3 Sarna A, Porwal A, Ramesh S, et al. Characterisation of the types of anaemia prevalent among children and adolescents aged 1-19 years in India: a population-based study.

BackgroundMost of the deaths among neonates in low-income and middle-income countries (LMICs) can be prevented through universal access to basic high-quality health services including essential facility-based inpatient care. However, poor routine data undermines data-informed efforts to monitor and promote improvements in the quality of newborn care across hospitals.MethodsContinuously collected routine patients’ data from structured paper record forms for all admissions to newborn units (NBUs) from 16 purposively selected Kenyan public hospitals that are part of a clinical information network were analysed together with data from all paediatric admissions ages 0–13 years from 14 of these hospitals. Data are used to show the proportion of all admissions and deaths in the neonatal age group and examine morbidity and mortality patterns, stratified by birth weight, and their variation across hospitals.FindingsDuring the 354 hospital months study period, 90 222 patients were admitted to the 14 hospitals contributing NBU and general paediatric ward data. 46% of all the admissions were neonates (aged 0–28 days), but they accounted for 66% of the deaths in the age group 0–13 years. 41 657 inborn neonates were admitted in the NBUs across the 16 hospitals during the study period. 4266/41 657 died giving a crude mortality rate of 10.2% (95% CI 9.97% to 10.55%), with 60% of these deaths occurring on the first-day of admission. Intrapartum-related complications was the single most common diagnosis among the neonates with birth weight of 2000 g or more who died. A threefold variation in mortality across hospitals was observed for birth weight categories 1000–1499 g and 1500–1999 g.InterpretationThe high proportion of neonatal deaths in hospitals may reflect changing patterns of childhood mortality. Majority of newborns died of preventable causes (>95%). Despite availability of high-impact low-cost interventions, hospitals have high and very variable mortality proportions after stratification by birth weight.

ObjectiveTo determine the extent and pattern of treatment failure (TF) among children hospitalised with community-acquired pneumonia at a large tertiary hospital in Kenya.MethodsWe followed up children aged 2–59 months with WHO-defined severe pneumonia (SP) and very severe pneumonia (VSP) for up to 5 days for TF using two definitions: (i) documentation of pre-defined clinical signs resulting in change of treatment (ii) primary clinician's decision to change treatment with or without documentation of the same pre-defined clinical signs.ResultsWe enrolled 385 children. The risk of TF varied between 1.8% (95% CI 0.4–5.1) and 12.4% (95% CI 7.9–18.4) for SP and 21.4% (95% CI 15.9–27) and 39.3% (95% CI 32.5–46.4) for VSP depending on the definition applied. Higher rates were associated with early changes in therapy by clinician in the absence of an obvious clinical rationale. Non-adherence to treatment guidelines was observed for 70/169 (41.4%) and 67/201 (33.3%) of children with SP and VSP, respectively. Among children with SP, adherence to treatment guidelines was associated with the presence of wheeze on initial assessment (P = 0.02), while clinician non-adherence to guideline-recommended treatments for VSP tended to occur in children with altered consciousness (P < 0.001). Using propensity score matching to account for imbalance in the distribution of baseline clinical characteristics among children with VSP revealed no difference in TF between those treated with the guideline-recommended regimen vs. more costly broad-spectrum alternatives [risk difference 0.37 (95% CI −0.84 to 0.51)].ConclusionBefore revising current pneumonia case management guidelines, standardised definitions of TF and appropriate studies of treatment effectiveness of alternative regimens are required.ObjectifDéterminer l'ampleur et les caractéristiques de l’échec du traitement (ET) chez les enfants hospitalisés avec une pneumonie acquise dans la communauté dans un grand hôpital tertiaire du Kenya.MéthodesNous avons suivi des enfants âgés de 2 à 59 mois avec une pneumonie sévère (PS) et une pneumonie très sévère (PTS) telles que définies par l’OMS, sur un maximum de cinq jours pour l’ET, en utilisant deux définitions: (a) documentation des signes cliniques prédéfinis ayant entraîné un changement du traitement, (b) décision primaire du clinicien de changer de traitement avec ou sans documentation des mêmes signes cliniques prédéfinis.RésultatsNous avons recruté 385 enfants. Le risque d’ET variait de 1,8% (IC95%: 0,4 à 5,1) à 12,4% (IC95%: 7,9 à 18,4) pour la PS et de 21,4% (IC95%: 15,9 à 27) à 39,3% (IC95%: 32,5 à 46,4) pour la PTS selon la définition appliquée. Des taux plus élevés étaient associés à des changements précoces du traitement par le clinicien en l'absence d'une justification clinique évidente. Le non-respect des directives de traitement a été observé pour 70/169 (41,4%) et 67/201 (33,3%) enfants avec une PS et une PTS respectivement. Chez les enfants avec une PS, le respect des directives de traitement était associé avec la présenc...

ObjectivePrognostic models aid clinical decision making and evaluation of hospital performance. Existing neonatal prognostic models typically use physiological measures that are often not available, such as pulse oximetry values, in routine practice in low-resource settings. We aimed to develop and validate two novel models to predict all cause in-hospital mortality following neonatal unit admission in a low-resource, high-mortality setting.Study design and settingWe used basic, routine clinical data recorded by duty clinicians at the time of admission to derive (n=5427) and validate (n=1627) two novel models to predict in-hospital mortality. The Neonatal Essential Treatment Score (NETS) included treatments prescribed at the time of admission while the Score for Essential Neonatal Symptoms and Signs (SENSS) used basic clinical signs. Logistic regression was used, and performance was evaluated using discrimination and calibration.ResultsAt derivation, c-statistic (discrimination) for NETS was 0.92 (95% CI 0.90 to 0.93) and that for SENSS was 0.91 (95% CI 0.89 to 0.93). At external (temporal) validation, NETS had a c-statistic of 0.89 (95% CI 0.86 to 0.92) and SENSS 0.89 (95% CI 0.84 to 0.93). The calibration intercept for NETS was −0.72 (95% CI −0.96 to −0.49) and that for SENSS was −0.33 (95% CI −0.56 to −0.11).ConclusionUsing routine neonatal data in a low-resource setting, we found that it is possible to predict in-hospital mortality using either treatments or signs and symptoms. Further validation of these models may support their use in treatment decisions and for case-mix adjustment to help understand performance variation across hospitals.

IntroductionContinuous physiological monitoring devices are often not available for monitoring high-risk neonates in low-resource settings. Easy-to-use, non-invasive, multiparameter, continuous physiological monitoring devices could be instrumental in providing appropriate care and improving outcomes for high-risk neonates in these low-resource settings.Methods and analysisThe purpose of this prospective, observational, facility-based evaluation is to provide evidence to establish whether two existing non-invasive, multiparameter, continuous physiological monitoring devices developed by device developers, EarlySense and Sibel, can accurately and reliably measure vital signs in neonates (when compared with verified reference devices). We will also assess the feasibility, usability and acceptability of these devices for use in neonates in low-resource settings in Africa. Up to 500 neonates are enrolled in two phases: (1) a verification and accuracy evaluation phase at Aga Khan University—Nairobi and (2) a clinical feasibility evaluation phase at Pumwani Maternity Hospital in Nairobi, Kenya. Both quantitative and qualitative data are collected and analysed. Agreement between the investigational and reference devices is determined using a priori-defined accuracy thresholds.Ethics and disseminationThis trial was approved by the Aga Khan University Nairobi Research Ethics Committee and the Western Institutional Review Board. We plan to disseminate research results in peer-reviewed journals and international conferences.Trial registration numberNCT03920761.