Literature DB >> 28660169

Distribution of shock index and age shock index score among trauma patients in India.

Prashant Bhandarkar1, Ashok Munivenkatappa2, Nobhojit Roy3, Vineet Kumar4, Veda Dhruthy Samudrala5, Amit Agrawal5.   

Abstract

Entities:  

Year:  2017        PMID: 28660169      PMCID: PMC5479077          DOI: 10.4103/IJCIIS.IJCIIS_19_17

Source DB:  PubMed          Journal:  Int J Crit Illn Inj Sci        ISSN: 2229-5151


× No keyword cloud information.
Dear Editor, Trauma is one of the leading causes of mortality worldwide. To avert trauma-related mortality, early recognition of relatively severe patients becomes crucially important. In limited resource settings, to identify such cases, simple indexes are useful to allocate required attention. Patient vitals such as pulse, heart rate (HR), and blood pressure (BP) are important for decision-making. Further, shock index (SI) is also such, bedside assessment calculated as a ratio of HR to systolic BP (SBP).[12] SI is reported to carry significant prognostic value for trauma and other emergency cases admitted to emergency department.[3] It is a simple and effective means of gauging the degree of hypovolemia in hemorrhagic and infectious shock states introduced in 1967 by Allgöwer and Burri. Among vitals of bedside assessment of patients are pulse, HR, and BP.[4] To elaborate the concept of SI and age × SI (ASI) in developing countries' scenario, we aimed to evaluate prognostic values of SI and ASI. The validation of SI with overall mortality among trauma victims was accessed. We used data from the Towards Improved Trauma Care Outcomes (TITCO) project from India. TITCO was a prospective, observational, multicenter trauma registry containing data of trauma patients admitted to four public university hospitals in Mumbai, Delhi, and Kolkata.[5] TITCO data were collected from October 1, 2013 to September 30, 2015. Patient details of trauma cases were recorded by trained data collectors at each identified center of TITCO. All the patients from TITCO registry with valid records of HR and SBP were considered for this study. Overall mortality recorded among the study participants was considered an important variable to assess the relationship with SI status. Age and gender were considered as secondary variables and effect of relative SI values and mortality was calculated and studied among them. Age was grouped as pediatric with age <18 years, adults with age between 18 and 60 years, and geriatric with age >60 years. Data were analyzed using SPSS version 20.0 (SPSS Inc., Chicago, IL, USA) for Windows and Microsoft Excel version 2013. To test the efficacy of SI, receiver operating characteristic curve was drawn; the overall hospital mortality was considered as a state variable. Corresponding area under the curve (AUC) was then calculated and considered for inferences. Primary and secondary variables under consideration were analyzed to estimate statistical parameters including mean, standard deviation, and percentages [Table 1 and Figure 1].
Table 1

Area under the curve calculated from receiver operating curve for overall hospital mortality prediction by shock index

Figure 1

Area under the curve calculated from receiver operating curve for overall hospital mortality prediction by shock index

Area under the curve calculated from receiver operating curve for overall hospital mortality prediction by shock index Area under the curve calculated from receiver operating curve for overall hospital mortality prediction by shock index Among 16,047 participants of TITCO registry, 12,474 patients with valid records of SBP and HR were studied to obtain SI and ASI. Overall mortality among the study participants was 21.69%, and gender-wise significant difference was observed (male: 21.1%, female: 23.9%, P < 0.002). Increase in age was also associated with respective increase in overall mortality (P < 0.00). AUC values calculated for age and gender as a factor of overall mortality and SI were found in the range of 0.546–0.659. Eliminating the effect of age group, AUC values for male and female were 0.589 and 0.584, respectively, and for overall patients, they were found to be 0.589, which shows the poor diagnostic ability of survival risk assessment with SI. Among pediatric male and adults of both sexes, corresponding AUC (>0.60) showed its ability to fairly diagnose the risk of mortality. Similarly, ASI values were also found in the similar range of 0.552–0.621. However, after eliminating the effect of age group, AUC values for male and female were 0.649 and 0.634, respectively, while for overall patients, they were found to be 0.645. This shows slightly better diagnostic values of ASI than actual SI.[6] Unlikely, no such significant differences were observed in the present study. SI has failed to show prognostic information among trauma victims in India, and variation among predictive values may not be beneficial. However, adjusting SI by ASI has shown slightly better prognostic level for overall mortality.

Financial support and sponsorship

This study was funded by grants from the Swedish National Board of Health and Welfare and the Laerdal Foundation for Acute Care Medicine.

Conflicts of interest

There are no conflicts of interest.
  5 in total

1.  30-Day In-hospital Trauma Mortality in Four Urban University Hospitals Using an Indian Trauma Registry.

Authors:  Nobhojit Roy; Martin Gerdin; Samarendra Ghosh; Amit Gupta; Vineet Kumar; Monty Khajanchi; Eric B Schneider; Russell Gruen; Göran Tomson; Johan von Schreeb
Journal:  World J Surg       Date:  2016-06       Impact factor: 3.352

2.  Age- and sex-specific normal values for shock index in National Health and Nutrition Examination Survey 1999-2008 for ages 8 years and older.

Authors:  Lara D Rappaport; Sara Deakyne; Joseph A Carcillo; Kim McFann; Marion R Sills
Journal:  Am J Emerg Med       Date:  2013-03-07       Impact factor: 2.469

Review 3.  Utility of the shock index in patients with sepsis.

Authors:  Jim Tseng; Kenneth Nugent
Journal:  Am J Med Sci       Date:  2015-06       Impact factor: 2.378

4.  ["Shock index"].

Authors:  M Allgöwer; C Burri
Journal:  Dtsch Med Wochenschr       Date:  1967-10-27       Impact factor: 0.628

5.  The Shock Index revisited - a fast guide to transfusion requirement? A retrospective analysis on 21,853 patients derived from the TraumaRegister DGU.

Authors:  Manuel Mutschler; Ulrike Nienaber; Matthias Münzberg; Christoph Wölfl; Herbert Schoechl; Thomas Paffrath; Bertil Bouillon; Marc Maegele
Journal:  Crit Care       Date:  2013-08-12       Impact factor: 9.097

  5 in total
  2 in total

1.  Pattern and Distribution of Shock Index and Age Shock Index Score Among Trauma Patients in Towards Improved Trauma Care Outcomes (TITCO) Dataset.

Authors:  Prashant Bhandarkar; Ashok Munivenkatappa; Nobhojit Roy; Vineet Kumar; Luis Rafael Moscote-Salazar; Amit Agrawal
Journal:  Bull Emerg Trauma       Date:  2018-10

2.  An Analysis of 30-Day in-Hospital Trauma Mortality in Four Urban University Hospitals Using the Australia India Trauma Registry.

Authors:  Prashant Bhandarkar; Priti Patil; Kapil Dev Soni; Gerard M O'Reilly; Satish Dharap; Joseph Mathew; Naveen Sharma; Bhakti Sarang; Anita Gadgil; Nobhojit Roy
Journal:  World J Surg       Date:  2020-10-21       Impact factor: 3.352

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.