Telephonic description of sepsis among callers to an emergency dispatch centre in South Africa

Introduction: Sepsis is an acute, life-threatening condition caused by a dysregulated systemic response to infection. Early medical intervention such as antibiotics and fluid resuscitation can be life-saving. Diagnosis or suspicion of sepsis by an emergency call-taker could potentially improve patient outcome. Therefore, the aim was to determine the keywords used by callers to describe septic patients in South Africa when calling a national private emergency dispatch centre. Methods: A retrospective review of prehospital patient records was completed to identify patients with sepsis in the prehospital environment. A mixed-methods design was employed in two-sequential phases. The first phase was qualitative. Thirty cases of sepsis were randomly selected, and the original call recording was extracted. These recordings were transcribed verbatim and subjected to content analysis to determine keywords of signs and symptoms telephonically. Once keywords were identified, an additional sample of sepsis cases that met inclusion and exclusion criteria were extracted and listened to. The frequency of each of the keywords was quantified. Results: Eleven distinct categories were identified. The most prevalent categories that were used to describe sepsis telephonically were: gastrointestinal symptoms (40%), acute altered mental status (35%), weakness of the legs (33%) and malaise (31%). At least one of these four categories of keywords appeared in 86% of all call recordings. Conclusion: It was found that certain categories appeared in higher frequencies than others so that a pattern could be recognised. Utilising these categories, telephonic recognition algorithms for sepsis could be developed to aid in predicting sepsis over the phone. This would allow for dispatching of the correct level of care immediately and could subsequently have positive effects on patient outcome

A prehospital randomised controlled trial in South Africa: Challenges and lessons learnt

The incidence of cardiovascular disease and STEMI is on the rise in sub-Saharan Africa. Timely treatment is essential to reduce mortality. Internationally, prehospital 12 lead ECG telemetry has been proposed to reduce time to reperfusion. Its value in South Africa has not been established. The aim of this study was to determine the effect of prehospital 12 lead ECG telemetry on the PCI-times of STEMI patients in South Africa. A multicentre randomised controlled trial was attempted among adult patients with prehospital 12 lead ECG evidence of STEMI. Due to poor enrolment and small sample sizes, meaningful analyses could not be made. The challenges and lessons learnt from this attempt at Africa's first prehospital RCT are discussed. Challenges associated with conducting this RCT related to the healthcare landscape, resources, training of paramedics, rollout and randomisation, technology, consent and research culture. High quality evidence to guide prehospital emergency care practice is lacking both in Africa and the rest of the world. This is likely due to the difficulties with performing prehospital clinical trials. Every trial will be unique to the test intervention and setting of each study, but by considering some of the challenges and lessons learnt in the attempt at this trial, future studies might experience less difficulty. This may lead to a stronger evidence-base for prehospital emergency care

Evaluating trauma scoring systems for patients presenting with gunshot injuries to a district-level urban public hospital in Cape Town, South Africa

Introduction : Trauma scoring systems are widely used in emergency settings to guide clinical decisions and to predict mortality. It remains unclear which system is most suitable to use for patients with gunshot injuries at district-level hospitals. This study compares the Triage Early Warning Score (TEWS), Injury Severity Score (ISS), Trauma and Injury Severity Score (TRISS), Kampala Trauma Score (KTS) and Revised Trauma Score (RTS) as predictors of mortality among patients with gunshot injuries at a district-level urban public hospital in Cape Town, South Africa. Methods : Gunshot-related patients admitted to the resuscitation area of Khayelitsha Hospital between 1 January 2016 and 31 December 2017 were retrospectively analysed. Receiver Operating Characteristic (ROC) analysis were used to determine the accuracy of each score to predict all-cause in-hospital mortality. The odds ratio (with 95% confidence intervals) was used as a measure of association.Results : In total, 331 patients were included in analysing the different scores (abstracted from database n = 431, excluded: missing files n = 16, non gunshot injury n = 10, <14 years n = 1, information incomplete to calculate scores n = 73). The mortality rate was 6% (n = 20). The TRISS and KTS had the highest area under the ROC curve (AUC), 0.90 (95% CI 0.83-0.96) and 0.86 (95% CI 0.79­0.94), respectively. The KTS had the highest sensitivity (90%, 95% CI 68-99%), while the TEWS and RTS had the highest specificity (91%, 95% CI 87­94% each). Conclusions : None of the different scoring systems performed better in predicting mortality in this high-trauma burden area. The results are limited by the low number of recorded deaths and further studies are needed

The association between hospital arrival time, transport method, prehospital time intervals, and in-hospital mortality in trauma patients presenting to Khayelitsha Hospital, Cape Town

Introduction:Trauma is a leading cause of unnatural death and disability in South Africa. The aim of the study was to determine whether method of transport, hospital arrival time or prehospital transport time intervals were associated with in-hospital mortality among trauma patients presenting to Khayelitsha Hospital, a district-level hospital on the outskirts of Cape Town, South Africa.Methods:The Khayelitsha Hospital Emergency Centre database was retrospectively analysed for trauma-related patients presenting to the resuscitation area between 1 November 2014 and 30 April 2015. Missing data and additional variables were collected by means of a chart review. Eligible patients' folders were scrutinised for hospital arrival time, transport time intervals, transport method and in-hospital mortality. Descriptive statistics were presented for all variables. Categorical data were analysed using the Fisher's Exact test and Chi-square, continuous data by logistic regression and the Mann Whitney test. A confidence interval of 95% was used to describe variance and a p-value of <0.05 was deemed significant.Results:The majority of patients were 19­44 year old males (n = 427, 80.3%) and penetrating trauma the most frequent mechanism of injury (n = 343, 64.5%). In total, 258 (48.5%) patients arrived with their own transport, 254 (47.7%) by ambulance and 20 (3.8%) by the police service. The arrival of trauma patients peaked during the weekend, and was especially noticeable between midnight and six a.m. In-hospital mortality (n = 18, 3.4%) was not significantly affected by transport method (p = 0.26), hospital arrival time (p = 0.22) or prehospital transport time intervals (all p-values >0.09).Discussion:Method of transport, hospital arrival time and prehospital transport time intervals did not have a substantially measurable effect on in-hospital mortality. More studies with larger samples are suggested due to the small event rate.African relevance

The association between hospital arrival time, transport method, prehospital time intervals, and in-hospital mortality in trauma patients presenting to Khayelitsha Hospital, Cape Town

Introduction:Trauma is a leading cause of unnatural death and disability in South Africa. The aim of the study was to determine whether method of transport, hospital arrival time or prehospital transport time intervals were associated with in-hospital mortality among trauma patients presenting to Khayelitsha Hospital, a district-level hospital on the outskirts of Cape Town, South Africa.Methods:The Khayelitsha Hospital Emergency Centre database was retrospectively analysed for trauma-related patients presenting to the resuscitation area between 1 November 2014 and 30 April 2015. Missing data and additional variables were collected by means of a chart review. Eligible patients' folders were scrutinised for hospital arrival time, transport time intervals, transport method and in-hospital mortality. Descriptive statistics were presented for all variables. Categorical data were analysed using the Fisher's Exact test and Chi-square, continuous data by logistic regression and the Mann Whitney test. A confidence interval of 95% was used to describe variance and a p-value of <0.05 was deemed significant.Results:The majority of patients were 19­44 year old males (n = 427, 80.3%) and penetrating trauma the most frequent mechanism of injury (n = 343, 64.5%). In total, 258 (48.5%) patients arrived with their own transport, 254 (47.7%) by ambulance and 20 (3.8%) by the police service. The arrival of trauma patients peaked during the weekend, and was especially noticeable between midnight and six a.m. In-hospital mortality (n = 18, 3.4%) was not significantly affected by transport method (p = 0.26), hospital arrival time (p = 0.22) or prehospital transport time intervals (all p-values >0.09). Discussion:Method of transport, hospital arrival time and prehospital transport time intervals did not have a substantially measurable effect on in-hospital mortality. More studies with larger samples are suggested due to the small event rate