Demographic Analysis of Adult Patients with Disseminated Intravascular Coagulation (DIC) Admitted to Hospitals in 2021

Background:

Disseminated Intravascular Coagulation (DIC) is a complex, life-threatening syndrome characterized by the simultaneous occurrence of widespread clotting and bleeding. This condition often arises as a secondary complication to a range of underlying diseases, including sepsis, trauma, malignancies, obstetric complications, and severe infections. The pathophysiology of DIC involves a disruption in the balance between coagulation and fibrinolysis. This imbalance leads to the formation of microvascular thrombi, causing ischemia, while simultaneously depleting platelets and coagulation factors, resulting in bleeding. This study aims to provide a comprehensive overview of the demographic profiles and healthcare utilization patterns of DIC patients admitted to hospitals in 2021, using data from the Nationwide Inpatient Sample (NIS) database.

Methods:

This retrospective study included adult patients diagnosed with DIC, identified by the ICD-10 code D65. Data analysis was conducted using Stata software. The demographic variables examined included gender, age, race, Charlson Comorbidity Index (CCI), income quartile, insurance type, hospital bed size, and teaching status. The CCI was used to categorize the severity of comorbid conditions, while the income quartile provided insight into the socioeconomic status of the patients.

Results:

The study identified a total of 549 adult patients with DIC. The gender distribution was 47.27% female and 52.73% male. The mean age of the patients was 59.05 years, with a 95% confidence interval of 55.97 to 62.13 years, indicating a predominance of older adults among the DIC patient population. The racial distribution was 71.03% White, 15.89% Black, 8.41% Hispanic, and 4.67% Asian, reflecting a diverse patient demographic. The Charlson Comorbidity Index revealed that 9.09% of the patients had no comorbidities, 6.36% had a CCI score of 1, 9.09% had a CCI score of 2, and a significant 75.45% had a CCI score of 3 or higher, indicating a high burden of comorbid conditions among the patient population.

In terms of socioeconomic status, the distribution across income quartiles was as follows: 29.09% in the lowest quartile, 30% in the second quartile, 20% in the third quartile, and 20.91% in the highest quartile. This spread suggests a diverse socioeconomic background among the DIC patients. Insurance coverage varied, with 39.25% of the patients on Medicare, 23.36% on Medicaid, 30.84% with private insurance, and 6.54% self-paying for their treatment. Hospital bed sizes were categorized as 15.45% small, 23.64% medium, and 60.91% large, with large hospitals accounting for the majority of admissions. Notably, teaching hospitals represented 80% of the admissions, highlighting their significant role in managing complex cases of DIC.

Conclusion:

The analysis underscores a slightly higher prevalence of DIC among males, predominantly affecting older adults with significant racial diversity. The high prevalence of comorbid conditions, as indicated by the Charlson Comorbidity Index, suggests that these patients often have complex medical backgrounds. The diverse socioeconomic profiles and the predominance of large, teaching hospitals emphasize the need for specialized and resource-intensive care in managing DIC. These findings can inform healthcare planning and resource allocation, ensuring better management and outcomes for patients with DIC. Further studies could explore the specific factors contributing to the onset and progression of DIC in these diverse populations, as well as the impact of different treatment strategies on patient outcomes.

No relevant conflicts of interest to declare.