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VOLUME 23 , ISSUE 6 ( June, 2019 ) > List of Articles

Original Article

Secular Trends in An Indian Intensive Care Unit-database Derived Epidemiology: The Stride Study

Manu Varma MK

Keywords : Customized Health in Intensive Care Trainable Research and Analysis tool (CHITRA), International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD 10), Admission Diagnosis, Comorbidity, Intensive Care Unit (ICU)

Citation Information : MK MV. Secular Trends in An Indian Intensive Care Unit-database Derived Epidemiology: The Stride Study. Indian J Crit Care Med 2019; 23 (6):251-257.

DOI: 10.5005/jp-journals-10071-23175

License: CC BY-NC 4.0

Published Online: 01-06-2019

Copyright Statement:  Copyright © 2019; Jaypee Brothers Medical Publishers (P) Ltd.


Abstract

Context: The Indian Society of Critical Care Medicine (ISCCM), had taken an initiative to enable all Indian ICUs (Intensive Care Unit) to capture and store relevant data in a systematic manner in an electronic database: “CHITRA” (Customized Health in Intensive Care Trainable Research and Analysis tool). Aims: This study was aimed at capturing, and summarising longitudinal epidemiological data from a single tertiary care hospital ICU (Intensive Care Unit), based on a pre-existing database and the CHITRA (Customized Health in Intensive Care Trainable Research and Analysis tool) system. Settings and design: Prospective Observational Methods and material: Data was extracted from two databases, a pre-existing database, arbitrarily named pre-CHITRA (January 2006 to April 2014), and the CHITRATM database (October 2015 to January 2018). Diagnoses of the patients admitted were tabulated using the ICD10 (International Statistical Classification of Diseases and Related Health Problems 10th Revision) coding format. The outcomes were summarised and cross tabulated. Statistical analysis used: Cross tabulations were used to display summarized data, analysis of outcomes were done using t test and regression analyses, and correspondence analysis was used to explore associations of descriptors. Results: A total of 18940 patients were admitted, with a male preponderance, and the median age was fifty-two years. Most of admissions were from emergency (62%). The age (0.3, p = 0.000, CI (0.2 - 0.38)) and mean APACHE II score of patients had increased over the years (0.18, p = 0.000 CI (0.12-0.25). The ICU mortality had decreased significantly over the years (–0.04, p = 0.000, CI (–0.05 to –0.03)). The most common admission diagnosis in the pre-CHITRA database was general symptoms and signs (ICD10 R50-R69), and in the CHITRA database was Type 1 Respiratory failure (ICD 10 J96.90). Conclusion: This study has shown the utility of the CHITRA system in capturing epidemiological data from a single centre.


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