BACKGROUND
Circulating markers of immune and endothelial activation risk stratify infection syndromes agnostic to disease aetiology. However, their utility in children presenting from the community remains unclear.
METHODS
This study recruited children aged 1-59 months presenting with community-acquired acute febrile illnesses to seven hospitals in Bangladesh, Cambodia, Indonesia, Laos, and Viet Nam. Clinical parameters and biomarker concentrations were measured at presentation. The outcome measure was death or receipt of vital organ support within two days of enrolment. Prognostic performance of endothelial (Ang-1, Ang-2, sFlt-1) and immune (CHI3L1, CRP, IP-10, IL-1ra, IL-6, IL-8, IL-10, PCT, sTNFR-1, sTREM-1, suPAR) activation markers, WHO Danger Signs, and two validated severity scores (LqSOFA, SIRS) was compared.
RESULTS
3,423 participants were recruited. 133 met the outcome (weighted prevalence: 0.34%; 95% CI 0.28-0.41). sTREM-1 exhibited highest prognostic accuracy (AUC 0.86; 95% CI 0.82-0.90), outperforming WHO Danger Signs (AUC 0.75; 95% CI 0.70-0.80; p < 0.001), LqSOFA (AUC 0.74; 95% CI 0.70-0.78; p < 0.001), and SIRS (AUC 0.63; 95% CI 0.58-0.68; p < 0.001). Discrimination of immune and endothelial activation markers was particularly strong for children who deteriorated later in the course of their illness. Compared to WHO Danger Signs, an sTREM-1-based triage strategy improved recognition of children at risk of progression to life-threatening infection (sensitivity: 0.80 vs. 0.72), while maintaining comparable specificity (0.81 vs. 0.79).
CONCLUSIONS
Measuring circulating markers of immune and endothelial activation may help earlier recognition of febrile children at risk of poor outcomes in resource-constrained community settings.
In locations where few people have received Covid-19 vaccines, health systems remain vulnerable to spikes in SARS-CoV-2 infections. Triage tools, which could include biomarkers, to identify patients with moderate Covid-19 infection suitable for community-based management would be useful in the event of surges. In consultation with FIND (Geneva, Switzerland) we shortlisted seven biomarkers for evaluation, all measurable using point-of-care tests, and either currently available or in late-stage development.
METHODS
We prospectively recruited unvaccinated adults with laboratory-confirmed Covid-19 presenting to two hospitals in India with moderate symptoms, in order to develop and validate a clinical prediction model to rule-out progression to supplemental oxygen requirement. Moderate disease was defined as oxygen saturation (SpO2) ≥ 94% and respiratory rate < 30 breaths per minute (bpm), in the context of systemic symptoms (breathlessness or fever and chest pain, abdominal pain, diarrhoea, or severe myalgia). All patients had clinical observations and blood collected at presentation, and were followed up for 14 days for the primary outcome, defined as any of the following: SpO2 < 94%; respiratory rate > 30 bpm; SpO2/fraction of inspired oxygen (FiO2) < 400; or death. We specified a priori that each model would contain three easily ascertained clinical parameters (age, sex, and SpO2) and one of the seven biomarkers (C-reactive protein (CRP), D-dimer, interleukin-6 (IL-6), neutrophil-to-lymphocyte ratio (NLR), procalcitonin (PCT), soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), or soluble urokinase plasminogen activator receptor (suPAR)), to ensure the models would be implementable in high patient-throughput, low-resource settings. We evaluated the models’ discrimination, calibration, and clinical utility in a held-out external temporal validation cohort.
ETHICS
Ethical approval was given by the ethics committees of AIIMS and CMC, India, the Oxford Tropical Research Ethics Committee, UK; and by the MSF Ethics Review Board.
ClinicalTrials.gov number, NCT04441372.
RESULTS
426 participants were recruited, of which 89 (21.0%) met the primary outcome. 257 participants comprised the development, and 166 the validation, cohorts. The three models containing NLR, suPAR, or IL-6 demonstrated promising discrimination (c-statistics: 0.72 to 0.74) and calibration (calibration slopes: 1.01 to 1.05) in the held-out validation cohort. Furthermore, they provided greater utility than a model containing the clinical parameters alone (c-statistic = 0.66; calibration slope = 0.68). The inclusion of either NLR or suPAR improved predictive performance such that the ratio of correctly to incorrectly discharged patients increased from 10:1 to 23:1 or 25:1 respectively. Including IL-6 resulted in a similar proportion (~21%) of correctly discharged patients as the clinical model, but without missing any patients requiring supplemental oxygen.
CONCLUSION
We present three clinical prediction models that could help clinicians identify patients with moderate Covid-19 suitable for community-based management. These models are readily implementable and, if validated, could be of particular relevance for resource-limited settings.
CONFLICTS OF INTEREST
None declared.
Insecticide-treated bed nets (ITN) reduce malaria morbidity and mortality consistently in Africa, but their benefits have been less consistent in Asia. This study's objective was to evaluate the malaria protective efficacy of village-wide usage of ITN in Western Myanmar and estimate the cost-effectiveness of ITN compared with extending early diagnosis and treatment services.
METHODS
A cluster-randomized controlled trial was conducted in Rakhine State to assess the efficacy of ITNs in preventing malaria and anaemia in children and their secondary effects on nutrition and development. The data were aggregated for each village to obtain cluster-level infection rates. In total 8,175 children under 10 years of age were followed up for 10 months, which included the main malaria transmission period. The incidence and prevalence of Plasmodium falciparum and Plasmodium vivax infections, and the biting behaviour of Anopheles mosquitoes in the area were studied concurrently. The trial data along with costs for current recommended treatment practices were modelled to estimate the cost-effectiveness of ITNs compared with, or in addition to extending the coverage of early diagnosis and treatment services.
RESULTS
In aggregate, malaria infections, spleen rates, haemoglobin concentrations, and weight for height, did not differ significantly during the study period between villages with and without ITNs, with a weighted mean difference of -2.6 P. falciparum episodes per 1,000 weeks at risk (95% Confidence Interval -7 to 1.8). In areas with a higher incidence of malaria there was some evidence ITN protective efficacy. The economic analysis indicated that, despite the uncertainty and variability in their protective efficacy in the different study sites, ITN could still be cost-effective, but not if they displaced funding for early diagnosis and effective treatment which is substantially more cost-effective.
CONCLUSION
In Western Myanmar deployment of ITNs did not provide consistent protection against malaria in children living in malaria endemic villages. Early diagnosis and effective treatment is a more cost effective malaria control strategy than deployment of ITNs in this area where the main vector bites early in the evening, often before people are protected by an ITN.
In locations where few people have received COVID-19 vaccines, health systems remain vulnerable to surges in SARS-CoV-2 infections. Tools to identify patients suitable for community-based management are urgently needed.
METHODS
We prospectively recruited adults presenting to two hospitals in India with moderate symptoms of laboratory-confirmed COVID-19 in order to develop and validate a clinical prediction model to rule-out progression to supplemental oxygen requirement. The primary outcome was defined as any of the following: SpO2 < 94%; respiratory rate > 30 bpm; SpO2/FiO2 < 400; or death. We specified a priori that each model would contain three clinical parameters (age, sex and SpO2) and one of seven shortlisted biochemical biomarkers measurable using commercially-available rapid tests (CRP, D-dimer, IL-6, NLR, PCT, sTREM-1 or suPAR), to ensure the models would be suitable for resource-limited settings. We evaluated discrimination, calibration and clinical utility of the models in a held-out temporal external validation cohort.
RESULTS
426 participants were recruited, of whom 89 (21.0%) met the primary outcome. 257 participants comprised the development cohort and 166 comprised the validation cohort. The three models containing NLR, suPAR or IL-6 demonstrated promising discrimination (c-statistics: 0.72 to 0.74) and calibration (calibration slopes: 1.01 to 1.05) in the validation cohort, and provided greater utility than a model containing the clinical parameters alone.
CONCLUSIONS
We present three clinical prediction models that could help clinicians identify patients with moderate COVID-19 suitable for community-based management. The models are readily implementable and of particular relevance for locations with limited resources.
In rural and difficult-to-access settings, early and accurate recognition of febrile children at risk of progressing to serious illness could contribute to improved patient outcomes and better resource allocation. This study aims to develop a prognostic clinical prediction tool to assist community healthcare providers identify febrile children who might benefit from referral or admission for facility-based medical care.
METHODS AND ANALYSIS
This prospective observational study will recruit at least 4900 paediatric inpatients and outpatients under the age of 5 years presenting with an acute febrile illness to seven hospitals in six countries across Asia. A venous blood sample and nasopharyngeal swab is collected from each participant and detailed clinical data recorded at presentation, and each day for the first 48 hours of admission for inpatients. Multianalyte assays are performed at reference laboratories to measure a panel of host biomarkers, as well as targeted aetiological investigations for common bacterial and viral pathogens. Clinical outcome is ascertained on day 2 and day 28.Presenting syndromes, clinical outcomes and aetiology of acute febrile illness will be described and compared across sites. Following the latest guidance in prediction model building, a prognostic clinical prediction model, combining simple clinical features and measurements of host biomarkers, will be derived and geographically externally validated. The performance of the model will be evaluated in specific presenting clinical syndromes and fever aetiologies.
ETHICS AND DISSEMINATION
The study has received approval from all relevant international, national and institutional ethics committees. Written informed consent is provided by the caretaker of all participants. Results will be shared with local and national stakeholders, and disseminated via peer-reviewed open-access journals and scientific meetings.
TRIAL REGISTRATION NUMBER NCT04285021.