BackgroundNeonatal mortality has remained high in Kenya despite various efforts being applied to reduce this negative trend. Early detection of neonatal illness is an important step towards improving new born survival. Toward this end there is need for the mothers to be able to identify signs in neonates that signifies severe neonatal illnesses. The objective of the study was to determine the level of knowledge of mothers attending well baby clinics on postnatal neonatal danger signs and determine the associated factors.Study designCross sectional descriptive study.Study methodsPurposive sampling of Health care facilities that provide antenatal, delivery and postnatal services were identified. In each of the selected health facility structured questionnaires were administered to mothers with children aged six weeks to nine months attending well baby clinics. Frequencies, Chi square and multivariate logistic regression were determined using the SPSS software (version 20).ResultsDuring the period of study 414 mothers attending well baby clinics were interviewed. Information on neonatal dangers was not provided to 237 (57.2%) of the postnatal mothers during their antenatal clinic attendance by the health care providers. Majority of mothers 350 (84.5%) identified less than three neonatal danger signs. Hotness of the body (fever) was the commonly recognized danger sign by 310 (74.9%) postnatal mothers. Out of 414 mothers 193 (46.6%), 166 (40.1%), 146 (35.3%) and 24 (5.8%) identified difficulty in breathing, poor sucking, jaundice and lethargy/unconsciousness as new born danger signs respectively. Only 46 (11.1%) and 40 (9.7%) identified convulsion and hypothermia as new born danger signs respectively. Education Level, PNC accompaniment by Spouse, Danger signs information to Mother, Explanation of MCH booklet by Care provider during ANC and Mother read MCH Booklet were factors positively associated with improved knowledge of neonatal danger sign. In multivariate logistic regression none of the factors tested were statistically significant in relation to level of knowledge.ConclusionKnowledge of neonatal danger signs was low among mothers attending well baby clinic despite the information being available in the MCH booklets provided to the mothers during antenatal clinics.

BackgroundHIV infected children experience a range of hematological complications which show marked improvement within 6 months of initiating anti-retroviral therapy. The Objectives of the study was to describe the changes in hematological indices of HIV-1 infected children following 6 months of treatment with first line antiretroviral drugs (ARVs) regimen.MethodsA retrospective study was conducted between September and November 2008. During this period medical records of children attending Comprehensive Care Clinic at Kenyatta National hospital were reviewed daily. HIV infected children aged 5–144 months were enrolled if they had received antiretroviral drugs for at least 6 months with available and complete laboratory results.ResultsMedical records of 337 children meeting enrollment criteria were included in the study. The median age was 63 months with equal male to female ratio. Following 6 months of HAART, prevalence of anemia (Hemoglobin (Hb) <10 g/dl) declined significantly from 35.9 to 16.6 % a nearly 50 % reduction in the risk of anemia RR = 0.56 [(95 % CI 0.44, 0.70) p < 0.001]. There was significant increase in Hb, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH) and platelets above the baseline measurements (p < 0.0001) and a significant decline in total white blood cell counts >11,000 cell/mm3 but a none significant decrease in red blood cells (RBC). Pre-HAART, World Health Organization (WHO) stage 3 and 4 was associated with a ten-fold increased likelihood of anemia. Chronic malnutrition was associated with anemia but not wasting and immunologic staging of disease.ConclusionHematological abnormalities changed significantly within 6 months of antiretroviral therapy with significant increase in hemoglobin level, MCV, MCH and platelet and decrease in WBC and RBC.

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Introduction. Respiratory distress (RD) contributes to common causes of neonatal mortality. Bubble continuous positive airway pressure (bCPAP) is a safe, low-cost therapy for RD; however, adoption of bCPAP programs remains challenging. Aim. To increase the percentage of neonates with RD treated with bCPAP from 2% to 25% by January 2019. Methods. In the newborn unit (NBU) at the Nakuru County and Referral Hospital in Kenya, a pre-initiative (pre) period (March 2016 to December 2017) and a post-initiative (post) period (January 2018 to December 2018) were defined. Tests of change included organization of infrastructure, staff trainings, development of a nurse educator role, and treatment protocols. Clinical and outcome data were abstracted from all available medical records. Results. A total of 405 infants were included in the pre group, with 2% bCPAP use. A total of 1157 infants were included in the post group, with 100 (17.6%) treated with bCPAP. bCPAP use increased during the post period. Rates of RD (49.9% pre, 49.0% post, P = .64) and mortality (30.9% pre, 29.1% post, P = .35) were similar. Neonates treated with bCPAP had lower mean birth weight and a higher risk of death (relative risk = 1.41, 95% confidence interval = 1.21-1.65) compared with those not treated with bCPAP. Conclusion. It was possible to build capacity for the use of bCPAP to treat neonates in this low-resource setting. Gaps in the delivery bCPAP remain, and the current capacity in the PGH NBU allows for application of bCPAP to smaller, likely, sicker neonates.

Background Two neonatal mortality prediction models, the Neonatal Essential Treatment Score (NETS) which uses treatments prescribed at admission and the Score for Essential Neonatal Symptoms and Signs (SENSS) which uses basic clinical signs, were derived in high-mortality, low-resource settings to utilise data more likely to be available in these settings. In this study, we evaluate the predictive accuracy of two neonatal prediction models for all-cause in-hospital mortality. Methods We used retrospectively collected routine clinical data recorded by duty clinicians at admission from 16 Kenyan hospitals used to externally validate and update the SENSS and NETS models that were initially developed from the data from the largest Kenyan maternity hospital to predict in-hospital mortality. Model performance was evaluated by assessing discrimination and calibration. Discrimination, the ability of the model to differentiate between those with and without the outcome, was measured using the c-statistic. Calibration, the agreement between predictions from the model and what was observed, was measured using the calibration intercept and slope (with values of 0 and 1 denoting perfect calibration). Results At initial external validation, the estimated mortality risks from the original SENSS and NETS models were markedly overestimated with calibration intercepts of − 0.703 (95% CI − 0.738 to − 0.669) and − 1.109 (95% CI − 1.148 to − 1.069) and too extreme with calibration slopes of 0.565 (95% CI 0.552 to 0.577) and 0.466 (95% CI 0.451 to 0.480), respectively. After model updating, the calibration of the model improved. The updated SENSS and NETS models had calibration intercepts of 0.311 (95% CI 0.282 to 0.350) and 0.032 (95% CI − 0.002 to 0.066) and calibration slopes of 1.029 (95% CI 1.006 to 1.051) and 0.799 (95% CI 0.774 to 0.823), respectively, while showing good discrimination with c-statistics of 0.834 (95% CI 0.829 to 0.839) and 0.775 (95% CI 0.768 to 0.782), respectively. The overall calibration performance of the updated SENSS and NETS models was better than any existing neonatal in-hospital mortality prediction models externally validated for settings comparable to Kenya. Conclusion Few prediction models undergo rigorous external validation. We show how external validation using data from multiple locations enables model updating and improving their performance and potential value. The improved models indicate it is possible to predict in-hospital mortality using either treatments or signs and symptoms derived from routine neonatal data from low-resource hospital settings also making possible their use for case-mix adjustment when contrasting similar hospital settings.