Derivation and validation of a universal vital assessment (UVA) score: a tool for predicting mortality in adult hospitalised patients in sub-Saharan Africa

Outcomes of adults hospitalized with COVID-19 at the University Teaching Hospital of Butare in Rwanda and validation of the Universal Vital Assessment (UVA) mortality risk score

There are few data regarding clinical outcomes from COVD-19 from low-income countries (LICs) including Rwanda. Accordingly, we aimed to determine 1) outcomes of patients admitted to hospital with COVID-19 in Rwanda, and 2) the ability of the Universal Vital Assessment (UVA) score to predict mortality in patients with COVID-19 compared to sequential organ failure assessment (SOFA) and quick (qSOFA) scores. We conducted a retrospective study of patients aged ≥18 years hospitalized with laboratory-confirmed COVID-19 at the University Teaching Hospital of Butare (CHUB), Rwanda, April 2021-January 2022. For each participant, we calculated UVA, SOFA, and qSOFA risk scores and determined their area under the receive operating characteristic curve (AUC). We used logistic regression to determine predictors of mortality. Of the 150 patients included, 83 (55%) were female and the median (IQR) age was 61 (43-73) years. The median (IQR) length of hospital stay was 6 (3-10) days. Respiratory failure occurred in 69 (46%) including 34 (23%) who had ARDS. The case fatality rate was 44%. Factors independently associated with mortality included acute kidney injury (adjusted odds ratio [aOR] 7.99, 95% confidence interval [CI] 1.47-43.22, p = 0.016), severe COVID-19 (aOR 3.42, 95% CI 1.06-11.01, p = 0.039), and a UVA score >4 (aOR 7.15, 95% CI 1.56-32.79, p = 0.011). The AUCs for UVA, qSOFA, and SOFA scores were 0.86 (95% CI 0.79-0.92), 0.81 (95% CI 0.74-0.88), and 0.84 (95% CI 0.78-0.91), respectively, which were not statistically significantly different from each other. At a UVA score cut-off of 4, the sensitivity, specificity, positive predictive value, and negative predictive value for mortality were 0.58, 0.93, 0.86, and 0.74, respectively. Patients hospitalized with COVID-19 in CHUB had high mortality, which was accurately predicted by the UVA score. Calculation of the UVA score in patients with COVID-19 in LICs may assist clinicians with triage and other management decisions.

Predicting mortality in febrile adults: comparative performance of the MEWS, qSOFA, and UVA scores using prospectively collected data among patients in four health-care sites in sub-Saharan Africa and South-Eastern Asia

Background

Clinical severity scores can identify patients at risk of severe disease and death, and improve patient management. The modified early warning score (MEWS), the quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA), and the Universal Vital Assessment (UVA) were developed as risk-stratification tools, but they have not been fully validated in low-resource settings where fever and infectious diseases are frequent reasons for health care seeking. We assessed the performance of MEWS, qSOFA, and UVA in predicting mortality among febrile patients in the Lao PDR, Malawi, Mozambique, and Zimbabwe.

Methods

We prospectively enrolled in- and outpatients aged ≥ 15 years who presented with fever (≥37.5 °C) from June 2018-March 2021. We collected clinical data to calculate each severity score. The primary outcome was mortality 28 days after enrolment. The predictive performance of each score was determined using area under the receiver operating curve (AUC).

Findings

A total of 2797 participants were included in this analysis. The median (IQR) age was 32 (24-43) years, 38% were inpatients, and 60% (1684/2797) were female. By the time of follow-up, 7% (185/2797) had died. The AUC (95% CI) for MEWS, qSOFA and UVA were 0.67 (0.63-0.71), 0.68 (0.64-0.72), and 0.82 (0.79-0.85), respectively. The AUC comparison found UVA outperformed both MEWS (p < 0.001) and qSOFA (p < 0.001).

Interpretation

We showed that the UVA score performed best in predicting mortality among febrile participants by the time follow-up compared with MEWS and qSOFA, across all four study sites. The UVA score could be a valuable tool for early identification, triage, and initial treatment guidance of high-risk patients in resource-limited clinical settings.

Funding

FCDO.

Factors Associated With Death at 30 Days and Evaluation of Clinical Risk Scores Among Patients With Cancer Admitted With Postchemotherapy Infection in Uganda: A Prospective Cohort Study

Background

Little is known about outcomes from cancer chemotherapy--associated infections in sub-Saharan Africa. Accordingly, among patients with cancer admitted with postchemotherapy infection in Mbarara, Uganda, we aimed to determine (1) the 30-day case fatality rate, (2) factors associated with mortality rate, and (3) clinical risk score performance.

Methods

We enrolled participants aged ≥18 years if they (1) received cancer chemotherapy within the past 30 days, (2) were admitted to the oncology ward, and (3) were prescribed intravenous antibiotics. We used Cox proportional hazards regression to determine predictors of death at 30 days and calculated the area under the receiver operating characteristic curve (AUC) for each clinical risk score.

Results

Among 150 participants, 67 (45%) were female, and the median (interquartile range) age was 56 (43-66) years. Esophageal cancer (18%) and pneumonia (42%) were the most common cancer and infection, respectively. Death occurred within 30 days in 63 participants (42%). Quick Sequential Organ Failure Assessment (qSOFA) score ≥2 (adjusted hazard ratio, 2.51 [95% confidence interval, 1.42-4.44]; P = .001), and Universal Vital Assessment (UVA) score >4 (2.13 [.08-4.18, P = .03) were independently associated with death at 30 days. An Eastern Cooperative Oncology Group (ECOG) score ≥3 was similarly independently associated with death at 30 days in the qSOFA and UVA models. The AUCs for qSOFA and UVA scores were 0.70 (95% confidence interval, .63-.79) and 0.72 (.64-.80), respectively.

Conclusions

In participants with postchemotherapy infection in Mbarara, Uganda, the case fatality rate was high. ECOG, qSOFA, and UVA scores were associated with death at 30 days.

The Universal Vital Assessment (UVA) score at 6 hours post-resuscitation predicts mortality in hospitalized adults with severe sepsis in Mbarara, Uganda

Sepsis is the leading cause of global death with the highest burden found in sub-Saharan Africa (sSA). The Universal Vital Assessment (UVA) score is a validated resource-appropriate clinical tool to identify hospitalized patients in sSA who are at risk of in-hospital mortality. Whether a decrease in the UVA score over 6 hours of resuscitation from sepsis is associated with improved outcomes is unknown. We aimed to determine (1) the association between 6-hour UVA score and in-hospital mortality, and (2) if a decrease in UVA score from admission to 6 hours was associated with improved in-hospital mortality. We analyzed data from participants with severe sepsis aged ≥14 years enrolled at the Mbarara Regional Referral Hospital in Uganda from October 2014 through May 2015. Among 197 participants, the median (interquartile range) age was 34 (27-47) years, 99 (50%) were female and 116 (59%) were living with HIV. At 6 hours, of the 65 participants in the high-risk group, 28 (43%) died compared to 28 (30%) of 94 in the medium-risk group (odds ratio [OR] 0.56, 95% confidence interval [CI] 0.29,1.08, p = 0.086) and 3 (9%) of 33 in the low-risk group (OR 0.13, 95% CI 0.03, 0.42, p = 0.002). In a univariate analysis of the 85 participants who improved their UVA risk group at 6 hours, 20 (23%) died compared to 39 (36%) of 107 participants who did not improve (OR 0.54, 95% CI 0.27-1.06, p = 0.055). In the multivariable analysis, the UVA score at 6 hours (adjusted OR [aOR] 1.26, 95%CI 1.10-1.45, p<0.001) was associated with in-hospital mortality. When adjusted for age and sex, improvement in the UVA risk group over 6 hours was associated with a non-statistically significant 43% decrease in odds of mortality (aOR 0.57, 95%CI 0.29-1.07, p = 0.08). Targeting a decrease in UVA score over 6 hours from admission may be a useful clinical endpoint for sepsis resuscitation in sSA, but this would need to be proven in a clinical trial.

Early Warning Systems for Critical Illness Outside the Intensive Care Unit

Early warning systems (EWSs) are designed and deployed to create a rapid assessment and response for patients with clinical deterioration outside the intensive care unit (ICU). These models incorporate patient-level data such as vital signs and laboratory values to detect or prevent adverse clinical events, such as vital signs and laboratories to allow detection and prevention of adverse clinical events such as cardiac arrest, intensive care transfer, or sepsis. The applicability, development, clinical utility, and general perception of EWS in clinical practice vary widely. Here, we review the field as it has grown from early vital sign-based scoring systems to contemporary multidimensional algorithms and predictive technologies for clinical decompensation outside the ICU.

A customised down-sampling machine learning approach for sepsis prediction

OBJECTIVE

Sepsis is a life-threatening condition in the ICU and requires treatment in time. Despite the accuracy of existing sepsis prediction models, insufficient focus on reducing alarms could worsen alarm fatigue and desensitisation in ICUs, potentially compromising patient safety. In this retrospective study, we aim to develop an accurate, robust, and readily deployable method in ICUs, only based on the vital signs and laboratory tests.

METHODS

Our method consists of a customised down-sampling process and a specific dynamic sliding window and XGBoost to offer sepsis prediction. The down-sampling process was applied to the retrospective data for training the XGBoost model. During the testing stage, the dynamic sliding window and the trained XGBoost were used to predict sepsis on the retrospective datasets, PhysioNet and FHC.

RESULTS

With the filtered data from PhysioNet, our method achieved 80.74% accuracy (77.90% sensitivity and 84.42% specificity) and 83.95% (84.82% sensitivity and 82.00% specificity) on the test set of PhysioNet-A and PhysioNet-B, respectively. The AUC score was 0.89 for both datasets. On the FHC dataset, our method achieved 92.38% accuracy (88.37% sensitivity and 95.16% specificity) and 0.98 AUC score on the test set of FHC.

CONCLUSION

Our results indicate that the down-sampling process and the dynamic sliding window with XGBoost brought robust and accurate performance to give sepsis prediction under various hospital settings. The localisation and robustness of our method can assist in sepsis diagnosis in different ICU settings.

The value of the INFECTIONS scoring system in identifying bacterial infections among patients presenting at the emergency department of a middle-income country: A pilot study

PURPOSE

To investigate which scoring system is the most accurate tool in predicting mortality among the infected patients who present to the emergency department in a middle-income country, and to validate a new scoring system to predict bacterial infections.

METHODS

This was a retrospective, single-center study among patients who were admitted via the emergency department of a public hospital. All patients who were started on antibiotics were included in the study, while patients aged < 18 years were excluded. Data collected includeding patients' demographics, vital signs and basic laboratory parameters like white blood cell count and creatinine. The sensitivity and specificity of different scoring systems were calculated as well as their negative and positive predictive values. Logistic regression was used to derive a novel early warning system for bacterial infections. The area under the receiver operating characteristic (AUROC) was computed for each scoring model.

RESULTS

In total, 109 patients were included in this study. The quick sequential organ failure assessment (qSOFA), search out severity and rapid acute physiology score had the highest AUROC (≥ 0.89) for predicting mortality, while qSOFA and universal vital assessment were the simplest scoring systems with an AUROC > 0.85; however, these scoring systems failed to predict whether patients were truly infected. The INFECTIONS (short for impaired mental status, not conscious, fast heart rate, elevated creatinine, high temperature, on inotrope, low oxygen, high neutrophils and high sugar) model reached an AUROC of 0.88 to more accurately predict the infectious state of a patient.

CONCLUSIONS

Middle-income countries should use the qSOFA or universal vital assessment score to identify the sickest patients in emergency department. The INFECTIONS score may help recognize patients with bacterial infections, but it should be further validated in multiple countries prior to widely use.

Multimorbidity-associated emergency hospital admissions: a "screen and link" strategy to improve outcomes for high-risk patients in sub-Saharan Africa: a prospective multicentre cohort study protocol

Background

The prevalence of multimorbidity (the presence of two or more chronic health conditions) is rapidly increasing in sub-Saharan Africa. Hospital care pathways that focus on single presenting complaints do not address this pressing problem. This has the potential to precipitate frequent hospital readmissions, increase health system and out-of-pocket expenses, and may lead to premature disability and death. We aim to present a description of inpatient multimorbidity in a multicentre prospective cohort study in Malawi and Tanzania.

Primary objectives

Clinical: Determine prevalence of multimorbid disease among adult medical admissions and measure patient outcomes. Health Economic: Measure economic costs incurred and changes in health-related quality of life (HRQoL) at 90 days post-admission. Situation analysis: Qualitatively describe pathways of patients with multimorbidity through the health system.

Secondary objectives

Clinical: Determine hospital readmission free survival and markers of disease control 90 days after admission. Health Economic: Present economic costs from patient and health system perspective, sub-analyse costs and HRQoL according to presence of different diseases. Situation analysis: Understand health literacy related to their own diseases and experience of care for patients with multimorbidity and their caregivers.

Methods

This is a prospective longitudinal cohort study of adult (≥18 years) acute medical hospital admissions with nested health economic and situation analysis in four hospitals: 1) Queen Elizabeth Central Hospital, Blantyre, Malawi; 2) Chiradzulu District Hospital, Malawi; 3) Hai District Hospital, Boma Ng'ombe, Tanzania; 4) Muhimbili National Hospital, Dar-es-Salaam, Tanzania. Follow-up duration will be 90 days from hospital admission. We will use consecutive recruitment within 24 hours of emergency presentation and stratified recruitment across four sites. We will use point-of-care tests to refine estimates of disease pathology. We will conduct qualitative interviews with patients, caregivers, healthcare providers and policymakers; focus group discussions with patients and caregivers, and observations of hospital care pathways.

Risk Prediction Models for Hospital Mortality in General Medical Patients: A Systematic Review

Objective

To systematically review contemporary prediction models for hospital mortality developed or validated in general medical patients.

Methods

We screened articles in five databases, from January 1, 2010, through April 7, 2022, and the bibliography of articles selected for final inclusion. We assessed the quality for risk of bias and applicability using the Prediction Model Risk of Bias Assessment Tool (PROBAST) and extracted data using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist. Two investigators independently screened each article, assessed quality, and extracted data.

Results

From 20,424 unique articles, we identified 15 models in 8 studies across 10 countries. The studies included 280,793 general medical patients and 19,923 hospital deaths. Models included 7 early warning scores, 2 comorbidities indices, and 6 combination models. Ten models were studied in all general medical patients (general models) and 7 in general medical patients with infection (infection models). Of the 15 models, 13 were developed using logistic or Poisson regression and 2 using machine learning methods. Also, 4 of 15 models reported on handling of missing values. None of the infection models had high discrimination, whereas 4 of 10 general models had high discrimination (area under curve >0.8). Only 1 model appropriately assessed calibration. All models had high risk of bias; 4 of 10 general models and 5 of 7 infection models had low concern for applicability for general medical patients.

Conclusion

Mortality prediction models for general medical patients were sparse and differed in quality, applicability, and discrimination. These models require hospital-level validation and/or recalibration in general medical patients to guide mortality reduction interventions.

Etiology of Fever and Associated Outcomes Among Adults Receiving Chemotherapy for the Treatment of Solid Tumors in Uganda

Background

Little is known about the microbiology and outcomes of chemotherapy-associated febrile illness among patients in sub-Saharan Africa. Understanding the microbiology of febrile illness could improve antibiotic selection and infection-related outcomes.

Methods

From September 2019 through June 2022, we prospectively enrolled adult inpatients at the Uganda Cancer Institute who had solid tumors and developed fever within 30 days of receiving chemotherapy. Evaluation included blood cultures, malaria rapid diagnostic tests, and urinary lipoarabinomannan testing for tuberculosis. Serum cryptococcal antigen was evaluated in participants with human immunodeficiency virus (HIV). The primary outcome was the mortality rate 40 days after fever onset, which we estimated using Cox proportional hazards models.

Results

A total of 104 febrile episodes occurred among 99 participants. Thirty febrile episodes (29%) had ≥1 positive microbiologic result. The most frequently identified causes of infection were tuberculosis (19%) and bacteremia (12%). The prevalence of tuberculosis did not differ by HIV status. The 40-day case fatality ratio was 25%. There was no difference in all-cause mortality based on HIV serostatus, presence of neutropenia, or positive microbiologic results. A universal vital assessment score of >4 was associated with all-cause mortality (hazard ratio, 14.5 [95% confidence interval, 5-42.7]).

Conclusions

The 40-day mortality rate among Ugandan patients with solid tumors who developed chemotherapy-associated febrile illness was high, and few had an identified source of infection. Tuberculosis and bacterial bloodstream infections were the leading diagnoses associated with fever. Tuberculosis should be included in the differential diagnosis for patients who develop fever after receiving chemotherapy in tuberculosis-endemic settings, regardless of HIV serostatus.

Association of clinical prediction scores with hospital mortality in an adult medical and surgical intensive care unit in Kenya

Importance

Mortality prediction among critically ill patients in resource limited settings is difficult. Identifying the best mortality prediction tool is important for counseling patients and families, benchmarking quality improvement efforts, and defining severity of illness for clinical research studies.

Objective

Compare predictive capacity of the Modified Early Warning Score (MEWS), Universal Vital Assessment (UVA), Tropical Intensive Care Score (TropICS), Rwanda Mortality Probability Model (R-MPM), and quick Sequential Organ Failure Assessment (qSOFA) for hospital mortality among adults admitted to a medical-surgical intensive care unit (ICU) in rural Kenya. We performed a pre-planned subgroup analysis among ICU patients with suspected infection.

Design, setting, and participants

Prospective single-center cohort study at a tertiary care, academic hospital in Kenya. All adults 18 years and older admitted to the ICU January 2018–June 2019 were included.

Main outcomes and measures

The primary outcome was association of clinical prediction tool score with hospital mortality, as defined by area under the receiver operating characteristic curve (AUROC). Demographic, physiologic, laboratory, therapeutic, and mortality data were collected. 338 patients were included, none were excluded. Median age was 42 years (IQR 33–62) and 61% (n = 207) were male. Fifty-nine percent (n = 199) required mechanical ventilation and 35% (n = 118) received vasopressors upon ICU admission. Overall hospital mortality was 31% (n = 104). 323 patients had all component variables recorded for R-MPM, 261 for MEWS, and 253 for UVA. The AUROC was highest for MEWS (0.76), followed by R-MPM (0.75), qSOFA (0.70), and UVA (0.69) (p &lt; 0.001). Predictive capacity was similar among patients with suspected infection.

Conclusion and relevance

All tools had acceptable predictive capacity for hospital mortality, with variable observed availability of the component data. R-MPM and MEWS had high rates of variable availability as well as good AUROC, suggesting these tools may prove useful in low resource ICUs.

Screening tools for predicting mortality of adults with suspected sepsis: an international sepsis cohort validation study

OBJECTIVES

We evaluated the performance of commonly used sepsis screening tools across prospective sepsis cohorts in the USA, Cambodia and Ghana.

DESIGN

Prospective cohort studies.

SETTING AND PARTICIPANTS

From 2014 to 2021, participants with two or more SIRS (Systemic Inflammatory Response Syndrome) criteria and suspected infection were enrolled in emergency departments and medical wards at hospitals in Cambodia and Ghana and hospitalised participants with suspected infection were enrolled in the USA. Cox proportional hazards regression was performed, and Harrell's C-statistic calculated to determine 28-day mortality prediction performance of the quick Sequential Organ Failure Assessment (qSOFA) score ≥2, SIRS score ≥3, National Early Warning Score (NEWS) ≥5, Modified Early Warning Score (MEWS) ≥5 or Universal Vital Assessment (UVA) score ≥2. Screening tools were compared with baseline risk (age and sex) with the Wald test.

RESULTS

The cohorts included 567 participants (42.9% women) including 187 participants from Kumasi, Ghana, 200 participants from Takeo, Cambodia and 180 participants from Durham, North Carolina in the USA. The pooled mortality was 16.4% at 28 days. The mortality prediction accuracy increased from baseline risk with the MEWS (C-statistic: 0.63, 95% CI 0.58 to 0.68; p=0.002), NEWS (C-statistic: 0.68; 95% CI 0.64 to 0.73; p<0.001), qSOFA (C-statistic: 0.70, 95% CI 0.64 to 0.75; p<0.001), UVA score (C-statistic: 0.73, 95% CI 0.69 to 0.78; p<0.001), but not with SIRS (0.60; 95% CI 0.54 to 0.65; p=0.13). Within individual cohorts, only the UVA score in Ghana performed better than baseline risk (C-statistic: 0.77; 95% CI 0.71 to 0.83; p<0.001).

CONCLUSIONS

Among the cohorts, MEWS, NEWS, qSOFA and UVA scores performed better than baseline risk, largely driven by accuracy improvements in Ghana, while SIRS scores did not improve prognostication accuracy. Prognostication scores should be validated within the target population prior to clinical use.

Evaluation of Three Clinical Prediction Tools to Predict Mortality in Hospitalized Patients with Lassa Fever

Lassa fever is a viral hemorrhagic illness with a case fatality rate for hospitalized patients as high as 69%. Identifying cases before they progress to serious illness can lead to earlier treatment and improved clinical outcomes. Three existing clinical prediction tools were evaluated on their ability to predict the in-hospital mortality in Lassa fever: the quick Sequential Organ Failure Assessment (qSOFA), the Modified Early Warning System (MEWS), and the Universal Vital Assessment (UVA). This was a retrospective cohort study of patients admitted to the dedicated Lassa fever ward of the Kenema Government Hospital in Sierra Leone between May 2013 and December 2019. Data among three serology groups were analyzed: Lassa antigen-positive (Ag+) regardless of IgM status, Lassa Ag- and IgM+, and Lassa Ag- and IgM- cases. There were 123 cases of suspected Lassa fever included in this study. Abnormalities in respiratory rate, oxygenation status, mental status, and serum markers of kidney and liver dysfunction were more likely seen in the Ag+ group, which had an in-hospital mortality of 85.7%. For the Lassa Ag+ group, the sensitivity and positive predictive value of qSOFA ≥ 2 was 70.6% and 92.3%, MEWS ≥ 5 was 96.9% and 86.1%, and UVA ≥ 5 was 60.0% and 100.0%. The MEWS and UVA scores show potential for use in Lassa fever, but there is opportunity for future development of a tool that includes the clinical and laboratory markers specific to Lassa fever.

Factors associated with in-hospital mortality of patients admitted to an intensive care unit in a tertiary hospital in Malawi

Objective

To determine factors associated with in-hospital death among patients admitted to ICU and to evaluate the predictive values of single severely deranged vital signs and several severity scoring systems.

Methods

A combined retrospective and prospective cohort study of patients admitted to the adult ICU in a tertiary hospital in Malawi was conducted between January 2017 and July 2019. Predefined potential risk factors for in-hospital death were studied with univariable and multivariable logistic regression models, and the performance of severity scores was assessed.

Results

The median age of the 822 participants was 31 years (IQR 21–43), and 50% were female. Several factors at admission were associated with in-hospital mortality: the presence of one or more severely deranged vital signs, adjusted odds ratio (aOR) 1.9 (1.4–2.6); treatment with vasopressor aOR 2.3 (1.6–3.4); received cardiopulmonary resuscitation aOR 1.7 (1.2–2.6) and treatment with mechanical ventilation aOR 1.5 (1.1–2.1). Having had surgery had a negative association with in-hospital mortality aOR 0.5 (0.4–0.7). The predictive accuracy of the severity scoring systems had varying sensitivities and specificities, but none were sufficiently accurate to be clinically useful.

Conclusions

In conclusion, the presence of one or more severely deranged vital sign in patients admitted to ICU may be useful as a simple marker of an increased risk of in-hospital death.

Enhanced bedside mortality prediction combining point-of-care lactate and the quick Sequential Organ Failure Assessment (qSOFA) score in patients hospitalised with suspected infection in southeast Asia: a cohort study

Background

Simple, bedside prediction of infection-related mortality in low-resource settings is crucial for triage and resource-utilisation decisions. We aimed to evaluate mortality prediction by combining point-of-care venous lactate with the quick Sequential Organ Failure Assessment (qSOFA) score in adult patients admitted to hospital with suspected infection in southeast Asia.

Methods

We performed a cohort study by prospectively enrolling patients aged 18 years or older who had been admitted to hospital within the previous 24 h for suspected infection (with at least three documented systemic manifestations of infection according to the 2012 Surviving Sepsis Campaign) at Sunpasitthiprasong Hospital in Ubon Ratchathani, Thailand (derivation cohort). Venous lactate concentration was determined by a point-of-care device and multiple scores were developed. We then evaluated candidate 28-day mortality prediction models combining qSOFA and the lactate scores. A final model was compared with the qSOFA score, a lactate score, and a modified Sequential Organ Failure Assessment (SOFA) score for mortality discrimination using the area under the receiver operating characteristic curve (AUROC). Mortality discrimination of the qSOFA-lactate score was then verified in an external, prospectively enrolled, multinational cohort in southeast Asia.

Findings

Between March 1, 2013, and Jan 26, 2017, 5001 patients were enrolled in the derivation cohort; 4980 had point-of-care lactate data available and were eligible for analysis, and 816 died within 28 days of enrolment. The discrimination for 28-day mortality prediction of a qSOFA-lactate score combining the qSOFA score and a lactate score was superior to that of the qSOFA score alone (AUROC 0·78 [95% CI 0·76–0·80] vs 0·68 [0·67–0·70]; p<0·0001) and similar to a modified SOFA score (0·77 [0·75–0·78]; p=0·088). A lactate score alone had superior discrimination compared with the qSOFA score (AUROC 0·76 [95% CI 0.74–0.78]; p<0·0001). 815 patients were enrolled in the external validation cohort and 792 had point-of-care lactate data and were included in the analysis; the qSOFA-lactate score (AUROC 0·77 [95% CI 0·73–0·82]) showed significantly improved 28-day mortality discrimination compared with the qSOFA score alone (0·69 [0·63–0·74]; p<0·0001).

Interpretation

In southeast Asia, rapid, bedside assessments based on point-of-care lactate concentration combined with the qSOFA score can identify patients at risk of sepsis-related mortality with greater accuracy than the qSOFA score alone, and with similar accuracy to a modified SOFA score.

Funding

National Institutes of Health, Wellcome Trust.

Multiple pathogens contribute to human immunodeficiency virus-related sepsis in addition to Mycobacterium tuberculosis: A prospective cohort in Tanzania

Background

Mortality from tuberculosis (TB) sepsis is common among patients living with human immunodeficiency virus (PLHIV). We aimed to detect M. tuberculosis (MTB) and additional sepsis etiologies, and mortality determinants in PLHIV.

Methods

This prospective cohort study consented and followed-up PLHIV for 28 days in northern Tanzania. From May through December 2021, patients provided urine and sputum for TB testing in lateral-flow lipoarabinomannan (LF-LAM) and Xpert® MTB/RIF. Bacterial blood culture, cryptococcal antigen, malaria rapid diagnostic, C-reactive-protein (CRP), and international normalized ratio (INR) tests were also performed. Sepsis severity was clinically measured by Karnofsky and modified early warning signs (MEWS) scores. Anti-TB, broad-spectrum antibiotics, and antimalarial and antifungal agents were prescribed in accordance with Tanzania treatment guideline. An independent t-test and Chi-square or Fisher's exact tests compared means and proportions, respectively. P < 0.05 was statistically significant.

Results

Among 98 patients, 59 (60.2%) were female. Their mean (standard deviation) age was 44 (12.9) years. TB detection increased from 24 (24.5%) by Xpert® MTB/RIF to 36 (36.7%) when LF-LAM was added. In total, 23 (23.5%) patients had other than TB etiologies of sepsis, including Staphylococcus aureus, Streptococcus pneumoniae, Cryptococcus spp., and Plasmodium spp. Twenty-four (94.4%) of 36 patients with TB had higher CRP (≥10 mg/l) compared to 25 (40.3%) non-TB patients (P < 0.001). Nine (9.2%) patients died and almost all had INR ≥1.8 (n = 8), Karnofsky score <50% (n = 9), MEWS score >6 (n = 8), and malnutrition (n = 9).

Conclusions

MTB and other microbes contributed to sepsis in PLHIV. Adding non-TB tests informed clinical decisions. Mortality was predicted by conventional sepsis and severity scoring, malnutrition, and elevated INR.

A Longitudinal, Observational Study of Etiology and Long-Term Outcomes of Sepsis in Malawi Revealing the Key Role of Disseminated Tuberculosis

BACKGROUND

Sepsis protocols in sub-Saharan Africa are typically extrapolated from high-income settings, yet sepsis in sub-Saharan Africa is likely caused by distinct pathogens and may require novel treatment strategies. Data to guide such strategies are lacking. We aimed to define causes and modifiable factors associated with sepsis outcomes in Blantyre, Malawi, in order to inform the design of treatment strategies tailored to sub-Saharan Africa.

METHODS

We recruited 225 adults who met a sepsis case definition defined by fever and organ dysfunction in an observational cohort study at a single tertiary center. Etiology was defined using culture, antigen detection, serology, and polymerase chain reaction. The effect of treatment on 28-day outcomes was assessed using Bayesian logistic regression.

RESULTS

There were 143 of 213 (67%) participants living with human immunodeficiency virus (HIV). We identified a diagnosis in 145 of 225 (64%) participants, most commonly tuberculosis (TB; 34%) followed by invasive bacterial infections (17%), arboviral infections (13%), and malaria (9%). TB was associated with HIV infection, whereas malaria and arboviruses with the absence of HIV infection. Antituberculous chemotherapy was associated with survival (adjusted odds ratio for 28-day death, 0.17; 95% credible interval, 0.05-0.49 for receipt of antituberculous therapy). Of those with confirmed etiology, 83% received the broad-spectrum antibacterial ceftriaxone, but it would be expected to be active in only 24%.

CONCLUSIONS

Sepsis in Blantyre, Malawi, is caused by a range of pathogens; the majority are not susceptible to the broad-spectrum antibacterials that most patients receive. HIV status is a key determinant of etiology. Novel antimicrobial strategies for sepsis tailored to sub-Saharan Africa, including consideration of empiric antituberculous therapy in individuals living with HIV, should be developed and trialed.

Recognising Sepsis as a Health Priority in Sub-Saharan African Country: Learning Lessons from Engagement with Gabon’s Health Policy Stakeholders

Sepsis has been recognised as a global health priority by the United Nations World Health Assembly, which adopted a resolution in 2017 to improve sepsis prevention, diagnosis, and management globally. This study investigated how sepsis is prioritised in Gabon. From May to November 2021, we conducted a qualitative study in healthcare stakeholders at the local, regional, and national levels. Stakeholders included the Ministry of Health (MOH), ethics/regulatory bodies, research institutions, academic institutions, referral hospitals, international funders, and the media. Twenty-three multisectoral stakeholders were interviewed. Respondents indicated that sepsis is not yet prioritised in Gabon due to the lack of evidence of its burden. They also suggest that the researchers should focus on linkages between sepsis and the countries’ existing health sector priorities to accelerate sepsis prioritisation in health policy. Stakeholder awareness and engagement might be accelerated by involving the media in the generation of communication strategies around sepsis awareness and prioritisation. There is a need for local, regional and national evidence to be generated by researchers and taken up by policymakers, focusing on linkages between sepsis and a country’s existing health sector priorities. The MOH should set sepsis reporting structures and develop appropriate sepsis guidelines for identification, management, and prevention.

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.

Improving sepsis care in Africa: an opportunity for change?

Sepsis is common and represents a major public health burden with significant associated morbidity and mortality. However, despite substantial advances in sepsis recognition and management in well-resourced health systems, there remains a distinct lack of research into sepsis in Africa. The lack of evidence affects all levels of healthcare delivery from individual patient management to strategic planning at health-system level. This is particular pertinent as African countries experience some of the highest global burden of sepsis. The 2017 World Health Assembly resolution on sepsis and the creation of the Africa Sepsis Alliance provided an opportunity for change. However, progress so far has been frustratingly slow. The recurrent Ebola virus disease outbreaks and the COVID-19 pandemic on the African continent further reinforce the need for urgent healthcare system strengthening. We recommend that African countries develop national action plans for sepsis which should address the needs of all critically ill patients.

The Association Between Abnormal Vital Signs and Mortality in the Emergency Department

Background

The emergency department (ED) receives patients from all over the world every day. Hence, using various triage scales to detect sick patients and the need for early admission are essential. Triage is a process used in the ED to prioritize patients requiring the most urgent care over those with minor injuries based on medical urgency and medical needs. These decisions may be based on patients’ chief complaints at the time of their ED visit and their vital signs. Vital signs, including blood pressure (BP), respiratory rate (RR), heart rate (HR), and body temperature, are necessary tools that are traditionally used in the ED during procedures such as triage and recognizing high-risk hospital inpatients. This study aimed to determine the relationship between abnormal vital signs and mortality in the ED.

Method and Material

This retrospective record review study was performed at the ED of King Abdulaziz University Hospital (KAUH). Altogether, 641 patients fulfilled our inclusion criteria. Data including patients’ demographics, vital signs, in-hospital mortality, triage level, and precipitating factors were collected.

Results

The mean age of the patients was 45.66 ± 18.43 years (69.3% females), and the majority of them had Canadian Triage and Acuity Scale (CTAS) level 3 (71.1%). The total number of in-hospital mortalities was 32 (5%). Lower systolic blood pressure (SBP) and diastolic blood pressure (DBP), high respiratory rates, and low oxygen saturation (O₂SAT) were significantly associated with high mortality rates.

Conclusion

Abnormal vital signs play a major role in determining patient prognosis and outcomes. Triage score systems should be adjusted and carefully studied in each center according to its population.

Performance Assessment of the Universal Vital Assessment Score vs Other Illness Severity Scores for Predicting Risk of In-Hospital Death Among Adult Febrile Inpatients in Northern Tanzania, 2016-2019

Importance

Severity scores are used to improve triage of hospitalized patients in high-income settings, but the scores may not translate well to low- and middle-income settings such as sub-Saharan Africa.

Objective

To assess the performance of the Universal Vital Assessment (UVA) score, derived in 2017, compared with other illness severity scores for predicting in-hospital mortality among adults with febrile illness in northern Tanzania.

Design, Setting, and Participants

This prognostic study used clinical data collected for the duration of hospitalization among patients with febrile illness admitted to Kilimanjaro Christian Medical Centre or Mawenzi Regional Referral Hospital in Moshi, Tanzania, from September 2016 through May 2019. All adult and pediatric patients with a history of fever within 72 hours or a tympanic temperature of 38.0 °C or higher at screening were eligible for enrollment. Of 3761 eligible participants, 1132 (30.1%) were enrolled in the parent study; of those, 597 adults 18 years or older were included in this analysis. Data were analyzed from December 2019 to September 2021.

Exposures

Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), quick Sequential Organ Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome (SIRS) assessment, and UVA.

Main Outcomes and Measures

The main outcome was in-hospital mortality during the same hospitalization as the participant's enrollment. Crude risk ratios and 95% CIs for in-hospital death were calculated using log-binomial risk regression for proposed score cutoffs for each of the illness severity scores. The area under the receiver operating characteristic curve (AUROC) for estimating the risk of in-hospital death was calculated for each score.

Results

Among 597 participants, the median age was 43 years (IQR, 31-56 years); 300 participants (50.3%) were female, 198 (33.2%) were HIV-infected, and in-hospital death occurred in 55 (9.2%). By higher risk score strata for each score, compared with lower risk strata, risk ratios for in-hospital death were 3.7 (95% CI, 2.2-6.2) for a MEWS of 5 or higher; 2.7 (95% CI, 0.9-7.8) for a NEWS of 5 or 6; 9.6 (95% CI, 4.2-22.2) for a NEWS of 7 or higher; 4.8 (95% CI, 1.2-20.2) for a qSOFA score of 1; 15.4 (95% CI, 3.8-63.1) for a qSOFA score of 2 or higher; 2.5 (95% CI, 1.2-5.2) for a SIRS score of 2 or higher; 9.1 (95% CI, 2.7-30.3) for a UVA score of 2 to 4; and 30.6 (95% CI, 9.6-97.8) for a UVA score of 5 or higher. The AUROCs, using all ordinal values, were 0.85 (95% CI, 0.80-0.90) for the UVA score, 0.81 (95% CI, 0.75-0.87) for the NEWS, 0.75 (95% CI, 0.69-0.82) for the MEWS, 0.73 (95% CI, 0.67-0.79) for the qSOFA score, and 0.63 (95% CI, 0.56-0.71) for the SIRS score. The AUROC for the UVA score was significantly greater than that for all other scores (P < .05 for all comparisons) except for NEWS (P = .08).

Conclusions and Relevance

This prognostic study found that the NEWS and the UVA score performed favorably compared with other illness severity scores in predicting in-hospital mortality among a hospitalized cohort of adults with febrile illness in northern Tanzania. Given its reliance on readily available clinical data, the UVA score may have utility in the triage and prognostication of patients admitted to the hospital with febrile illness in low- to middle-income settings such as sub-Saharan Africa.

Sensitivity and specificity of a quick sequential [Sepsis-Related] organ failure assessment sepsis screening tool

AIM

There is limited evidence on the diagnostic accuracy of a quick Sequential [Sepsis-Related] Organ Failure Assessment (qSOFA) sepsis screening (SS) tool in developing nation health settings. The aim of this study was to test the diagnostic accuracy of a qSOFA-based SS tool, and the predictive validity of the qSOFA score in hospital ward patients from Argentina.

METHODS

Prospective observational study. Patients (≥18 years, without sepsis) were recruited within 24-48 hours of admission to a 169-bed tertiary referral private hospital in Buenos Aires. The index test was the qSOFA-based SS tool, and the reference standard sepsis diagnosed at discharge blindly evaluated with reference to the Sepsis-3.

RESULTS

In 1151 patients (median age 69.9 [IQR, 29.0]); 47 (4.1%) had sepsis, 413 (35.9%) had infection and 691 (60.0%) other diagnoses at discharge. The qSOFA-based SS tool (index test) had moderate sensitivity (60%), good specificity (89%), a very low positive (19%) and very high negative (98%) predictive value for sepsis diagnosed at discharge according to the Sepsis-3 criteria (reference standard). For the same outcome, the qSOFA score in isolation had a reasonable predictive validity area under receiver operating characteristics curve 0.77 (95% CI 0.70-0.83) P < 0.001.

CONCLUSION

The qSOFA score could reasonably discriminate patients at risk of developing sepsis; qSOFA-based screening may be valuable where no screening criteria are in place.

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).

Trends in fever case management for febrile inpatients in a low malaria incidence setting of Tanzania

OBJECTIVES

In 2010, WHO published guidelines emphasising parasitological confirmation of malaria before treatment. We present data on changes in fever case management in a low malaria transmission setting of northern Tanzania after 2010.

METHODS

We compared diagnoses, treatments and outcomes from two hospital-based prospective cohort studies, Cohort 1 (2011-2014) and Cohort 2 (2016-2019), that enrolled febrile children and adults. All participants underwent quality-assured malaria blood smear-microscopy. Participants who were malaria smear-microscopy negative but received a diagnosis of malaria or received an antimalarial were categorised as malaria over-diagnosis and over-treatment, respectively.

RESULTS

We analysed data from 2098 participants. The median (IQR) age was 27 (3-43) years and 1047 (50.0%) were female. Malaria was detected in 23 (2.3%) participants in Cohort 1 and 42 (3.8%) in Cohort 2 (p = 0.059). Malaria over-diagnosis occurred in 334 (35.0%) participants in Cohort 1 and 190 (17.7%) in Cohort 2 (p < 0.001). Malaria over-treatment occurred in 528 (55.1%) participants in Cohort 1 and 196 (18.3%) in Cohort 2 (p < 0.001). There were 30 (3.1%) deaths in Cohort 1 and 60 (5.4%) in Cohort 2 (p = 0.007). All deaths occurred among smear-negative participants.

CONCLUSION

We observed a substantial decline in malaria over-diagnosis and over-treatment among febrile inpatients in northern Tanzania between two time periods after 2010. Despite changes, some smear-negative participants were still diagnosed and treated for malaria. Our results highlight the need for continued monitoring of fever case management across different malaria epidemiological settings in sub-Saharan Africa.

Derivation and Validation of a Risk Score to Predict Mortality of Early Neonates at Neonatal Intensive Care Unit: The END in NICU Score

BACKGROUND

Early neonatal death is death of infants in the first week of life. And 34% to 92% of neonatal deaths happen within 7 days of postnatal period. Thus, the early neonatal period is the most critical time for an infant, requiring different strategies to prevent mortality. Among strategies, deriving and implementing early warning scores is crucial to predict early neonatal mortality earlier upon hospital admission.

OBJECTIVE

To derive and validate a risk score to predict mortality of early neonates at Felege Hiwot Specialized Hospital neonatal intensive care unit, Bahir Dar, 2021.

METHODS

The document review was conducted from February 24, to April 08, 2021, on all early neonates admitted to neonatal intensive care unit from January 1, 2018 to December 31, 2020. The total number of early neonates included in the derivation study was 1100. Data were collected by using checklists prepared on EpiCollect5 software. After exporting the data to R version 4.0.5 software, variables with (p < 0.25) from the simple binary regression were entered into a multiple logistic regression model, and significant variables (p < 0.05) were kept in the model. The discrimination and calibration were assessed. The model was internally validated using bootstrapping technique.

RESULTS

Admission weight, birth Apgar score, perinatal asphyxia, respiratory distress syndrome, mode of delivery, sepsis, and gestational age at birth remained in the final multiple logistic regression prediction model. The area under curve of receiver operating characteristic curve for early neonatal mortality score was 90.7%. The model retained excellent discrimination under internal validation. The sensitivity, specificity, and positive predictive value, negative predictive value of the model was 89.4%, 82.5%, 55.5%, and 96.9%, respectively.

CONCLUSION

The derived score has an excellent discriminative ability and good prediction performance. This is an important tool for predicting early neonatal mortality in neonatal intensive care units at admission.

Acute Kidney Injury and Associated Factors in Intensive Care Units at a Tertiary Hospital in Northern Tanzania

Background

Acute kidney injury (AKI) is a recognized complication in critically ill patients. The epidemiology of AKI varies worldwide, depending on the diagnostic criteria used and the setting. The International Society of Nephrology has called for a reduction in preventable deaths from AKI to zero by the year 2025. It is suspected that the majority of AKI cases are in limited-resource countries, but the true burden of AKI in these settings remains unknown.

Objective

We aimed to determine, using standardized KDIGO (Kidney Disease Improving Global Outcomes) criteria, the prevalence of AKI, associated factors, and clinical characteristics of adult (≥18 years) patients admitted to intensive care units (ICUs) at a tertiary hospital in Tanzania.

Design

Prospective observational study from November 2017 to May 2018.

Methods

In all, 320 patients admitted to medical and surgical ICUs were consecutively enrolled. Baseline, clinical, and laboratory data were collected on admission and during their ICU stay. Serum creatinine and urine output were measured, and KDIGO criteria were used to determine AKI status.

Results

More than half (55.3%) of ICU patients were diagnosed with AKI. Of these, 80% were diagnosed within 24 hours of admission. Acute kidney injury stage 3 accounted for 35% of patients with AKI. Patients with AKI were older, more likely to have cardiovascular comorbidities, and with higher baseline serum levels of creatinine, potassium, universal vital assessment admission scores, and total white cell count ≥12. Sepsis (odds ratio [OR] = 3.81; confidence interval [CI] = 1.21-11.99), diabetes (OR = 2.54; CI = 1.24-5.17), and use of vasopressors (OR = 3.78; CI = 1.36-10.54) were independently associated with AKI in multivariable logistic regression. Less than one-third of those who needed dialysis received it. There was 100% mortality in those who needed dialysis but did not receive (n = 19).

Limitations

Being based at a referral center, the findings do not represent the true burden of AKI in the community.

Conclusion

The prevalence of AKI was very high in ICUs in Northern Tanzania. The majority of patients presented with AKI and were severely ill, suggesting late presentation, underscoring the importance of prioritizing prevention and early intervention. Further studies should explore locally suitable AKI risk scores that could be used to identify high-risk patients in the community health centers from where patients are referred.

Sepsis in two hospitals in Rwanda: A retrospective cohort study of presentation, management, outcomes, and predictors of mortality

Purpose

Few studies have assessed the presentation, management, and outcomes of sepsis in low-income countries (LICs). We sought to characterize these aspects of sepsis and to assess mortality predictors in sepsis in two referral hospitals in Rwanda.

Materials and methods

This was a retrospective cohort study in two public academic referral hospitals in Rwanda. Data was abstracted from paper medical records of adult patients who met our criteria for sepsis.

Results

Of the 181 subjects who met eligibility criteria, 111 (61.3%) met our criteria for sepsis without shock and 70 (38.7%) met our criteria for septic shock. Thirty-five subjects (19.3%) were known to be HIV positive. The vast majority of septic patients (92.7%) received intravenous fluid therapy (median = 1.0 L within 8 hours), and 94.0% received antimicrobials. Vasopressors were administered to 32.0% of the cohort and 46.4% received mechanical ventilation. In-hospital mortality for all patients with sepsis was 51.4%, and it was 82.9% for those with septic shock. Baseline characteristic mortality predictors were respiratory rate, Glasgow Coma Scale score, and known HIV seropositivity.

Conclusions

Septic patients in two public tertiary referral hospitals in Rwanda are young (median age = 40, IQR = 29, 59) and experience high rates of mortality. Predictors of mortality included baseline clinical characteristics and HIV seropositivity status. The majority of subjects were treated with intravenous fluids and antimicrobials. Further work is needed to understand clinical and management factors that may help improve mortality in septic patients in LICs.

Population Incidence and Mortality of Sepsis in an Urban African Setting, 2013-2016

BACKGROUND

Sepsis is an important cause of mortality globally, although population incidence estimates from low-income settings, including sub-Saharan Africa, are absent. We aimed to estimate sepsis incidence burden using routinely available data from a large urban hospital in Malawi.

METHODS

We linked routine-care databases at Queen Elizabeth Central Hospital, Blantyre, Malawi, to provide admission and discharge data for 217 149 adults from 2013-2016. Using a definition of sepsis based on systemic inflammatory response syndrome criteria and Blantyre census population data, we calculated population incidence estimates of sepsis and severe sepsis and used negative binomial regression to assess for trends over time. Missing data were multiply imputed with chained equations.

RESULTS

We estimate that the incidence rate of emergency department-attending sepsis and severe sepsis in adults was 1772 per 100 000 person-years (95% confidence interval [CI], 1754-1789) and 303 per 100 000 person-years (95% CI, 295-310), respectively, between 2013 and 2016, with a year-on-year decrease in incidence. In-hospital mortality for patients admitted to the hospital with sepsis and severe sepsis was 23.7% (95% CI, 22.7-24.7%) and 28.1% (95% CI, 26.1 - 30.0%), respectively, with no clear change over time.

CONCLUSIONS

Sepsis incidence is higher in Blantyre, Malawi, than in high-income settings, from where the majority of sepsis incidence data are derived. Worldwide sepsis burden is likely to be underestimated, and data from low-income countries are needed to inform the public health response.

Risk factors for delirium among hospitalized patients in Zambia

Objective

To identify risk factors for delirium among hospitalized patients in Zambia.

Methods

We conducted a prospective cohort study at the University Teaching Hospital in Lusaka, Zambia, from October 2017 to April 2018. We report associations of exposures including sociodemographic and clinical factors with delirium over the first three days of hospital admission, assessed using a modified Brief Confusion Assessment Method (bCAM).

Findings

749 patients were included for analysis (mean age, 42.9 years; 64.8% men; 47.3% with HIV). In individual regression analyses of potential delirium risk factors adjusted for age, sex and education, factors significantly associated with delirium included being divorced/widowed (OR 1.64, 95% CI 1.09–2.47), lowest tercile income (OR 1.58, 95% CI 1.04–2.40), informal employment (OR 1.97, 95% CI 1.25–3.15), untreated HIV infection (OR 2.18, 95% CI 1.21–4.06), unknown HIV status (OR 2.90, 95% CI 1.47–6.16), history of stroke (OR 2.70, 95% CI 1.15–7.19), depression/anxiety (OR 1.52, 95% CI 1.08–2.14), alcohol overuse (OR 1.96, 95% CI 1.39–2.79), sedatives ordered on admission (OR 3.77, 95% CI 1.70–9.54), severity of illness (OR 2.00, 95% CI 1.82–2.22), neurological (OR 7.66, 95% CI 4.90–12.24) and pulmonary-system admission diagnoses (OR 1.91, 95% CI 1.29–2.85), and sepsis (OR 2.44, 95% CI 1.51–4.08). After combining significant risk factors into a multivariable regression analysis, severity of illness, history of stroke, and being divorced/widowed remained predictive of delirium (p<0.05).

Conclusion

Among hospitalized adults at a national referral hospital in Zambia, severity of illness, history of stroke, and being divorced/widowed were independently predictive of delirium. Extension of this work will inform future efforts to prevent, detect, and manage delirium in low- and middle-income countries.

A 2-Biomarker Model Augments Clinical Prediction of Mortality in Melioidosis

BACKGROUND

Melioidosis, infection caused by Burkholderia pseudomallei, is a common cause of sepsis with high associated mortality in Southeast Asia. Identification of patients at high likelihood of clinical deterioration is important for guiding decisions about resource allocation and management. We sought to develop a biomarker-based model for 28-day mortality prediction in melioidosis.

METHODS

In a derivation set (N = 113) of prospectively enrolled, hospitalized Thai patients with melioidosis, we measured concentrations of interferon-γ, interleukin-1β, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-ɑ, granulocyte-colony stimulating factor, and interleukin-17A. We used least absolute shrinkage and selection operator (LASSO) regression to identify a subset of predictive biomarkers and performed logistic regression and receiver operating characteristic curve analysis to evaluate biomarker-based prediction of 28-day mortality compared with clinical variables. We repeated select analyses in an internal validation set (N = 78) and in a prospectively enrolled external validation set (N = 161) of hospitalized adults with melioidosis.

RESULTS

All 8 cytokines were positively associated with 28-day mortality. Of these, interleukin-6 and interleukin-8 were selected by LASSO regression. A model consisting of interleukin-6, interleukin-8, and clinical variables significantly improved 28-day mortality prediction over a model of only clinical variables [AUC (95% confidence interval [CI]): 0.86 (.79-.92) vs 0.78 (.69-.87); P = .01]. In both the internal validation set (0.91 [0.84-0.97]) and the external validation set (0.81 [0.74-0.88]), the combined model including biomarkers significantly improved 28-day mortality prediction over a model limited to clinical variables.

CONCLUSIONS

A 2-biomarker model augments clinical prediction of 28-day mortality in melioidosis.

Disposition Decision Support by Laboratory Based Outcome Prediction

Disposition is one of the main tasks in the emergency department. However, there is a lack of objective and reliable disposition criteria, and diagnosis-based risk prediction is not feasible at early time points. The aim was to derive a risk score (TRIAL) based on routinely collected baseline (TRIage level and Age) and Laboratory data—supporting disposition decisions by risk stratification based on mortality. We prospectively included consecutive patients presenting to the emergency department over 18 weeks. Data sets of routinely collected baseline (triage level and age) and laboratory data were used for multivariable logistic regression to develop the TRIAL risk score predicting mortality. Routine laboratory variables and disposition cut-offs were chosen beforehand by expert consensus. Risk stratification was based on low risk (<1%), intermediate risk (1–10%), and high risk (>10%) of in-hospital mortality. In total, 8687 data sets were analyzed. Variables identified to develop the TRIAL risk score were triage level (Emergency Severity Index), age, lactate dehydrogenase, creatinine, albumin, bilirubin, and leukocyte count. The area under the ROC curve for in-hospital mortality was 0.93. Stratification according to the TRIAL score showed that 67.5% of all patients were in the low-risk category. Mortality was 0.1% in low-risk, 3.5% in intermediate-risk, and 26.2% in high-risk patients. The TRIAL risk score based on routinely available baseline and laboratory data provides prognostic information for disposition decisions. TRIAL could be used to minimize admission in low-risk and to maximize observation in high-risk patients.

Delirium as a predictor of mortality and disability among hospitalized patients in Zambia

OBJECTIVE

To study the epidemiology and outcomes of delirium among hospitalized patients in Zambia.

METHODS

We conducted a prospective cohort study at the University Teaching Hospital in Lusaka, Zambia, from October 2017 to April 2018. The primary exposure was delirium duration over the initial 3 days of hospitalization, assessed daily using the Brief Confusion Assessment Method. The primary outcome was 6-month mortality. Secondary outcomes included 6-month disability, evaluated using the World Health Organization Disability Assessment Schedule 2.0.

FINDINGS

711 adults were included (median age, 39 years; 461 men; 459 medical, 252 surgical; 323 with HIV). Delirium prevalence was 48.5% (95% CI, 44.8%-52.3%). 6-month mortality was higher for delirious participants (44.6% [39.3%-50.1%]) versus non-delirious participants (20.0% [15.4%-25.2%]; P < .001). After adjusting for covariates, delirium duration independently predicted 6-month mortality and disability with a significant dose-response association between number of days with delirium and odds of worse clinical outcome. Compared to no delirium, presence of 1, 2 or 3 days of delirium resulted in odds ratios for 6-month mortality of 1.43 (95% CI, 0.73-2.80), 2.20 (1.07-4.51), and 3.92 (2.24-6.87), respectively (P < .001). Odds of 6-month disability were 1.20 (0.70-2.05), 1.73 (0.95-3.17), and 2.80 (1.78-4.43), respectively (P < .001).

CONCLUSION

Among hospitalized medical and surgical patients in Zambia, delirium prevalence was high and delirium duration independently predicted mortality and disability at 6 months. This work lays the foundation for prevention, detection, and management of delirium in low-income countries. Long-term follow up of outcomes of critical illness in resource-limited settings appears feasible using the WHO Disability Assessment Schedule.

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.

The comparative ability of commonly used disease severity scores to predict death or a requirement for ICU care in patients hospitalised with possible sepsis in Yangon, Myanmar

OBJECTIVES

To determine the comparative prognostic utility of commonly used disease prediction scores in adults with presumed community-acquired sepsis in a resource-limited tropical setting.

METHODS

This prospective, observational study was performed on the medical ward of a tertiary-referral hospital in Yangon, Myanmar. The ability of the National Early Warning Score 2 (NEWS2), quick NEWS (qNEWS), quick Sequential Organ Failure Assessment (qSOFA) score, Universal Vital Assessment (UVA) and Sequential Organ Failure Assessment (SOFA) scores to predict a complicated inpatient course (death or requirement for intensive care unit (ICU) support) in patients with two or more systemic inflammatory response syndrome criteria was determined.

RESULTS

Among the 509 patients, 30 (6%) were HIV-seropositive. The most commonly confirmed diagnoses were tuberculosis (30/509, 5.9%) and measles (26/509, 5.1%). Overall, 75/509 (14.7%) died or required ICU support. All the scores except the qSOFA score, which was inferior, had a similar ability to predict a complicated inpatient course.

CONCLUSIONS

In this resource-limited tropical setting, disease severity scores calculated at presentation using only vital signs-such as the NEWS2 score-identified high-risk sepsis patient as well as the SOFA score, which is calculated at 24 h and which also requires laboratory data. Use of these simple clinical scores can be used to facilitate recognition of the high-risk patient and to optimise the use of finite resources.

Defining High-risk Emergency Chief Complaints: Data-driven Triage for Low- and Middle-income Countries

OBJECTIVES

Emergency medicine in low- and middle-income countries (LMICs) is hindered by lack of research into patient outcomes. Chief complaints (CCs) are fundamental to emergency care but have only recently been uniquely codified for an LMIC setting in Uganda. It is not known whether CCs independently predict emergency unit patient outcomes.

METHODS

Patient data collected in a Ugandan emergency unit between 2009 and 2018 were randomized into validation and derivation data sets. A recursive partitioning algorithm stratified CCs by 3-day mortality risk in each group. The process was repeated in 10,000 bootstrap samples to create an averaged risk ranking. Based on this ranking, CCs were categorized as "high-risk" (>2× baseline mortality), "medium-risk" (between 2 and 0.5× baseline mortality), and "low-risk" (<0.5× baseline mortality). Risk categories were then included in a logistic regression model to determine if CCs independently predicted 3-day mortality.

RESULTS

Overall, the derivation data set included 21,953 individuals with 7,313 in the validation data set. In total, 43 complaints were categorized, and 12 CCs were identified as high-risk. When controlled for triage data including age, sex, HIV status, vital signs, level of consciousness, and number of complaints, high-risk CCs significantly increased 3-day mortality odds ratio (OR = 2.39, 95% confidence interval [CI] = 1.95 to 2.93, p < 0.001) while low-risk CCs significantly decreased 3-day mortality odds (OR = 0.16, 95% CI = 0.09 to 0.29, p < 0.001).

CONCLUSIONS

High-risk CCs were identified and found to predict increased 3-day mortality independent of vital signs and other data available at triage. This list can be used to expand local triage systems and inform emergency training programs. The methodology can be reproduced in other LMIC settings to reflect their local disease patterns.

Establishment of a high-dependency unit in Malawi

Adults admitted to hospital with critical illness are vulnerable and at high risk of morbidity and mortality, especially in sub-Saharan African settings where resources are severely limited. As life expectancy increases, patient demographics and healthcare needs are increasingly complex and require integrated approaches. Patient outcomes could be improved by increased critical care provision that standardises healthcare delivery, provides specialist staff and enhanced patient monitoring and facilitates some treatment modalities for organ support. In Malawi, we established a new high-dependency unit within Queen Elizabeth Central Hospital, a tertiary referral centre serving the country's Southern region. This unit was designed in partnership with managers, clinicians, nurses and patients to address their needs. In this practice piece, we describe a participatory approach to design and implement a sustainable high-dependency unit for a low-income sub-Saharan African setting. This included: prospective agreement on remit, alignment with existing services, refurbishment of a dedicated physical space, recruitment and training of specialist nurses, development of context-sensitive clinical standard operating procedures, purchase of appropriate and durable equipment and creation of digital clinical information systems. As the global COVID-19 pandemic unfolded, we accelerated unit opening in anticipation of increased clinical requirement and describe how the high-dependency unit responded to this demand.

Management of intra-abdominal-infections: 2017 World Society of Emergency Surgery guidelines summary focused on remote areas and low-income nations

BACKGROUND

Most remote areas have restricted access to healthcare services and are too small and remote to sustain specialist services. In 2017, the World Society of Emergency Surgery (WSES) published guidelines for the management of intra-abdominal infections. Many hospitals, especially those in remote areas, continue to face logistical barriers, leading to an overall poorer adherence to international guidelines.

METHODS

The aim of this paper is to report and amend the 2017 WSES guidelines for the management of intra-abdominal infections, extending these recommendations for remote areas and low-income countries. A literature search of the PubMed/MEDLINE databases was conducted covering the period up until June 2020.

RESULTS

The critical shortages of healthcare workers and material resources in remote areas require the use of a robust triage system. A combination of abdominal signs and symptoms with early warning signs may be used to screen patients needing immediate acute care surgery. A tailored diagnostic step-up approach based on the hospital's resources is recommended. Ultrasound and plain X-ray may be useful diagnostic tools in remote areas. The source of infection should be totally controlled as soon as possible.

CONCLUSIONS

The cornerstones of effective treatment for intra-abdominal infections in remote areas include early diagnosis, prompt resuscitation, early source control, and appropriate antimicrobial therapy. Standardization in applying the guidelines is mandatory to adequately manage intra-abdominal infections.

Febrile Illness Evaluation in a Broad Range of Endemicities (FIEBRE): protocol for a multisite prospective observational study of the causes of fever in Africa and Asia

INTRODUCTION

Fever commonly leads to healthcare seeking and hospital admission in sub-Saharan Africa and Asia. There is only limited guidance for clinicians managing non-malarial fevers, which often results in inappropriate treatment for patients. Furthermore, there is little evidence for estimates of disease burden, or to guide empirical therapy, control measures, resource allocation, prioritisation of clinical diagnostics or antimicrobial stewardship. The Febrile Illness Evaluation in a Broad Range of Endemicities (FIEBRE) study seeks to address these information gaps.

METHODS AND ANALYSIS

FIEBRE investigates febrile illness in paediatric and adult outpatients and inpatients using standardised clinical, laboratory and social science protocols over a minimum 12-month period at five sites in sub-Saharan Africa and Southeastern and Southern Asia. Patients presenting with fever are enrolled and provide clinical data, pharyngeal swabs and a venous blood sample; selected participants also provide a urine sample. Laboratory assessments target infections that are treatable and/or preventable. Selected point-of-care tests, as well as blood and urine cultures and antimicrobial susceptibility testing, are performed on site. On day 28, patients provide a second venous blood sample for serology and information on clinical outcome. Further diagnostic assays are performed at international reference laboratories. Blood and pharyngeal samples from matched community controls enable calculation of AFs, and surveys of treatment seeking allow estimation of the incidence of common infections. Additional assays detect markers that may differentiate bacterial from non-bacterial causes of illness and/or prognosticate illness severity. Social science research on antimicrobial use will inform future recommendations for fever case management. Residual samples from participants are stored for future use.

ETHICS AND DISSEMINATION

Ethics approval was obtained from all relevant institutional and national committees; written informed consent is obtained from all participants or parents/guardians. Final results will be shared with participating communities, and in open-access journals and other scientific fora. Study documents are available online (https://doi.org/10.17037/PUBS.04652739).

sTREM-1 predicts mortality in hospitalized patients with infection in a tropical, middle-income country

BACKGROUND

Few studies of biomarkers as predictors of outcome in infection have been performed in tropical, low- and middle-income countries where the burden of sepsis is highest. We evaluated whether selected biomarkers could predict 28-day mortality in infected patients in rural Thailand.

METHODS

Four thousand nine hundred eighty-nine adult patients admitted with suspected infection to a referral hospital in northeast Thailand were prospectively enrolled within 24 h of admission. In a secondary analysis of 760 patients, interleukin-8 (IL-8), soluble tumor necrosis factor receptor 1 (sTNFR-1), angiopoietin-1 (Ang-1), angiopoietin-2 (Ang-2), and soluble triggering receptor expressed by myeloid cells 1 (sTREM-1) were measured in the plasma. Association with 28-day mortality was evaluated using regression; a parsimonious biomarker model was selected using the least absolute shrinkage and selection operator (LASSO) method. Discrimination of mortality was assessed by receiver operating characteristic curve analysis and verified by multiple methods.

RESULTS

IL-8, sTNFR-1, Ang-2, and sTREM-1 concentrations were strongly associated with death. LASSO identified a three-biomarker model of sTREM-1, Ang-2, and IL-8, but sTREM-1 alone provided comparable mortality discrimination (p = 0.07). sTREM-1 alone was comparable to a model of clinical variables (area under receiver operating characteristic curve [AUC] 0.81, 95% confidence interval [CI] 0.77-0.85 vs AUC 0.79, 95% CI 0.74-0.84; p = 0.43). The combination of sTREM-1 and clinical variables yielded greater mortality discrimination than clinical variables alone (AUC 0.83, 95% CI 0.79-0.87; p = 0.004).

CONCLUSIONS

sTREM-1 predicts mortality from infection in a tropical, middle-income country comparably to a model derived from clinical variables and, when combined with clinical variables, can further augment mortality prediction.

TRIAL REGISTRATION

The Ubon-sepsis study was registered on ClinicalTrials.gov ( NCT02217592 ), 2014.

Early warning scores for detecting deterioration in adult hospital patients: systematic review and critical appraisal of methodology

OBJECTIVE

To provide an overview and critical appraisal of early warning scores for adult hospital patients.

DESIGN

Systematic review.

DATA SOURCES

Medline, CINAHL, PsycInfo, and Embase until June 2019.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Studies describing the development or external validation of an early warning score for adult hospital inpatients.

RESULTS

13 171 references were screened and 95 articles were included in the review. 11 studies were development only, 23 were development and external validation, and 61 were external validation only. Most early warning scores were developed for use in the United States (n=13/34, 38%) and the United Kingdom (n=10/34, 29%). Death was the most frequent prediction outcome for development studies (n=10/23, 44%) and validation studies (n=66/84, 79%), with different time horizons (the most frequent was 24 hours). The most common predictors were respiratory rate (n=30/34, 88%), heart rate (n=28/34, 83%), oxygen saturation, temperature, and systolic blood pressure (all n=24/34, 71%). Age (n=13/34, 38%) and sex (n=3/34, 9%) were less frequently included. Key details of the analysis populations were often not reported in development studies (n=12/29, 41%) or validation studies (n=33/84, 39%). Small sample sizes and insufficient numbers of event patients were common in model development and external validation studies. Missing data were often discarded, with just one study using multiple imputation. Only nine of the early warning scores that were developed were presented in sufficient detail to allow individualised risk prediction. Internal validation was carried out in 19 studies, but recommended approaches such as bootstrapping or cross validation were rarely used (n=4/19, 22%). Model performance was frequently assessed using discrimination (development n=18/22, 82%; validation n=69/84, 82%), while calibration was seldom assessed (validation n=13/84, 15%). All included studies were rated at high risk of bias.

CONCLUSIONS

Early warning scores are widely used prediction models that are often mandated in daily clinical practice to identify early clinical deterioration in hospital patients. However, many early warning scores in clinical use were found to have methodological weaknesses. Early warning scores might not perform as well as expected and therefore they could have a detrimental effect on patient care. Future work should focus on following recommended approaches for developing and evaluating early warning scores, and investigating the impact and safety of using these scores in clinical practice.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017053324.

Derivation and validation of a prognostic score for neonatal mortality in Ethiopia: a case-control study

Background

Early warning scores for neonatal mortality have not been designed for low income countries. We developed and validated a score to predict mortality upon admission to a NICU in Ethiopia.

Methods

We conducted a retrospective case-control study at the University of Gondar Hospital, Gondar, Ethiopia. Neonates hospitalized in the NICU between January 1, 2016 to June 31, 2017. Cases were neonates who died and controls were neonates who survived.

Results

Univariate logistic regression identified variables associated with mortality. The final model was developed with stepwise logistic regression. We created the Neonatal Mortality Score, which ranged from 0 to 52, from the model’s coefficients. Bootstrap analysis internally validated the model. The discrimination and calibration were calculated. In the derivation dataset, there were 207 cases and 605 controls. Variables associated with mortality were admission level of consciousness, admission respiratory distress, gestational age, and birthweight. The AUC for neonatal mortality using these variables in aggregate was 0.88 (95% CI 0.85–0.91). The model achieved excellent discrimination (bias-corrected AUC) under internal validation. Using a cut-off of 12, the sensitivity and specificity of the Neonatal Mortality Score was 81 and 80%, respectively. The AUC for the Neonatal Mortality Score was 0.88 (95% CI 0.85–0.91), with similar bias-corrected AUC. In the validation dataset, there were 124 cases and 122 controls, the final model and the Neonatal Mortality Score had similar discrimination and calibration.

Conclusions

We developed, internally validated, and externally validated a score that predicts neonatal mortality upon NICU admission with excellent discrimination and calibration.

Development and validation of early warning score system: A systematic literature review

OBJECTIVES

This review aims to: 1) evaluate the quality of model reporting, 2) provide an overview of methodology for developing and validating Early Warning Score Systems (EWSs) for adult patients in acute care settings, and 3) highlight the strengths and limitations of the methodologies, as well as identify future directions for EWS derivation and validation studies.

METHODOLOGY

A systematic search was conducted in PubMed, Cochrane Library, and CINAHL. Only peer reviewed articles and clinical guidelines regarding developing and validating EWSs for adult patients in acute care settings were included. 615 articles were extracted and reviewed by five of the authors. Selected studies were evaluated based on the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist. The studies were analyzed according to their study design, predictor selection, outcome measurement, methodology of modeling, and validation strategy.

RESULTS

A total of 29 articles were included in the final analysis. Twenty-six articles reported on the development and validation of a new EWS, while three reported on validation and model modification. Only eight studies met more than 75% of the items in the TRIPOD checklist. Three major techniques were utilized among the studies to inform their predictive algorithms: 1) clinical-consensus models (n = 6), 2) regression models (n = 15), and 3) tree models (n = 5). The number of predictors included in the EWSs varied from 3 to 72 with a median of seven. Twenty-eight models included vital signs, while 11 included lab data. Pulse oximetry, mental status, and other variables extracted from electronic health records (EHRs) were among other frequently used predictors. In-hospital mortality, unplanned transfer to the intensive care unit (ICU), and cardiac arrest were commonly used clinical outcomes. Twenty-eight studies conducted a form of model validation either within the study or against other widely-used EWSs. Only three studies validated their model using an external database separate from the derived database.

CONCLUSION

This literature review demonstrates that the characteristics of the cohort, predictors, and outcome selection, as well as the metrics for model validation, vary greatly across EWS studies. There is no consensus on the optimal strategy for developing such algorithms since data-driven models with acceptable predictive accuracy are often site-specific. A standardized checklist for clinical prediction model reporting exists, but few studies have included reporting aligned with it in their publications. Data-driven models are subjected to biases in the use of EHR data, thus it is particularly important to provide detailed study protocols and acknowledge, leverage, or reduce potential biases of the data used for EWS development to improve transparency and generalizability.

Vital Signs Data and Probability of Hospitalization, Transfer to Another Facility, or Emergency Department Death Among Adults Presenting for Medical Illnesses to the Emergency Department at a Large Urban Hospital in the United States

BACKGROUND

Vital signs are routinely measured from patients presenting to the emergency department (ED), but how they predict clinical outcomes like hospitalization is unclear.

OBJECTIVES

To evaluate how pulse, respiratory rate, temperature, and mean arterial pressure (MAP) at ED presentation predicted probability of hospitalization, transfer to another center, or death in the ED (as a composite outcome) vs. other ED dispositions (discharged, eloped, and sent to observation or labor and delivery), and to assess the performance of different modeling strategies, specifically, models including flexible forms of vital signs (as restricted cubic splines) vs. linear forms (untransformed numeric variables) vs. binary transformations (vital signs values categorized simply as normal or abnormal).

METHODS

We analyzed the data of 12,660 adults presenting for medical illnesses to the ED at the University of California, San Francisco Medical Center, San Francisco, California, throughout 2014. We used flexible forms of vital signs data at presentation (pulse, temperature, respiratory rate, and MAP) to predict ED disposition (admitted, transferred, or died, vs. other ED dispositions) and to guide binary transformation of vital signs. We compared performance of models including vital signs as flexible terms, binary transformations, or linear terms.

RESULTS

A model including flexible forms of vital signs and age to predict the outcome had good calibration and moderate discrimination (C-statistic = 71.2, 95% confidence interval [CI] 70.0-72.4). Binary transformation of vital signs had minimal impact on performance (C-statistic = 71.3, 95% CI 70.2-72.5). A model with linear forms was less calibrated and had slightly reduced discrimination (C-statistic = 70.3, 95% CI 69.1-71.5).

CONCLUSIONS

Findings suggest that flexible modeling of vital signs may better reflect their association with clinical outcomes. Future studies to evaluate how vital signs could assist clinical decision-making in acute care settings are suggested.

Do different patient populations need different early warning scores? The performance of nine different early warning scores used on acutely ill patients admitted to a low-resource hospital in sub-Saharan Africa

BACKGROUND

Early warning scores (EWS) generated in a developed healthcare setting may not perform as well in low-resource settings in sub-Saharan Africa.

METHOD

The performance of EWS used in developed world was compared with those generated in low-resource settings in sub-Saharan Africa.

RESULTS

When tested on 1,266 acutely ill patients consecutively admitted to a low-resource Ugandan hospital there was no statistical difference in the performance of any of the EWS tested. The performance of all the scores appeared to be improved by the addition of mobility assessment. Although statistically insignificant, the National Early Warning Score with extra points added for impaired mobility had the highest discrimination and sensitivity.

CONCLUSION

There were only marginal and no statistical differences in the performance of EWS generated in low- and high-resource healthcare settings in a cohort of unselected acutely ill medical patients admitted to a low-resource hospital in sub-Saharan Africa.

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.