Objectives: Modified shock index (MSI) is a simple bedside tool used in the emergency department. There are a few studies suggesting MSI as a good prognostic indicator than shock index in sepsis patients. However, there is not enough research emphasizing the role of MSI in patients with comorbidities. Hence, this study aims to assess the predictive validity of MSI in predicting the prognosis of sepsis patients with and without co-morbidities. Methods: From January to December 2020, a prospective observational study was conducted in a tertiary care teaching hospital. Patients with sepsis diagnosed based on systemic inflammatory response syndrome criteria and quick sequential organ failure assessment (qSOFA) were included. The need for mechanical ventilation and step down from the intensive care unit were outcome variables, MSI was considered as a predictor variable, and co-morbidities as an explanatory variable. Results: Among people with co-morbidities, the MSI value on arrival to the emergency department had fair predictive validity in predicting the need for mechanical ventilation after 24 hours, as indicated by the area under the curve of 0.749 (95% CI: 0.600-0.897; p-value = 0.002) and a sensitivity of 68.75% in predicting mechanical ventilation after 24 hours (MSI ≥ 1.59). Among people without co-morbidities, the MSI value on arrival to the emergency department had fair predictive validity in predicting the need for mechanical ventilation after 24 hours, as indicated by the area under the curve of 0.879 (95% CI: 0.770-0.988; p-value <0.001) and a sensitivity of 83.33% in predicting the need for mechanical ventilation after 24 hours (MSI ≥ 1.67). Conclusion: MSI can be used as an indicator in predicting the prognosis of sepsis patients in the emergency department. A simple bedside calculation of the MSI can indicate the need for mechanical ventilation and step down from the intensive care unit after 24 hours in patients with co-morbidities and without co-morbidities.
Objectives: This study aimed to evaluate the trauma and injury severity score (TRISS), IMPACT (international mission for prognosis and analysis of clinical trials), and CRASH (corticosteroid randomization after significant head injury) prognostic models for prediction of outcome after moderate-to-severe traumatic brain injury (TBI) in the elderly following road traffic accident. Design: This was a prospective observational study. Materials and Methods: This was a prospective observational study on 104 elderly trauma patients who were admitted to tertiary care hospital, over a consecutive period of 18 months from December 2016 to May 2018. On the day of admission, data were collected from each patient to compute the TRISS, IMPACT, and CRASH and outcome evaluation was prospectively done at discharge, 14 th day, and 6-month follow-up. Results: This study included 104 TBI patients with a mean age of 66.75 years and with a mortality rate of 32% and 45%, respectively, at discharge and at the end of 6 months. The predictive accuracies of the TRISS, CRASH (computed tomography), and IMPACT (core, extended, laboratory) were calculated using receiver operator characteristic (ROC) curves for the prediction of mortality. Best cutoff point for predicting mortality in elderly TBI patients using TRISS system was a score of ≤88 (sensitivity 94%, specificity of 80%, and area under ROC curve 0.95), similarly cutoff point under the CRASH at 14 days was score of >35 (100%, 80%, 0.958); for CRASH at 6 months, best cutoff point was at >84 (88%, 88%, 0.959); for IMPACT (core), it was >38 (88%, 93%, 0.976); for IMPACT (extended), it was >27 (91%, 89%, 0.968); and for IMPACT (lab), it was >41 (82%, 100%, 0.954). There were statistical differences among TRISS, CRASH (at 14 days and 6 months), and IMPACT (core, extended, lab) in terms of area under the ROC curve ( P < 0.0001). Conclusion: IMPACT (core, extended) models were the strongest predictors of mortality in moderate-to-severe TBI when compared with the TRISS, CRASH, and IMPACT (lab) models.
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