Mortality outcomes based on ED qSOFA score and HIV status in a developing low income country

Combining C-reactive protein and quick sequential organ failure assessment (qSOFA) to improve prognostic accuracy for sepsis and mortality in adult inpatients: A systematic review

Background and Aims

Infections are common in hospitals, and if mismanaged can develop into sepsis, a leading cause of death and disability worldwide. This study aimed to examine whether combining C-reactive protein (CRP) with the quick sequential organ failure assessment (qSOFA) improves its accuracy for predicting mortality and sepsis in adult inpatients.

Methods

PubMed, MEDLINE, EMBASE, Scopus, Web of Science, Science Direct, CINAHL, Open Grey, Grey Literature Report, and the Clinical Trials registry were searched using CRP and qSOFA search terms. Title, abstract, and full-text screening were performed by two independent reviewers using pre-determined eligibility criteria, followed by data extraction and a risk of bias assessment using the Quality Assessment tool for Diagnostic Accuracy Studies 2 (QUADAS-2). Disagreements were settled through discussion and consultation with a third reviewer.

Results

Four retrospective studies with a total of 2070 patients were included in this review. Adding CRP to qSOFA improved the Area Under the Receiver Operating Characteristic Curve up to 9.7% for predicting mortality and by 14.9% for identifying sepsis. The sensitivity and specificity of the combined score for mortality prediction were available in two studies. CRP improved the sensitivity of qSOFA by 43% and 71% while only decreasing the specificity by 12% and 7%, respectively. A meta-analysis was not performed due to study heterogeneity.

Conclusion

This comprehensive review provided initial evidence that combining CRP with qSOFA may improve the accuracy of qSOFA alone in identifying sepsis or patients at risk of dying in hospital. The combined tool demonstrated the potential to improve patient outcomes, with implications for low-resource settings given its simplicity and low-cost.

Performance of the Universal Vital Assessment (UVA) mortality risk score in hospitalized adults with infection in Rwanda: A retrospective external validation study

Background

We previously derived a Universal Vital Assessment (UVA) score to better risk-stratify hospitalized patients in sub-Saharan Africa, including those with infection. Here, we aimed to externally validate the performance of the UVA score using previously collected data from patients hospitalized with acute infection in Rwanda.

Methods

We performed a secondary analysis of data collected from adults ≥18 years with acute infection admitted to Gitwe District Hospital in Rwanda from 2016 until 2017. We calculated the UVA score from the time of admission and at 72 hours after admission. We also calculated quick sepsis-related organ failure assessment (qSOFA) and modified early warning scores (MEWS). We calculated amalgamated qSOFA scores by inserting UVA cut-offs into the qSOFA score, and modified UVA scores by removing the HIV criterion. The performance of each score determined by the area under the receiver operator characteristic curve (AUC) was the primary outcome measure.

Results

We included 573 hospitalized adult patients with acute infection of whom 40 (7%) died in-hospital. The admission AUCs (95% confidence interval [CI]) for the prediction of mortality by the scores were: UVA, 0.77 (0.68–0.85); modified UVA, 0.77 (0.68–0.85); qSOFA, 0.66 (0.56–0.75), amalgamated qSOFA, 0.71 (0.61–0.80); and MEWS, 0.74 (0.64, 0.83). The positive predictive values (95% CI) of the scores at commonly used cut-offs were: UVA >4, 0.35 (0.15–0.59); modified UVA >4, 0.35 (0.15–0.59); qSOFA >1, 0.14 (0.07–0.24); amalgamated qSOFA >1, 0.44 (0.20–0.70); and MEWS >5, 0.14 (0.08–0.22). The 72 hour (N = 236) AUC (95% CI) for the prediction of mortality by UVA was 0.59 (0.43–0.74). The Chi-Square test for linear trend did not identify an association between mortality and delta UVA score at 72 hours (p = 0.82).

Conclusions

The admission UVA score and amalgamated qSOFA score had good predictive ability for mortality in adult patients admitted to hospital with acute infection in Rwanda. The UVA score could be used to assist with triage decisions and clinical interventions, for baseline risk stratification in clinical studies, and in a clinical definition of sepsis in Africa.

Prognostic value of the Quick Sepsis-related Organ Failure Assessment (qSOFA) score among critically ill medical and surgical patients with suspected infection in a resource-limited setting

Background

The Quick Sequential Organ Failure Assessment (qSOFA) score is a simple bedside tool validated outside of the intensive care unit (ICU) to identify patients with suspected infection who are at risk for poor outcomes.

Objectives

To assess qSOFA at the time of ICU referral as a mortality prognosticator in adult medical v. surgical patients with suspected infection admitted to an ICU in a resource-limited regional hospital in South Africa (SA).

Methods

We conducted a retrospective cohort study on adult medical or surgical patients that were admitted to an ICU in a resource-limited hospital in SA. We performed univariate and multivariable logistic regression and compared nested models using likelihood ratio test, and we calculated the area under the receiver operating characteristic curve (AUROC).

Results

We recruited a total of 1 162 (medical n=283 and surgical n=875) participants in the study who were admitted to the ICU with suspected infection. qSOFA at the time of ICU referral was highly associated with but poorly discriminant of in-ICU mortality among medical (odds ratio (OR) 2.60, 95% confidence interval (CI) 1.19 - 5.71; p=0.02; AUROC 0.60; 95% CI 0.53 - 0.67; p=0.02) and surgical (OR 2.74; 95% CI 1.73-4.36; p<0.001; AUROC 0.60; 95% CI 0.55 - 0.65; p=0.04) patients. qSOFA model performance was similar between medical and surgical subgroups (p≥0.26). Addition of qSOFA to a baseline risk factor model including age, sex, and HIV status improved the model discrimination in both subgroups (medical AUROC 0.64; 95% CI 0.56 - 0.71; p=0.049; surgical AUROC 0.69; 95% CI 0.64 - 0.74; p<0.0001).

Conclusion

qSOFA was highly associated with, but poorly discriminant for, poor outcomes among medical and surgical patients with suspected infection admitted to the ICU in a resource-limited setting. These findings suggest that qSOFA may be useful as a tool to identify patients at increased risk of mortality in these populations and in this context.

The timing of use of risk stratification tools affects their ability to predict mortality from sepsis. A meta-regression analysis

Background: Risk stratification tools (RSTs) are used in healthcare settings to identify patients at risk of sepsis and subsequent adverse outcomes. In practice RSTs are used on admission and thereafter as ‘trigger’ tools prompting sepsis management. However, studies investigating their performance report scores at a single timepoint which varies in relation to admission. The aim of this meta-analysis was to determine if the predictive performance of RSTs is altered by the timing of their use. Methods: We conducted a systematic review and meta-regression analysis of studies published from inception to 31 October 2018, using EMBASE and PubMed databases. Any cohort studies investigating the ability of an RST to predict mortality in adult sepsis patients admitted to hospital, from which a 2x2 table was available or could be constructed, were included. The diagnostic performance of RSTs in predicting mortality was the primary outcome. Sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver-operating curve (AUROC) were the primary measures, enabling further meta-regression analysis. Results: 47 studies were included, comprising 430,427 patients. Results of bivariate meta-regression analysis found tools using a first-recorded score were less sensitive than those using worst-recorded score (REML regression coefficient 0.57, 95% CI 0.07-1.08). Using worst-recorded score led to a large increase in sensitivity (summary sensitivity 0.76, 95% CI 0.67-0.83, for worst-recorded scores vs. 0.64 (0.57-0.71) for first-recorded scores). Scoring system type did not have a significant relationship with studies’ predictive ability. The most analysed RSTs were qSOFA (n=37) and EWS (n=14). Further analysis of these RSTs also found timing of their use to be associated with predictive performance. Conclusion: The timing of any RST is paramount to their predictive performance. This must be reflected in their use in practice, and lead to prospective studies in future.

A comparison of different scores for diagnosis and mortality prediction of adults with sepsis in Low-and-Middlencome Countries: a systematic review and meta-analysis

BACKGROUND

Clinical scores for sepsis have been primarily developed for, and applied in High-Income Countries. This systematic review and meta-analysis examined the performance of the quick Sequential Organ Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome (SIRS), Modified Early Warning Score (MEWS), and Universal Vital Assessment (UVA) scores for diagnosis and prediction of mortality in patients with suspected infection in Low-and-Middle-Income Countries.

METHODS

PubMed, Science Direct, Web of Science, and the Cochrane Central Register of Controlled Trials databases were searched until May 18, 2021. Studies reporting the performance of at least one of the above-mentioned scores for predicting mortality in patients of 15 years of age and older with suspected infection or sepsis were eligible. The Quality Assessment of Diagnostic Accuracy Studies tool was used for risk-of-bias assessment. PRISMA guidelines were followed (PROSPERO registration: CRD42020153906). The bivariate random-effects regression model was used to pool the individual sensitivities, specificities and areas-under-the-curve (AUC).

FINDINGS

Twenty-four articles (of 5669 identified) with 27,237 patients were eligible for inclusion. qSOFA pooled sensitivity was 0·70 (95% confidence interval [CI] 0·60-0·78), specificity 0·73 (95% CI 0·67-0·79), and AUC 0·77 (95% CI 0·72-0·82). SIRS pooled sensitivity, specificity and AUC were 0·88 (95% CI 0·79 -0·93), 0·34 (95% CI 0·25-0·44), and 0·69 (95% CI 0·50-0·83), respectively. MEWS pooled sensitivity, specificity and AUC were 0·70 (95% CI 0·57 -0·81), 0·61 (95% CI 0·42-0·77), and 0·72 (95% CI 0·64-0·77), respectively. UVA pooled sensitivity, specificity and AUC were 0·49 (95% CI 0·33 -0·65), 0·91(95% CI 0·84-0·96), and 0·76 (95% CI 0·44-0·93), respectively. Significant heterogeneity was observed in the pooled analysis.

INTERPRETATION

Individual score performances ranged from poor to acceptable. Future studies should combine selected or modified elements of different scores.

FUNDING

Partially funded by the UK National Institute for Health Research (NIHR) (17/63/42).

Predicting mortality in adults with suspected infection in a Rwandan hospital: an evaluation of the adapted MEWS, qSOFA and UVA scores

RATIONALE

Mortality prediction scores are increasingly being evaluated in low and middle income countries (LMICs) for research comparisons, quality improvement and clinical decision-making. The modified early warning score (MEWS), quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA), and Universal Vital Assessment (UVA) score use variables that are feasible to obtain, and have demonstrated potential to predict mortality in LMIC cohorts.

OBJECTIVE

To determine the predictive capacity of adapted MEWS, qSOFA and UVA in a Rwandan hospital.

DESIGN, SETTING, PARTICIPANTS AND OUTCOME MEASURES

We prospectively collected data on all adult patients admitted to a tertiary hospital in Rwanda with suspected infection over 7 months. We calculated an adapted MEWS, qSOFA and UVA score for each participant. The predictive capacity of each score was assessed including sensitivity, specificity, positive and negative predictive value, OR, area under the receiver operating curve (AUROC) and performance by underlying risk quartile.

RESULTS

We screened 19 178 patient days, and enrolled 647 unique patients. Median age was 35 years, and in-hospital mortality was 18.1%. The proportion of data missing for each variable ranged from 0% to 11.7%. The sensitivities and specificities of the scores were: adapted MEWS >4, 50.4% and 74.9%, respectively; qSOFA >2, 24.8% and 90.4%, respectively; and UVA >4, 28.2% and 91.1%, respectively. The scores as continuous variables demonstrated the following AUROCs: adapted MEWS 0.69 (95% CI 0.64 to 0.74), qSOFA 0.65 (95% CI 0.60 to 0.70), and UVA 0.71 (95% CI 0.66 to 0.76); there was no statistically significant difference between the discriminative capacities of the scores.

CONCLUSION

Three scores demonstrated a modest ability to predict mortality in a prospective study of inpatients with suspected infection at a Rwandan tertiary hospital. Careful consideration must be given to their adequacy before using them in research comparisons, quality improvement or clinical decision-making.

Variation of vital signs with potential to influence the performance of qSOFA scoring in the Ethiopian general population at different altitudes of residency: A multisite cross-sectional study

Introduction

The physiological range of different vital signs is dependent on various environmental and individual factors. There is a strong interdependent relationship between vital signs and health conditions. Deviations of the physiological range are commonly used for risk assessment in clinical scores, e.g. respiratory rate (RR) and systolic blood pressure (BP_sys) in patients with infections within the quick sequential organ failure assessment (qSOFA) score. A limited number of studies have evaluated the performance of such scores in resource-limited health care settings, showing inconsistent results with mostly poor discriminative power. Divergent standard values of vital parameters in different populations, e.g. could influence the accuracy of various clinical scores.

Methods

This multisite cross-sectional observational study was performed among Ethiopians residing at various altitudes in the cities of Asella (2400m above sea level (a.s.l.)), Adama (1600m a.s.l.), and Semara (400m a.s.l.). Volunteers from the local general population were asked to complete a brief questionnaire and have vital signs measured. Individuals reporting acute or chronic illness were excluded.

Results

A positive qSOFA score (i.e. ≥2), indicating severe illness in patients with infection, was common among the studied population (n = 612). The proportion of participants with a positive qSOFA score was significantly higher in Asella (28.1%; 55/196), compared with Adama, (8.3%; 19/230; p<0.001) and Semara (15.1%; 28/186; p = 0.005). Concerning the parameters comprised in qSOFA, the thresholds for RR (≥22/min) were reached in 60.7%, 34.8%, and 38.2%, and for BP_sys (≤100 mmHg) in 48.5%, 27.8%, and 36.0% in participants from Asella, Adama, and Semara, respectively.

Discussion

The high positivity rate of qSOFA score in the studied population without signs of acute infection may be explained by variations of the physiological range of different vital signs, possibly related to the altitude of residence. Adaptation of existing scores using local standard values could be helpful for reliable risk assessment.

Profile of presentation of HIV-positive patients to an emergency department in Johannesburg, South Africa

Background

Despite improved availability and better access to antiretroviral therapy (ART), approximately 36% of human immunodeficiency virus (HIV)-positive South Africans are still not virally suppressed.

Objective

The aim of this study was to describe the patterns of presentation of HIV-positive patients to a major central hospital emergency department (ED).

Methods

In this prospectively designed study, consecutive HIV-positive patients presenting to the Charlotte Maxeke Johannesburg Academic Hospital (CMJAH) adult ED were enrolled between 07 July 2017 and 18 October 2018.

Results

A total of 1224 participants were enrolled. Human immunodeficiency virus was newly diagnosed in 212 (17.3%) patients, 761 (75.2%) were on ART, 245 (32.2%) reported ART non-adherence, 276 (22.5%) had bacterial pneumonia, 244 (19.9%) had tuberculosis (TB), 86 (7.0%) had gastroenteritis, 205 (16.7%) required intensive care unit admission, 381 (31.1%) were admitted for ≥ 7 days and 166 (13.6%) died. With regard to laboratory parameters, CD₄ cell count was < 100 cell/mm³ in 527 (47.6%) patients, the viral load (VL) was > 1000 copies/mL in 619 (59.0%), haemoglobin was < 11 g/dL in 636 (56.3%), creatinine was > 120 µmol/L in 294 (29.3%), lactate was > 2 mmol/L in 470 (42.0%) and albumin was < 35 g/L in 633 (60.8%).

Conclusion

Human immunodeficiency virus-positive patients presenting to the CMJAH ED demonstrated a high prevalence of opportunistic infections, required a prolonged hospital stay and had high mortality rates. There is a need to improve the quality of ART services and accessibility to care.

Performance of Prognostication Scores for Mortality in Injured Patients in Rwanda

INTRODUCTION

While trauma prognostication and triage scores have been designed for use in lower-resourced healthcare settings specifically, the comparative clinical performance between trauma-specific and general triage scores for risk-stratifying injured patients in such settings is not well understood. This study evaluated the Kampala Trauma Score (KTS), Revised Trauma Score (RTS), and Triage Early Warning Score (TEWS) for accuracy in predicting mortality among injured patients seeking emergency department (ED) care at the Centre Hospitalier Universitaire de Kigali (CHUK) in Rwanda.

METHODS

A retrospective, randomly sampled cohort of ED patients presenting with injury was accrued from August 2015-July 2016. Primary outcome was 14-day mortality and secondary outcome was overall facility-based mortality. We evaluated summary statistics of the cohort. Bootstrap regression models were used to compare areas under receiver operating curves (AUC) with associated 95% confidence intervals (CI).

RESULTS

Among 617 cases, the median age was 32 years and 73.5% were male. The most frequent mechanism of injury was road traffic incident (56.2%). Predominant anatomical regions of injury were craniofacial (39.3%) and lower extremities (38.7%), and the most common injury types were fracture (46.0%) and contusion (12.0%). Fourteen-day mortality was 2.6% and overall facility-based mortality was 3.4%. For 14-day mortality, TEWS had the highest accuracy (AUC = 0.88, 95% CI, 0.76-1.00), followed by RTS (AUC = 0.73, 95% CI, 0.55-0.92), and then KTS (AUC = 0.65, 95% CI, 0.47-0.84). Similarly, for facility-based mortality, TEWS (AUC = 0.89, 95% CI, 0.79-0.98) had greater accuracy than RTS (AUC = 0.76, 95% CI, 0.61-0.91) and KTS (AUC = 0.68, 95% CI, 0.53-0.83). On pairwise comparisons, RTS had greater prognostic accuracy than KTS for 14-day mortality (P = 0.011) and TEWS had greater accuracy than KTS for overall (P = 0.007) mortality. However, TEWS and RTS accuracy were not significantly different for 14-day mortality (P = 0.864) or facility-based mortality (P = 0.101).

CONCLUSION

In this cohort of emergently injured patients in Rwanda, the TEWS demonstrated the greatest accuracy for predicting mortality outcomes, with no significant discriminatory benefit found in the use of the trauma-specific RTS or KTS instruments, suggesting that the TEWS is the most clinically useful approach in the setting studied and likely in other similar ED environments.

Emergency medicine matters: epidemiology of medical pathology and changes in patient outcomes after implementation of a post-graduate training program at a Tertiary Teaching Hospital in Kigali, Rwanda

Background

Emergency care is a new but growing specialty across Africa where medical conditions have been estimated to account for 92% of all disability-adjusted life years. This study describes the epidemiology of medical emergencies and the impact of formalized emergency care training on patient outcomes for medical conditions in Rwanda.

Methods

A retrospective cohort study was performed using a database of randomly sampled patients presenting to the emergency center (EC) at the University Teaching Hospital of Kigali. All patients, > 15 years of age treated for medical emergencies pre- and post-implementation of an Emergency Medicine (EM) residency training program were eligible for inclusion. Patient characteristics and final diagnosis were described by time period (January 2013–September 2013 versus September 2015–June 2016). Univariate chi-squared analysis was performed for diagnoses, EC interventions, and all cause EC and inpatient mortality stratified by time period.

Results

A random sample of 1704 met inclusion with 929 patients in the pre-residency time period and 775 patients in the post-implementation period. Demographics, triage vital signs, and shock index were not different between time periods. Most frequent diagnoses included gastrointestinal, infectious disease, and neurologic pathology. Differences by time period in EC management included antibiotic use (37.2% vs. 42.2%, p = 0.04), vasopressor use (1.9% vs. 0.5%, p = 0.01), IV crystalloid fluid (IVF) use (55.5% vs. 47.6%, p = 0.001) and mean IVF administration (2057 ml vs. 2526 ml, p < 0.001). EC specific mortality fell from 10.0 to 1.4% (p < 0.0001) across time periods.

Conclusions

Mortality rates fell across top medical diagnoses after implementation of an EM residency program. Changes in resuscitation care may explain, in part, this mortality decrease. This study demonstrates that committing to emergency care can potentially have large effects on reducing mortality.

Funding sources for research: A research primer for low- and middle-income countries

Research is a fundamental component of the development of quality emergency care systems. Developing qualified professionals and programs to conduct emergency care research is essential to understanding epidemiology in low resource settings. This leads to evaluating research outcomes, developing clinical practice guidelines and program implementation. This paper aims to introduce the reader to opportunities for research funding at various stages of one's career. We will discuss concepts necessary to obtain funding for research, a crucial step towards initiating a research program. The chapter further describes competitive funding mechanisms including governmental agencies, foundations and private industry along with organisations that offer funding for global health and emergency care research. We describe categories of grants specific to a stage of an investigator's career, developing a team for a proposal and the grant application process.

The Combined SIRS + qSOFA (qSIRS) Score is More Accurate Than qSOFA Alone in Predicting Mortality in Patients with Surgical Sepsis in an LMIC Emergency Department

BACKGROUND

qSOFA has been proposed as a prognostic tool in patients with sepsis. This study set out to assess the sensitivity of several scores, namely: the pre-ICU qSOFA, the qSOFA with lactate (qSOFA L), SIRS score, qSOFA + SIRS score (qSIRS) and qSIRS with lactate (qSIRS L) in predicting in-hospital mortality in patients with surgical sepsis as well as the sensitivity of these scores in predicting high-grade sepsis. The secondary aim was to determine which of these scores is best suited to predict high-grade surgical sepsis.

METHODS

This was a retrospective cohort study that was conducted between December 2012 and August 2017 in a public metropolitan surgical service. Data from patients aged > 13 years, who were admitted to the hospital and who had an emergency surgical procedure for source control were retrieved from a prospectively maintained hybrid electronic database. The qSOFA, qSOFA plus lactate (qSOFA L), SIRS and qSOFA + SIRS (qSIRS), as well as the qSIRS plus lactate (qSIRS L), were calculated for each patient. A lactate level that was greater than 2mmol/L was deemed to be a positive finding. Any score ≥2 was deemed to be a positive score. The outcome measure was in-hospital mortality. The prognostic value of qSOFA, qSOFA L, SIRS, qSIRS and qSIRS L was studied. Receiver operating characteristic analyses were performed to determine the area under the curve (AUC), sensitivity, specificity and positive and negative likelihood ratios for positive qSOFA, qSOFA L, SIRS, qSIRS, and qSIRS L. Contingency tables were used to calculate the sensitivity, specificity, PPV and NPV for predicting severe or high-grade surgical sepsis.

RESULTS

There were a total number of 1884 patients in the sample group of whom 855 were female (45.4%). The median patient age was 36 years (IQR 23-56). A total of 1489 patients (79%) were deemed to have high-grade sepsis based on an advanced EGS AAST grading, whilst 395 patients (21%) had low-grade sepsis. A total of 71 patients died (3.8%). Of these patients who died, 67 (94.4%) had high-grade sepsis and 4 (5.6%) had low-grade sepsis. The mortality rate in the high-grade sepsis group was 4.5%, whilst the mortality rate in the low-grade sepsis group was 1%. The scores with the greatest accuracy in predicting mortality were qSIRS (AUROC 0.731, 95% CI 0.68-0.78), followed by SIRS (AUROC 0.70, 95% CI 0.65-0.75). The qSOFA and qSOFA L were the least accurate in predicting mortality (AUROC 0.684, 95% CI 0.63-0.74 for both). The addition of lactate had no significant effect on the accuracy of the five scores in predicting mortality. Patients with a qSOFA ≥ 2 have an increased risk of dying (OR 5.8), as do patients with a SIRS score ≥2 (OR 2.7). qSIRS L had the highest sensitivity (69%) in predicting the presence of high-grade surgical sepsis, followed by qSIRS (65.5% sensitivity). qSOFA showed a very low sensitivity of only 4.5% and a high specificity of 99.2%. The addition of lactate to the score marginally improved the sensitivity. Lactate of 2mmol/L or more was also an independent predictor of high-grade sepsis.

CONCLUSION

The qSIRS score is most accurate in predicting mortality in surgical sepsis. The qSOFA score is inferior to both the SIRS and the qSIRS scores in predicting mortality. The qSIRS score with the addition of lactate to the qSIRS score made it the most sensitive score in predicting high-grade surgical sepsis.

The Prevalence and Outcomes of Sepsis in Adult Patients in Two Hospitals in Malawi

There are an estimated 19.4 million sepsis cases every year, many of them in low-income countries. The newly adopted definition of sepsis uses Sequential Organ Failure Assessment Score (SOFA), a score which is not feasible in many low-resource settings. A simpler quick-SOFA (qSOFA) based solely on vital signs score has been devised for identification of suspected sepsis. This study aimed to determine in-hospital prevalence and outcomes of sepsis, as defined as suspected infection and a qSOFA score of 2 or more, in two hospitals in Malawi. The secondary aim was to evaluate qSOFA as a predictor of mortality. A cross-sectional study of adult in-patients in two hospitals in Malawi was conducted using prospectively collected single-day point-prevalence data and in-hospital follow-up. Of 1,135 participants, 81 (7.1%) had sepsis. Septic patients had a higher hospital mortality rate (17.5%) than non-septic infected patients (9.0%, p = 0.027, odds ratio 2.1 [1.1-4.3]), although the difference was not statistically significant after adjustment for baseline characteristics. For in-hospital mortality among patients with suspected infection, qSOFA ≥ 2 had a sensitivity of 31.8%, specificity of 82.1%, a positive predictive value of 17.5%, and a negative predictive value of 91.0%. In conclusion, sepsis is common and is associated with a high risk of death in admitted patients in hospitals in Malawi. In low-resource settings, qSOFA score that uses commonly available vital signs data may be a tool that could be used for identifying patients at risk-both for those with and without a suspected infection.

Predictive Validity of the qSOFA Score for Sepsis in Adults with Community-Onset Staphylococcal Infection in Thailand

The quick sequential organ failure assessment (qSOFA) score has had limited validation in lower resource settings and was developed using data from high-income countries. We sought to evaluate the predictive validity of the qSOFA score for sepsis within a low- and middle-income country (LMIC) population with culture-proven staphylococcal infection. This was a secondary analysis of a prospective multicenter cohort in Thailand with culture-positive infection due to Staphylococcus aureus or S. argenteus within 24 h of admission and positive (≥2/4) systemic inflammatory response syndrome (SIRS) criteria. Primary exposure was maximum qSOFA score within 48 h of culture collection and primary outcome was mortality at 28 days. Baseline risk of mortality was determined using a multivariable logistic regression model with age, gender, and co-morbidities significantly associated with the outcome. Predictive validity was assessed by discrimination of mortality using area under the receiver operating characteristic (AUROC) curve compared to a model using baseline risk factors alone. Of 253 patients (mean age 54 years (SD 16)) included in the analysis, 23 (9.1%) died by 28 days after enrollment. Of those who died, 0 (0%) had a qSOFA score of 0, 8 (35%) had a score of 1, and 15 (65%) had a score ≥2. The AUROC of qSOFA plus baseline risk was significantly greater than for the baseline risk model alone (AUROC_qSOFA = 0.80 (95% CI, 0.70–0.89), AUROC_baseline = 0.62 (95% CI, 0.49–0.75); p < 0.001). Among adults admitted to four Thai hospitals with community-onset coagulase-positive staphylococcal infection and SIRS, the qSOFA score had good predictive validity for sepsis.

A Prospective Comparison of Quick Sequential Organ Failure Assessment, Systemic Inflammatory Response Syndrome Criteria, Universal Vital Assessment, and Modified Early Warning Score to Predict Mortality in Patients with Suspected Infection in Gabon

The quick sequential organ failure assessment (qSOFA) score has been proposed for risk stratification of emergency room patients with suspected infection. Its use of simple bedside observations makes qSOFA an attractive option for resource-limited regions. We prospectively assessed the predictive ability of qSOFA compared with systemic inflammatory response syndrome (SIRS), universal vital assessment (UVA), and modified early warning score (MEWS) in a resource-limited setting in Lambaréné, Gabon. In addition, we evaluated different adaptations of qSOFA and UVA in this cohort and an external validation cohort from Malawi. We included 279 cases, including 183 with an ad hoc (suspected) infectious disease diagnosis. Overall mortality was 5%. In patients with an infection, oxygen saturation, mental status, human immunodeficiency virus (HIV) status, and all four risk stratification score results differed significantly between survivors and non-survivors. The UVA score performed best in predicting mortality in patients with suspected infection, with an area under the receiving operator curve (AUROC) of 0.90 (95% confidence interval [CI]: 0.78-1.0, P < 0.0001), outperforming qSOFA (AUROC 0.77; 95% CI: 0.63-0.91, P = 0.0003), MEWS (AUROC 0.72; 95% CI: 0.58-0.87, P = 0.01), and SIRS (AUROC 0.70; 95% CI: 0.52-0.88, P = 0.03). An amalgamated qSOFA score applying the UVA thresholds for blood pressure and respiratory rate improved predictive ability in Gabon (AUROC 0.82; 95% CI: 0.68-0.96) but performed poorly in a different cohort from Malawi (AUROC 0.58; 95% CI: 0.51-0.64). In conclusion, UVA had the best predictive ability, but multicenter studies are needed to validate the qSOFA and UVA scores in various settings and assess their impact on patient outcome.

Musculoskeletal Injuries and Outcomes Pre- and Post- Emergency Medicine Training Program

Introduction

Musculoskeletal injuries (MSI) comprise a large portion of the trauma burden in low- and middle-income countries (LMIC). Rwanda recently launched its first emergency medicine training program (EMTP) at the University Teaching Hospital-Kigali (UTH-K), which may help to treat such injuries; yet no current epidemiological data is available on MSI in Rwanda.

Methods

We conducted this pre-post study during two data collection periods at the UTH-K from November 2012 to July 2016. Data collection for MSI is limited and thus is specific to fractures. We included all patients with open, closed, or mixed fractures, hereafter referred to as MSI. Gathered information included demographics and outcomes including death, traumatic complications, and length of hospital stay, before and after the implementation of the EMTP.

Results

We collected data from 3609 patients. Of those records, 691 patients were treated for fractures, and 674 of them had sufficient EMTP data measured for inclusion in the analysis of results (279 from pre-EMTP and 375 from post-EMTP). Patient demographics demonstrate that a majority of MSI cases are male (71.6% male vs 28.4% female) and young (64.3% below 35 years of age). Among mechanisms of injury, major causes included road traffic accidents (48.1%), falls (34.2%), and assault (6.0%). There was also an observed association between EMTP and trends of the three primary outcomes: a reduction of death in the emergency department (ED) from those with MSI by 89.9%, from 2.51% to 0.25% (p = 0.0077); a reduction in traumatic complications for MSI patients by 71.7%, from 3.58% to 1.01% (p = 0.0211); and a reduction in duration of stay in the ED among those with MSI by 52.7% or 2.81 days on average, from 5.33 to 2.52 days (p = 0.0437).

Conclusion

This study reveals the current epidemiology of MSI morbidity and mortality for a major Rwandan teaching hospital and the potential impacts of EM training implementation among those with MSI. Residency training programs such as EMTP appear capable of reducing mortality, complications, and ED length of stay among those with MSI caused by fractures. Such findings underscore the efficacy and importance of investments in educating the next generation of health professionals to combat prevalent MSI within their communities.

Clinical emergency care research in low-income and middle-income countries: opportunities and challenges

Disease processes that frequently require emergency care constitute approximately 50% of the total disease burden in low-income and middle-income countries (LMICs). Many LMICs continue to deal with emergencies caused by communicable disease states such as pneumonia, diarrhoea, malaria and meningitis, while also experiencing a marked increase in non-communicable diseases, such as cardiovascular diseases, diabetes mellitus and trauma. For many of these states, emergency care interventions have been developed through research in high-income countries (HICs) and advances in care have been achieved. However, in LMICs, clinical research, especially interventional trials, in emergency care are rare. Furthermore, there exists minimal research on the emergency management of diseases, which are rarely encountered in HICs but impact the majority of LMIC populations. This paper explores challenges in conducting clinical research in patients with emergency conditions in LMICs, identifies examples of successful clinical research and highlights the system, individual and study design characteristics that made such research possible in LMICs. Derived from the available literature, a focused list of high impact research considerations are put forth.

Impact of emergency medicine training implementation on mortality outcomes in Kigali, Rwanda: An interrupted time-series study

INTRODUCTION

Although emergency medicine (EM) training programmes have begun to be introduced in low- and middle-income countries (LMICs), minimal data exist on their effects on patient-centered outcomes in such settings. This study evaluated the impact of EM training and associated systems implementation on mortality among patients treated at the University Teaching Hospital-Kigali (UTH-K).

METHODS

At UTH-K an EM post-graduate diploma programme was initiated in October 2013, followed by a residency-training programme in August 2015. Prior to October 2013, care was provided exclusively by general practice physicians (GPs); subsequently, care has been provided through mutually exclusive shifts allocated between GPs and EM trainees. Patients seeking Emergency Centre (EC) care during November 2012-October 2013 (pre-training) and August 2015-July 2016 (post-training) were eligible for inclusion. Data were abstracted from a random sample of records using a structured protocol. The primary outcomes were EC and overall hospital mortality. Mortality prevalence and risk differences (RD) were compared pre- and post-training. Magnitudes of effects were quantified using regression models to yield adjusted odds ratios (aOR) with 95% confidence intervals (CI).

RESULTS

From 43,213 encounters, 3609 cases were assessed. The median age was 32 years with a male predominance (60.7%). Pre-training EC mortality was 6.3% (95% CI 5.3-7.5%), while post-training EC mortality was 1.2% (95% CI 0.7-1.8%), constituting a significant decrease in adjusted analysis (aOR = 0.07, 95% CI 0.03-0.17; p < 0.001). Pre-training overall hospital mortality was 12.2% (95% CI 10.9-13.8%). Post-training overall hospital mortality was 8.2% (95% CI 6.9-9.6%), resulting in a 43% reduction in mortality likelihood (aOR = 0.57, 95% CI 0.36-0.94; p = 0.016).

DISCUSSION

In the studied population, EM training and systems implementation was associated with significant mortality reductions demonstrating the potential patient-centered benefits of EM development in resource-limited settings.

Association of the Quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) Score With Excess Hospital Mortality in Adults With Suspected Infection in Low- and Middle-Income Countries

Importance

The quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) score has not been well-evaluated in low- and middle-income countries (LMICs).

Objective

To assess the association of qSOFA with excess hospital death among patients with suspected infection in LMICs and to compare qSOFA with the systemic inflammatory response syndrome (SIRS) criteria.

Design, Settings, and Participants

Retrospective secondary analysis of 8 cohort studies and 1 randomized clinical trial from 2003 to 2017. This study included 6569 hospitalized adults with suspected infection in emergency departments, inpatient wards, and intensive care units of 17 hospitals in 10 LMICs across sub-Saharan Africa, Asia, and the Americas.

Exposures

Low (0), moderate (1), or high (≥2) qSOFA score (range, 0 [best] to 3 [worst]) or SIRS criteria (range, 0 [best] to 4 [worst]) within 24 hours of presentation to study hospital.

Main Outcomes and Measures

Predictive validity (measured as incremental hospital mortality beyond that predicted by baseline risk factors, as a marker of sepsis or analogous severe infectious course) of the qSOFA score (primary) and SIRS criteria (secondary).

Results

The cohorts were diverse in enrollment criteria, demographics (median ages, 29-54 years; males range, 36%-76%), HIV prevalence (range, 2%-43%), cause of infection, and hospital mortality (range, 1%-39%). Among 6218 patients with nonmissing outcome status in the combined cohort, 643 (10%) died. Compared with a low or moderate score, a high qSOFA score was associated with increased risk of death overall (19% vs 6%; difference, 13% [95% CI, 11%-14%]; odds ratio, 3.6 [95% CI, 3.0-4.2]) and across cohorts (P < .05 for 8 of 9 cohorts). Compared with a low qSOFA score, a moderate qSOFA score was also associated with increased risk of death overall (8% vs 3%; difference, 5% [95% CI, 4%-6%]; odds ratio, 2.8 [95% CI, 2.0-3.9]), but not in every cohort (P < .05 in 2 of 7 cohorts). High, vs low or moderate, SIRS criteria were associated with a smaller increase in risk of death overall (13% vs 8%; difference, 5% [95% CI, 3%-6%]; odds ratio, 1.7 [95% CI, 1.4-2.0]) and across cohorts (P < .05 for 4 of 9 cohorts). qSOFA discrimination (area under the receiver operating characteristic curve [AUROC], 0.70 [95% CI, 0.68-0.72]) was superior to that of both the baseline model (AUROC, 0.56 [95% CI, 0.53-0.58; P < .001) and SIRS (AUROC, 0.59 [95% CI, 0.57-0.62]; P < .001).

Conclusions and Relevance

When assessed among hospitalized adults with suspected infection in 9 LMIC cohorts, the qSOFA score identified infected patients at risk of death beyond that explained by baseline factors. However, the predictive validity varied among cohorts and settings, and further research is needed to better understand potential generalizability.