Skip to main content
eScholarship
Open Access Publications from the University of California

Climate Change Adaptation: Prehospital Data Facilitate the Detection of Acute Heat Illness in India

  • Author(s): Ranadive, Nikhil;
  • Desai, Jayraj;
  • LM, Sathish;
  • Knowlton, Kim;
  • Dutta, Priya;
  • Ganguly, Parthasarathi;
  • Tiwari, Abhiyant;
  • Jaiswal, Anjali;
  • Shah, Tejas;
  • Solanki, Bhavin;
  • Mavalankar, Dileep;
  • Hess, Jeremy J.
  • et al.
Abstract

Introduction: Extreme heat is a significant cause of morbidity and mortality, and the incidence of acute heat illness (AHI) will likely increase secondary to anthropogenic climate change. Prompt diagnosis and treatment of AHI are critical; however, relevant diagnostic and surveillance tools have received little attention. In this exploratory cross-sectional and diagnostic accuracy study, we evaluated three tools for use in the prehospital setting: 1) case definitions; 2) portable loggers to measure on-scene heat exposure; and 3) prevalence data for potential AHI risk factors.

Methods: We enrolled 480 patients who presented to emergency medical services with chief complaints consistent with AHI in Ahmedabad, India, from April–June 2016 in a cross-sectional study. We evaluated AHI case definition test characteristics in reference to trained prehospital provider impressions, compared on-scene heat index measured by portable loggers to weather station measurements, and identified AHI behavioral and environmental risk factors using logistic regression.

Results: The case definition for heat exhaustion was 23.8% (12.1-39.5%) sensitive and 93.6% (90.9-95.7%) specific. The positive and negative predictive values were 33.5% (20.8-49.0%) and 90.1% (88.5-91.5%), respectively. Mean scene heat index was 6.7°C higher than the mean station heat index (P < 0.001), and station data systematically underestimated heat exposure, particularly for AHI cases. Heat exhaustion cases were associated with on-scene heat index ≥ 49°C (odds ratio [OR] 2.66 [1.13–6.25], P = 0.025) and a history of recent exertion (OR 3.66 [1.30–10.29], P = 0.014), while on-scene air conditioning was protective (OR 0.29 [0.10–0.85], P = 0.024).

Conclusion: Systematic collection of prehospital data including recent activity history and presence of air conditioning can facilitate early AHI detection, timely intervention, and surveillance. Scene temperature data can be reliably collected and improve heat exposure and AHI risk assessment. Such data may be important elements of surveillance, clinical practice, and climate change adaptation.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View