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Early warning scores (EWS) are widely used in well-resourced healthcare settings to identify patients at risk of mortality. The Modified Early Warning Score (MEWS) is a well-known EWS used comprehensively in the United Kingdom. The HOTEL score (Hypotension, Oxygen saturation, Temperature, ECG abnormality, Loss of independence) was developed and tested in a European cohort; however, its validity is unknown in resource limited settings. This study compared the performance of both scores and suggested modifications to enhance accuracy. A prospective cohort study of adults (≥18 yrs) admitted to medical wards at a Malawian hospital. Primary outcome was mortality within three days. Performance of MEWS and HOTEL were assessed using ROC analysis. Logistic regression analysis identified important predictors of mortality and from this a new score was defined. Three-hundred-and-two patients were included. Fifty-one (16.9%) died within three days of admission. With a cut-point ≥2, the HOTEL score had sensitivity 70.6% (95% CI: 56.2 to 82.5) and specificity 59.4% (95% CI: 53.0 to 65.5), and was superior to MEWS (cut-point ≥5); sensitivity: 58.8% (95% CI: 44.2 to 72.4), specificity: 56.2% (95% CI: 49.8 to 62.4). The new score, dubbed TOTAL (Tachypnoea, Oxygen saturation, Temperature, Alert, Loss of independence), showed slight improvement with a cut-point ≥2; sensitivity 76.5% (95% CI: 62.5 to 87.2) and specificity 67.3% (95% CI: 61.1 to 73.1). Using an EWS generated in developed healthcare systems in resource limited settings results in loss of sensitivity and specificity. A score based on predictors of mortality specific to the Malawian population showed enhanced accuracy but not enough to warrant clinical use. Despite an assumption of common physiological responses, disease and population differences seem to strongly determine the performance of EWS. Local validation and impact assessment of these scores should precede their adoption in resource limited settings.

Generalized linear models were used to compare colonization positivity, duration of colonization, and AUC bacterial density, with generalized estimating equations used for comparison at multiple time points. Among pneumococcal-colonized individuals, the AUC of colonization density was higher in the LAIV group than in the control group, with borderline statistical significance at Days 2-14 (P = 0.05), and reached statistical significance after exclusion of participants who had nasal-swab PCR evidence of concurrent wild-type viral illness (three influenza B in the control arm, one rhinovirus in the LAIV arm; data not shown; P= 0.03) after presenting with symptoms of illness. Harvard Medical School Boston, Massachusetts Debby Bogaert, M.D., Ph.D.x University of Edinburgh Edinburgh, United Kingdom and University Medical Center Utrecht Utrecht, the Netherlands Neil French, M.B. Ch.B., Ph.D.x University of Liverpool Liverpool, United Kingdom Daniela M. Ferreira, Ph.D.x Liverpool School of Tropical Medicine Liverpool, United Kingdom The EHPC-LAIV Study Group ORCID IDs: 0000-0002-2323-3611 (J.R.); 0000-0001-7730-9477 (D.M.F.). *These authors contributed equally to this work. ‡Corresponding author (e-mail: jamie.rylance@lstmed.ac.uk). §Joint senior authors. Supported by the Bill and Melinda Gates Foundation and the UK Medical Research Council.

BackgroundCritical illness is a leading cause of morbidity and mortality in sub-Saharan Africa (SSA). Identifying patients with the highest risk of death could help with resource allocation and clinical decision making. Accordingly, we derived and validated a universal vital assessment (UVA) score for use in SSA.MethodsWe pooled data from hospital-based cohort studies conducted in six countries in SSA spanning the years 2009–2015. We derived and internally validated a UVA score using decision trees and linear regression and compared its performance with the modified early warning score (MEWS) and the quick sepsis-related organ failure assessment (qSOFA) score.ResultsOf 5573 patients included in the analysis, 2829 (50.8%) were female, the median (IQR) age was 36 (27–49) years, 2122 (38.1%) were HIV-infected and 996 (17.3%) died in-hospital. The UVA score included points for temperature, heart and respiratory rates, systolic blood pressure, oxygen saturation, Glasgow Coma Scale score and HIV serostatus, and had an area under the receiver operating characteristic curve (AUC) of 0.77 (95% CI 0.75 to 0.79), which outperformed MEWS (AUC 0.70 (95% CI 0.67 to 0.71)) and qSOFA (AUC 0.69 (95% CI 0.67 to 0.72)).ConclusionWe identified predictors of in-hospital mortality irrespective of the underlying condition(s) in a large population of hospitalised patients in SSA and derived and internally validated a UVA score to assist clinicians in risk-stratifying patients for in-hospital mortality. The UVA score could help improve patient triage in resource-limited environments and serve as a standard for mortality risk in future studies.

Aim Early warning scores (EWS) are widely used in well-resourced healthcare settings to identify patients at risk of mortality. The Modified Early Warning Score (MEWS) is a well-known EWS used comprehensively in the United Kingdom. The HOTEL score (Hypotension, Oxygen saturation, Temperature, ECG abnormality, Loss of independence) was developed and tested in a European cohort; however, its validity is unknown in resource limited settings. This study compared the performance of both scores and suggested modifications to enhance accuracy. Methods A prospective cohort study of adults ( greater than or equal to 18 yrs) admitted to medical wards at a Malawian hospital. Primary outcome was mortality within three days. Performance of MEWS and HOTEL were assessed using ROC analysis. Logistic regression analysis identified important predictors of mortality and from this a new score was defined. Results Three-hundred-and-two patients were included. Fifty-one (16.9%) died within three days of admission. With a cut-point greater than or equal to 2, the HOTEL score had sensitivity 70.6% (95% CI: 56.2 to 82.5) and specificity 59.4% (95% CI: 53.0 to 65.5), and was superior to MEWS (cut-point greater than or equal to 5); sensitivity: 58.8% (95% CI: 44.2 to 72.4), specificity: 56.2% (95% CI: 49.8 to 62.4). The new score, dubbed TOTAL (Tachypnoea, Oxygen saturation, Temperature, Alert, Loss of independence), showed slight improvement with a cut-point greater than or equal to 2; sensitivity 76.5% (95% CI: 62.5 to 87.2) and specificity 67.3% (95% CI: 61.1 to 73.1). Conclusion Using an EWS generated in developed healthcare systems in resource limited settings results in loss of sensitivity and specificity. A score based on predictors of mortality specific to the Malawian population showed enhanced accuracy but not enough to warrant clinical use. Despite an assumption of common physiological responses, disease and population differences seem to strongly determine the performance of EWS. Local validation and impact assessment of these scores should precede their adoption in resource limited settings.

The widely used nasally-administered Live Attenuated Influenza Vaccine (LAIV) alters the dynamics of naturally occurring nasopharyngeal carriage of Streptococcus pneumoniae in animal models. Using a human experimental model (serotype 6B) we tested two hypotheses: 1) LAIV increased the density of S. pneumoniae in those already colonised; 2) LAIV administration promoted colonisation. Randomised, blinded administration of LAIV or nasal placebo either preceded bacterial inoculation or followed it, separated by a 3-day interval. The presence and density of S. pneumoniae was determined from nasal washes by bacterial culture and PCR. Overall acquisition for bacterial carriage were not altered by prior LAIV administration vs. controls (25/55 [45.5%] vs 24/62 [38.7%] respectively, p=0.46). Transient increase in acquisition was detected in LAIV recipients at day 2 (33/55 [60.0%] vs 25/62 [40.3%] in controls, p=0.03). Bacterial carriage densities were increased approximately 10-fold by day 9 in the LAIV recipients (2.82 vs 1.81 log10 titers, p=0.03). When immunisation followed bacterial acquisition (n=163), LAIV did not change area under the bacterial density-time curve (AUC) at day 14 by conventional microbiology (primary endpoint), but significantly reduced AUC to day 27 by PCR (p=0.03). These studies suggest that LAIV may transiently increase nasopharyngeal density of S. pneumoniae. Transmission effects should therefore be considered in the timing design of vaccine schedules.