Vineet Karwa
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Vineet Karwa has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Maimoona Khan
Department of General Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, India
1 shared publication - Nishant Rathod
Department of General Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, India
1 shared publication - Rajvardhan Patil
Department of General Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, India
1 shared publication - Roma Chavhan
Department of General Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, India
1 shared publication - Sourya Acharya
Department of General Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, India
1 shared publication - Sunil Kumar
Department of Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND
1 shared publication
Latest Publications
- Open Access
- 1 January 2026
- Published by Hamad bin Khalifa University Press (HBKU Press) in Journal of Emergency Medicine, Trauma and Acute Care
- Vol. 2026 (4)
Charlson comorbidity index in predicting outcomes among patients in the medical intensive care unit at a tertiary care university hospital: A cross-sectional study
Background: In critical care, comorbidities significantly influence outcomes, but they are often underutilized in real-time decision-making. The Charlson Comorbidity Index (CCI), a widely validated tool for quantifying comorbid burden, offers a practical way to assess prognosis in intensive care unit (ICU) patients. This study was planned to explore the predictive utility of CCI alone in determining patient outcomes in a rural Indian ICU setting. Methodology: This prospective, cross-sectional study was conducted from April 2023 to March 2025 at a tertiary care center in central India. A total of 700 adult patients admitted to the medical ICU were included, excluding those with 3 were significantly older (mean age: 58.9 years) compared to those with CCI p < 0.001). The receiver operating characteristic (ROC) analysis revealed a fair predictive capacity of CCI for in-hospital mortality, with an area under the curve (AUC) of 0.635. At an optimal cutoff of 3.5, the CCI demonstrated good sensitivity (80.9%) but limited specificity (29.6%). Conclusion: The CCI is a valuable, easy-to-use tool for assessing the prognostic outlook of ICU patients, especially in low-resource settings. Although its standalone predictive power for mortality is moderate, its high sensitivity makes it a useful screening tool to identify high-risk patients early during ICU admission. The findings underscore the need to incorporate structured comorbidity assessment into critical care workflows, particularly where advanced physiological scoring systems may not be readily available.
- 1 January 2026
- Published by Hamad bin Khalifa University Press (HBKU Press) in Journal of Emergency Medicine, Trauma and Acute Care
- Vol. 2026 (4)
Open AccessCharlson comorbidity index in predicting outcomes among patients in the medical intensive care unit at a tertiary care university hospital: A cross-sectional study
Background: In critical care, comorbidities significantly influence outcomes, but they are often underutilized in real-time decision-making. The Charlson Comorbidity Index (CCI), a widely validated tool for quantifying comorbid burden, offers a practical way to assess prognosis in intensive care unit (ICU) patients. This study was planned to explore the predictive utility of CCI alone in determining patient outcomes in a rural Indian ICU setting. Methodology: This prospective, cross-sectional study was conducted from April 2023 to March 2025 at a tertiary care center in central India. A total of 700 adult patients admitted to the medical ICU were included, excluding those with 3 were significantly older (mean age: 58.9 years) compared to those with CCI p < 0.001). The receiver operating characteristic (ROC) analysis revealed a fair predictive capacity of CCI for in-hospital mortality, with an area under the curve (AUC) of 0.635. At an optimal cutoff of 3.5, the CCI demonstrated good sensitivity (80.9%) but limited specificity (29.6%). Conclusion: The CCI is a valuable, easy-to-use tool for assessing the prognostic outlook of ICU patients, especially in low-resource settings. Although its standalone predictive power for mortality is moderate, its high sensitivity makes it a useful screening tool to identify high-risk patients early during ICU admission. The findings underscore the need to incorporate structured comorbidity assessment into critical care workflows, particularly where advanced physiological scoring systems may not be readily available.