A retrospective descriptive analysis of non-physician-performed prehospital endotracheal intubation practices and performance in South Africa

Abstract

Introduction Prehospital advanced airway management, including endotracheal intubation (ETI), is one of the most commonly performed advanced life support skills. In South Africa, prehospital ETI is performed by non-physician prehospital providers. This practice has recently come under scrutiny due to lower first pass (FPS) and overall success rates, a high incidence of adverse events (AEs), and limited evidence regarding the impact of ETI on mortality. The aim of this study was to describe non-physician ETI in a South African national sample in terms of patient demographics, indications for intubation, means of intubation and success rates. A secondary aim was to determine what factors were predictive of first pass success. Methods This study was a retrospective chart review of prehospital ETIs performed by non-physician prehospital providers, between 01 January 2017 and 31 December 2017. Two national private Emergency Medical Services (EMS) and one provincial public EMS were sampled. Data were analysed descriptively and summarised. Logistic regression was performed to evaluate factors that affect the likelihood of FPS. Results A total of 926 cases were included. The majority of cases were adults (n = 781, 84.3%) and male (n = 553, 57.6%). The most common pathologies requiring emergency treatment were head injury, including traumatic brain injury (n = 328, 35.4%), followed by cardiac arrest (n = 204, 22.0%). The mean time on scene was 46 minutes (SD = 28.3). The most cited indication for intubation was decreased level of consciousness (n = 515, 55.6%), followed by cardiac arrest (n = 242, 26.9%) and ineffective ventilation (n = 96, 10.4%). Rapid sequence intubation (RSI, n = 344, 37.2%) was the most common approach. The FPS rate was 75.3%, with an overall success rate of 95.7%. Intubation failed in 33 (3.6%) patients. The need for ventilation was inversely associated with FPS (OR = 0.42, 95% CI: 0.20–0.88, p = 0.02); while deep sedation (OR = 0.56, 95% CI: 0.36–0.88, p = 0.13) and no drugs (OR = 0.47, 95% CI: 0.25–0.90, p = 0.02) compared to RSI was less likely to result in FPS. Increased scene time (OR = 0.99, 95% CI: 0.985–0.997, p < 0.01) was inversely associated FPS. Conclusion This is one of the first and largest studies evaluating prehospital ETI in Africa. In this sample of ground-based EMS non-physician ETI, we found success rates similar to those reported in the literature. More research is needed to determine AE rates and the impact of ETI on patient outcome. There is an urgent need to standardise prehospital ETI reporting in South Africa to facilitate future research.

A retrospective review of post-intubation sedation and analgesia practices in a South African private ambulance service

“…The demographic descriptors of the patients were similar to other studies done in the South African pre-hospital setting with the predominant population being young males with trauma [ 17 , [20] , [21] , [22] ]. Interestingly, males were more likely to receive PISA than females.…”

Prehospital Emergency Care in Low- and Middle-Income Countries: A Systematic Review

“…86,[96][97][98] Advanced transport systems like HEMS and Urgent Medical Aid Service (SAMU) have reduced transportation time and played a crucial role in reducing mortality. 80,99,100 A study conducted by Sobuwa, et al 101 showed that prehospital intubations performed among traumatic brain injury patients did not demonstrate improved outcomes, however, another study conducted in South Africa reported a 98% success rate of prehospital endotracheal intubation 102 (Table 4 80,81,86,[94][95][96][97][98][99][100][101][102][103][104][105][106][107][108] ).…”

The Behavioral and Social Dimension of the Public Health System of European Countries: Descriptive, Canonical, and Factor Analysis

“…Thus, modern healthcare scientists suggest studying various issues using the descriptive analysis method. For example, Riediger N. D. et al [58] used descriptive analysis of food pantries in twelve American states; Taljaard L. et al [59] conducted a descriptive analysis of the case mix in East London, South Africa; Bayou N. B. et al [60] used a descriptive structural analysis of quality of labor and delivery care in Ethiopia; and Wylie C. A. et al [61] described a retrospective descriptive analysis. Descriptive analysis is also very often used in social sciences (18.56%).…”

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