coma, which will serve as a reference for subsequent clinical decision-making
Methods and analysis
This observational study utilized Taiwan National Health Insurance Database to identify cases of acute coma from 2000 to 2017 based on ED discharge diagnoses. Clinical Classification Software (CCS) was employed to categorize the causes of acute coma. We examined the characteristics of acute coma cases, age-specific incidence rates, underlying causes, and clinical outcomes such as reversible coma, hospitalization, and 30-day mortality. Additionally, we assessed functional outcomes at a one-year follow-up. Long-term factors influencing mortality were ascertained using Cox regression.
Results
Among 99,217,322 ED visits between 2000 and 2017, 419,480 acute coma events were identified, with an event rate of 4.23 per 1,000 ED visits and an incidence rate of 0.93 per 1,000 person-years. We analyzed 205,747 first-ever acute coma cases, predominantly male (58.90%), aged 58.27 years (SD 23.04). Infection and CNS causes were predominant. CNS and drug-related causes contributed to increased 30-day mortality, while psychiatric, alcohol, women's health and perinatal care, and seizure are causes linked to reversible coma. Patients needed intensive care (26.54%), life-sustaining treatments (41.09%), or disability (6.57%). Generalized estimating equations revealed that CNS (aOR, 0.68; 95% CI, 0.62 to 0.74; p < .0001) and drug-related causes (aOR, 0.72; 95% CI, 0.65 to 0.81; p < .0001) were less likely to result in reversible coma, suggesting higher 30-day mortality risk factors. Cox regression showed drugs (aHR, 1.30, 95% CI 1.20 to 1.41, p < .001), neoplasm (aHR, 1.18, 95% CI 1.11 to 1.25, p < .001), and symptoms (aHR, 1.44, 95% CI 1.24 to 1.67, p < .001) elevated the long-term death risk.
Conclusion
Our study demonstrates the use of ICD codes aggregation to CCS in acute coma clinical study, providing insights into its clinical nature.