Heat-related illnesses in a mass gathering event and the necessity for newer diagnostic criteria: a field study

Abstract

Heat-related illnesses (HRIs), mainly heat exhaustion (HE) and heat stroke (HS), are characterized by an elevation of core body temperature. In this study, we aimed to explore the HRIs' types and patient characteristics among a sample taken from various representative in-field points in the Hajj season. A cross-sectional study was conducted in 2018 at 80 data collection points distributed in the field. Data related to demographics, features and risk factors were collected and analyzed from all encountered cases with suspected HRIs. Moreover, we developed a diagnostic tree for HRIs by using the XGBoost model. Out of the 1200 persons encountered during the study period, 231 fulfilled the criteria of HRIs spectrum and were included in this study. Around 6% had HS and 20% had HE. All HS cases (100%) were from outside of Saudi Arabia as compared with 72.5% diagnosed with HE (27.5% were from Saudi Arabia). In addition, 16% were considered as heat-induced muscle spasms, and 7% had limb heat edema. Additionally, most of HRIs cases were reported between 11 am and 1 pm. The HRIs diagnostic tree model gave a diagnostic accuracy of 93.6%. This study highlights the magnitude of HRIs among pilgrims in Hajj and provides a diagnostic tree that can aid in the risk stratification and diagnosis of these patients. We advise the implementation of more educational campaigns to pilgrims regarding preventable measures especially for the vulnerable groups (e.g. from outside Saudi Arabia, those with comorbidities and light-skinned people).

Keywords: Crowds; Field study; HRIs; Hajj; Heat exhaustion; Heat stroke; Heat-related illnesses.

Fig. 1

Heat-related illnesses (HRI) spectrum of eligible encountered cases in the field. HE: heat exhaustion; HS: heat stroke

Fig. 2

The time distribution of HRI cases during the days of Hajj. It showed the highest risk of getting HRIs in this period of time (11 AM and 1 PM)

Fig. 3

Reported symptoms among diagnosed HE and HS cases

Fig. 4

HRI feature importance as determined by the XGBoost model shows the F score of each variable from the highest to the lowest (top to bottom). GCS: Glasgow Coma Scale; DBP: diastolic blood pressure; SBP: systolic blood pressure

Fig. 5

HRI diagnostic tree based on the XGBoost model. It has a diagnostic accuracy of 93.6%