Accuracy of Nelson and best guess formulae in estimation of weights in Nigerian children population

Background: An alternative method of estimating children’s weights, when direct weighing is impracticable is the use of age-based formulae but these formulae have not been validated in Nigeria. This study compares estimated weights from two commonly used formulae against actual weights of healthy children.Methods: Children aged 1 month to 11 years (n= 2754) were randomlyselected in Ibadan, Nigeria using a two-stage sampling procedure. Weight of each child, measured using a standard calibrated scale and determined using Nelson and Best Guess formulae, were compared. Demographic characteristics were also obtained. Mean percentage error (MPE) was calculated and stratified by gender and age. Bland-Altman graphs were used for visual assessment of the agreement between estimated and measured weights. Clinically acceptable MPE was defined as ±5%.  Descriptive statistics and paired t test were used to examine the data. Statistical level of significance was set at p = 0.05.Results: There were 1349 males and 1405 females. Nelson and Best Guess formulae overestimated weight by 10.11% (95% CI: -20.44, 40.65) in infants. For 1-5 years group, Nelson formula marginally underestimated weight by -0.59% (95% CI: -5.16, 3.96) while it overestimated weight by 9.87% (95% CI: 24.89, 44.63) in 6-11 years. Best Guess formulae consistently overestimated weight in all age groups with the MPE ranging from 10.11 to 30.67%.Conclusion: Nelson and Best Guess formulae are inaccurate for weight estimations in infants and children aged 6-11 years. Development of new formulae or modifications should be considered for use in the Nigerian children population.Keywords: Measured weight, Best Guess formula, Nelson formula, Mean percentage erro

Prevalence of dermatological lesions in hospitalized children at the University College Hospital, Ibadan, Nigeria

Objective: Skin disorders constitute a significant proportion of consultations in children’s clinics; however, there is a paucity of data on the prevalence of dermatological lesions in hospitalized children in Nigeria. This study determines the prevalence of dermatological lesions in hospitalized children.Materials and Methods: In this cross-sectional study, 402 children aged three months to twelve years admitted in the Pediatric wards of the University College Hospital, Ibadan, were enrolled over a six-month period. Examination of the skin and its appendages was done for each patient. Data on the socioeconomic status, hygiene, and health-related factors were also obtained using a structured questionnaire.Results: Over 96% of the children had at least one identifiable skin lesion. The five leading skin lesions were postinflammatory hyperpigmentation (49.5%), BCG scar (28.4%), Mongolian spots (27.1%), junctional melanocytic nevi (20.1%), and café-au-lait macules (18.4%). The leading infectious skin disease was pyoderma (13.4%), followed by tinea capitis (6.7%). Scarification marks (P=0.001), tinea capitis (P=0.014), plantar fissuring (P=0.001), and impetigo (P=0.016) were associated with low socioeconomic classes, while the presence of BCG scar (50.0%) was associated with the high socioeconomic class.Conclusions: This study shows that dermatologic lesions are common in hospitalized children. Identifying them will provide an opportunity for pediatricians to educate parents on the various causes as well as prevention of lesions

Epidermolysis bullosa simplex: A case report

Epidermolysis bullosa (EB) is a rare hereditary cutaneous disorder inherited mainly in an autosomal dominant fashion. It consists of a group of conditions that cause the skin to be fragile and blister easily. EB has been classified into three types namely; simplex, junctional and dystrophic. Although all three types of EB have different causes, their symptoms are similar, manifesting as painful blisters and sores. Epidermolysis bullosa is a very rare condition but may probably be more common in clinical practice than reported in literature, especially in places like Nigeria where there is under reporting of clinical cases. To the knowledge of the authors, there are few reported cases in Nigeria and none from Bayelsa State in the delta region of the country. We herein present a case of epidermolysis bullosa simplex (Dowling Meara type) in a 35 day old infant. This case is reported with the aim of increasing awareness of its existence in Nigeria and Bayelsa State in particular.Key words: epidermolysis bullosa simplex, case, skin ulcer

Congenital tuberculosis: A case report and review of the literature

Congenital tuberculosis (TB) is a rare infection transmitted from a mother to her foetus, either through an infected placenta or amniotic fluid. Congenital tuberculosis was previously thought to be rare but recent changes in the epidemiology of TB, have resulted in an increased risk.1 Affected infants usually present with non specific signs and symptoms, hence a high index of suspicion is required to make a diagnosis. Fewer than 300 cases have been reported worldwide till date1 and to the knowledge of the authors, there have been only three reported cases in Nigeria.2-4 We herein report a case of congenital tuberculosis with a review of other published cases in this high TBprevalent region of Southern Nigeria with the aim of creating awarenessof its existence in this region

Data-driven malaria prevalence prediction in large densely populated urban holoendemic sub-Saharan West Africa

Over 200 million malaria cases globally lead to half-million deaths annually. The development of malaria prevalence prediction systems to support malaria care pathways has been hindered by lack of data, a tendency towards universal "monolithic" models (one-size-fits-all-regions) and a focus on long lead time predictions. Current systems do not provide short-term local predictions at an accuracy suitable for deployment in clinical practice. Here we show a data-driven approach that reliably produces one-month-ahead prevalence prediction within a densely populated all-year-round malaria metropolis of over 3.5 million inhabitants situated in Nigeria which has one of the largest global burdens of P. falciparum malaria. We estimate one-month-ahead prevalence in a unique 22-years prospective regional dataset of > 9 × 10^{4} participants attending our healthcare services. Our system agrees with both magnitude and direction of the prediction on validation data achieving MAE ≤ 6 × 10^{-2}, MSE ≤ 7 × 10^{-3}, PCC (median 0.63, IQR 0.3) and with more than 80% of estimates within a (+ 0.1 to - 0.05) error-tolerance range which is clinically relevant for decision-support in our holoendemic setting. Our data-driven approach could facilitate healthcare systems to harness their own data to support local malaria care pathways