A Novel method for the identification and quantification of weight faltering.

OBJECTIVE: We describe a new method for identifying and quantifying the magnitude and rate of short-term weight faltering episodes, and assess how (a) these episodes relate to broader growth outcomes, and (b) different data collection intervals influence the quantification of weight faltering. MATERIALS AND METHODS: We apply this method to longitudinal growth data collected every other day across the first year of life in Gambian infants (n = 124, males = 65, females = 59). Weight faltering episodes are identified from velocity peaks and troughs. Rate of weight loss and regain, maximum weight loss, and duration of each episode were calculated. We systematically reduced our dataset to mimic various potential measurement intervals, to assess how these intervals affect the ability to derive information about short-term weight faltering episodes. We fit linear models to test whether metrics associated with growth faltering were associated with growth outcomes at 1 year, and generalized additive mixed models to determine whether different collection intervals influence episode identification and metrics. RESULTS: Three hundred weight faltering episodes from 119 individuals were identified. The number and magnitude of episodes negatively impacted growth outcomes at 1 year. As data collection interval increases, weight faltering episodes are missed and the duration of episodes is overestimated, resulting in the rate of weight loss and regain being underestimated. CONCLUSIONS: This method identifies and quantifies short-term weight faltering episodes, that are in turn negatively associated with growth outcomes. This approach offers a tool for investigators interested in understanding how short-term weight faltering relates to longer-term outcomes.

Nutritional status and disease severity in children acutely presenting to a primary health clinic in rural Gambia.

BACKGROUND: Accurate and timely data on the health of a population are key for evidence-based decision making at both the policy and programmatic level. In many low-income settings, such data are unavailable or outdated. Using an electronic medical records system, we determined the association between nutritional status and severe illness and mortality among young children presenting to a rural primary health care facility in the Gambia. METHODS: Clinical data collected over five years (2010-2014) on children aged under 60 months making acute visits to a primary health care clinic in the rural Gambian district of Kiang West were retrospectively extracted from the medical records system. Generalised estimating equation models were used to investigate associations between nutritional status and illness severity, accounting for repeat visits, gender, age and access to transport to the clinic. The Population Attributable Fraction (PAF) was used to determine the proportion of severe illness likely attributable to different grades of malnutrition. RESULTS: 3839/5021 (77%) children under 60 months of age living in Kiang West presented acutely to the clinic at least once, yielding 21,278 visits (47% girls, median age 20.2 months (Interquartile Range (IQR) 23.92 months)) and 26,001 diagnoses, 86% being infectious diseases. Severe illness was seen in 4.5% of visits (961/21,278). Wasting was associated with an increased risk of severe illness in a dose-dependent manner, ('WHZ < -1' adjusted Odds Ratio (aOR) 1.68, 95% CI:1.43-1.98, p < 0.001, 'WHZ <-2 and ≥-3' aOR 2.78, 95% CI:2.31-3.36, p < 0.001 and 'WHZ < -3' aOR 7.82, 95% CI:6.40-9.55, p < 0.001) the PAF for wasting (WHZ < -2) was 0.21 (95% CI: 0.18-0.24). Stunting, even in the most severe form (HAZ < -3), was not significantly associated with severe illness (aOR 1.19 95% CI:0.94-1.51) but was associated with a significantly increased risk of death (aOR 6.04 95% CI:1.94-18.78). CONCLUSION: In this population-based cohort of young children in rural Gambia, wasting was associated with disease severity in a dose-dependent manner. Further research is needed into strategies to identify and reach these children with effective interventions to improve their nutritional status.

Validation of the Emergency Department-Paediatric Early Warning Score (ED-PEWS) for use in low- and middle-income countries: A multicentre observational study.

Early recognition of children at risk of serious illness is essential in preventing morbidity and mortality, particularly in low- and middle-income countries (LMICs). This study aimed to validate the Emergency Department-Paediatric Early Warning Score (ED-PEWS) for use in acute care settings in LMICs. This observational study is based on previously collected clinical data from consecutive children attending four diverse settings in LMICs. Inclusion criteria and study periods (2010-2021) varied. We simulated the ED-PEWS, consisting of patient age, consciousness, work of breathing, respiratory rate, oxygen saturation, heart rate, and capillary refill time, based on the first available parameters. Discrimination was assessed by the area under the curve (AUC), sensitivity and specificity (previously defined cut-offs < 6 and ≥ 15). The outcome measure was for each setting a composite marker of high urgency. 41,917 visits from Gambia rural, 501 visits from Gambia urban, 2,608 visits from Suriname, and 1,682 visits from Tanzania were included. The proportion of high urgency was variable (range 4.6% to 24.9%). Performance ranged from AUC 0.80 (95%CI 0.70-0.89) in Gambia urban to 0.62 (95%CI 0.55-0.67) in Tanzania. The low-urgency cut-off showed a high sensitivity in all settings ranging from 0.83 (95%CI 0.81-0.84) to 1.00 (95%CI 0.97-1.00). The high-urgency cut-off showed a specificity ranging from 0.71 (95%CI 0.66-0.75) to 0.97 (95%CI 0.97-0.97). The ED-PEWS has a moderate to good performance for the recognition of high urgency children in these LMIC settings. The performance appears to have potential in improving the identification of high urgency children in LMICs.

Timing of the Infancy-Childhood Growth Transition in Rural Gambia.

The Karlberg model of human growth describes the infancy, childhood, and puberty (ICP) stages as continuous and overlapping, and defined by transitions driven by sequential additional effects of several endocrine factors that shape the growth trajectory and resultant adult size. Previous research has suggested that a delayed transition from the infancy to the childhood growth stage contributes to sub-optimal growth outcomes. A new method developed to analyze the structure of centile crossing in early life has emerged as a potential tool for identifying the infancy-childhood transition (ICT), through quantifying patterns of adjacent monthly weight-for-age z-score (WAZ) deviation correlations. Using this method, the infancy-childhood transition was identified as taking place at around 12 months of age in two cohorts of UK infants. Here, we apply this method to data collected as part of a longitudinal growth study in rural Gambia [the Hormonal and Epigenetic Regulators of Growth, or HERO-G study, N = 212 (F = 99, M = 113)], in order to identify the ICT and assess whether timing of this transition differs across groups based on sex or birth seasonality. We calculated Pearson correlation coefficients for adjacent monthly WAZ score deviations. Based on the patterns of change in the correlation structure over time, our results suggest that the infancy-childhood transition occurs at around 9 months of age in rural Gambian infants. This points to an accelerated ICT compared to UK infants, rather than a delayed ICT. A comparatively later transition, seen in UK infants, allows maximal extension of the high rates of growth during the infancy stage; an earlier transition as seen in Gambian infants cuts short this period of rapid growth, potentially impacting on growth outcomes in childhood while diverting energy into other processes critical to responses to acute infectious challenges. Growth in later developmental stages in this population offers an extended window for catch-up.