Geographical validation of the Smart Triage Model by age group.

Infectious diseases in neonates account for half of the under-five mortality in low- and middle-income countries. Data-driven algorithms such as clinical prediction models can be used to efficiently detect critically ill children in order to optimize care and reduce mortality. Thus far, only a handful of prediction models have been externally validated and are limited to neonatal in-hospital mortality. The aim of this study is to externally validate a previously derived clinical prediction model (Smart Triage) using a combined prospective baseline cohort from Uganda and Kenya with a composite endpoint of hospital admission, mortality, and readmission. We evaluated model discrimination using area under the receiver-operator curve (AUROC) and visualized calibration plots with age subsets (< 30 days, ≤ 2 months, ≤ 6 months, and < 5 years). Due to reduced performance in neonates (< 1 month), we re-estimated the intercept and coefficients and selected new thresholds to maximize sensitivity and specificity. 11595 participants under the age of five (under-5) were included in the analysis. The proportion with an endpoint ranged from 8.9% in all children under-5 (including neonates) to 26% in the neonatal subset alone. The model achieved good discrimination for children under-5 with AUROC of 0.81 (95% CI: 0.79-0.82) but poor discrimination for neonates with AUROC of 0.62 (95% CI: 0.55-0.70). Sensitivity at the low-risk thresholds (CI) were 85% (83%-87%) and 68% (58%-76%) for children under-5 and neonates, respectively. After model revision for neonates, we achieved an AUROC of 0.83 (95% CI: 0.79-0.87) with 13% and 41% as the low- and high-risk thresholds, respectively. The updated Smart Triage performs well in its predictive ability across different age groups and can be incorporated into current triage guidelines at local healthcare facilities. Additional validation of the model is indicated, especially for the neonatal model.

External validation of a paediatric Smart triage model for use in resource limited facilities.

Models for digital triage of sick children at emergency departments of hospitals in resource poor settings have been developed. However, prior to their adoption, external validation should be performed to ensure their generalizability. We externally validated a previously published nine-predictor paediatric triage model (Smart Triage) developed in Uganda using data from two hospitals in Kenya. Both discrimination and calibration were assessed, and recalibration was performed by optimizing the intercept for classifying patients into emergency, priority, or non-urgent categories based on low-risk and high-risk thresholds. A total of 2539 patients were eligible at Hospital 1 and 2464 at Hospital 2, and 5003 for both hospitals combined; admission rates were 8.9%, 4.5%, and 6.8%, respectively. The model showed good discrimination, with area under the receiver-operator curve (AUC) of 0.826, 0.784 and 0.821, respectively. The pre-calibrated model at a low-risk threshold of 8% achieved a sensitivity of 93% (95% confidence interval, (CI):89%-96%), 81% (CI:74%-88%), and 89% (CI:85%-92%), respectively, and at a high-risk threshold of 40%, the model achieved a specificity of 86% (CI:84%-87%), 96% (CI:95%-97%), and 91% (CI:90%-92%), respectively. Recalibration improved the graphical fit, but new risk thresholds were required to optimize sensitivity and specificity.The Smart Triage model showed good discrimination on external validation but required recalibration to improve the graphical fit of the calibration plot. There was no change in the order of prioritization of patients following recalibration in the respective triage categories. Recalibration required new site-specific risk thresholds that may not be needed if prioritization based on rank is all that is required. The Smart Triage model shows promise for wider application for use in triage for sick children in different settings.

Mortality after hospital discharge among children younger than 5 years admitted with suspected sepsis in Uganda: a prospective, multisite, observational cohort study.

BACKGROUND: Substantial mortality occurs after hospital discharge in children younger than 5 years with suspected sepsis, especially in low-income countries. A better understanding of its epidemiology is needed for effective interventions to reduce child mortality in these countries. We evaluated risk factors for death after discharge in children admitted to hospital for suspected sepsis in Uganda, and assessed how these differed by age, time of death, and location of death. METHODS: In this prospective, multisite, observational cohort study, we recruited and consecutively enrolled children aged 0-60 months admitted with suspected sepsis from the community to the paediatric wards of six Ugandan hospitals. Suspected sepsis was defined as the need for admission due to a suspected or proven infectious illness. At admission, trained study nurses systematically collected data on clinical variables, sociodemographic variables, and baseline characteristics with encrypted study tablets. Participants were followed up for 6 months after discharge by field officers who contacted caregivers at 2 months and 4 months after discharge by telephone and at 6 months after discharge in person to measure vital status, health-care seeking after discharge, and readmission details. We assessed 6-month mortality after hospital discharge among those discharged alive, with verbal autopsies conducted for children who had died after hospital discharge. FINDINGS: Between July 13, 2017, and March 30, 2020, 16 991 children were screened for eligibility. 6545 children (2927 [44·72%] female children and 3618 [55·28%] male children) were enrolled and 6191 were discharged from hospital alive. 6073 children (2687 [44·2%] female children and 3386 [55·8%] male children) completed follow-up. 366 children died in the 6-month period after discharge (weighted mortality rate 5·5%). Median time from discharge to death was 28 days (IQR 9-74). For the 360 children for whom location of death was documented, deaths occurred at home (162 [45·0%]), in transit to care (66 [18·3%]), or in hospital (132 [36·7%]) during a subsequent readmission. Death after hospital discharge was strongly associated with weight-for-age Z scores less than -3 (adjusted risk ratio [aRR] 4·7, 95% CI 3·7-5·8 vs a Z score of >-2), discharge or referral to a higher level of care (7·3, 5·6-9·5), and unplanned discharge (3·2, 2·5-4·0). Hazard ratios (HRs) for severe anaemia (<7g/dL) increased with time since discharge, from 1·7 (95% CI 0·9-3·0) for death occurring in the first time tertile to 5·2 (3·1-8·5) in the third time tertile. HRs for some discharge vulnerabilities decreased significantly with increasing time since discharge, including unplanned discharge (from 4.5 [2·9-6·9] in the first tertile to 2·0 [1·3-3·2] in the third tertile) and poor feeding status (from 7·7 [5·4-11·0] to 1·84 [1·0-3·3]). Age interacted with several variables, including reduced weight-for-age Z score, severe anaemia, and reduced admission temperature. INTERPRETATION: Paediatric mortality following hospital discharge after suspected sepsis is common, with diminishing, although persistent, risk during the first 6 months after discharge. Efforts to improve outcomes after hospital discharge are crucial to achieving Sustainable Development Goal 3.2 (ending preventable childhood deaths under age 5 years). FUNDING: Grand Challenges Canada, Thrasher Research Fund, BC Children's Hospital Foundation, and Mining4Life.

Factor structure and measurement invariance of post-concussion symptom ratings on the Health and Behaviour Inventory across time, raters, and groups: An A-CAP study.

OBJECTIVES: To validate the two-factor structure (i.e., cognitive and somatic) of the Health and Behaviour Inventory (HBI), a widely used post-concussive symptom (PCS) rating scale, through factor analyses using bifactor and correlated factor models and by examining measurement invariance (MI). METHODS: PCS ratings were obtained from children aged 8-16.99 years, who presented to the emergency department with concussion (n = 565) or orthopedic injury (OI) (n = 289), and their parents, at 10-days, 3-months, and 6-months post-injury. Item-level HBI ratings were analyzed separately for parents and children using exploratory and confirmatory factor analyses (CFAs). Bifactor and correlated models were compared using various fit indices and tested for MI across time post-injury, raters (parent vs. child), and groups (concussion vs. OI). RESULTS: CFAs showed good fit for both a three-factor bifactor model, consisting of a general factor with two subfactors (i.e., cognitive and somatic), and a correlated two-factor model with cognitive and somatic factors, at all time points for both raters. Some results suggested the possibility of a third factor involving fatigue. All models demonstrated strict invariance across raters and time. Group comparisons showed at least strong or strict invariance. CONCLUSIONS: The findings support the two symptom dimensions measured by the HBI. The three-factor bifactor model showed the best fit, suggesting that ratings on the HBI also can be captured by a general factor. Both correlated and bifactor models showed substantial MI. The results provide further validation of the HBI, supporting its use in childhood concussion research and clinical practice.

Association of sleep duration and sleep quality with overweight/obesity among adolescents of Bangladesh: a multilevel analysis.

BACKGROUND: Sleep deprivation is widely recognized as a potential contributor to childhood obesity. However, few studies have addressed this issue in low-income settings. The aim of this study was to determine the association of both sleep duration and sleep quality with overweight/obesity among adolescents of Bangladesh. METHODS: A cross-sectional study was conducted in four randomly selected schools in Gazipur, Bangladesh, from May to August 2019. Using a self-administered semi-structured questionnaire, data on sleep duration and sleep quality were collected from 1,044 adolescents between 13 and 17 years of age. The body mass indices of the study participants were evaluated using their objectively-assessed anthropometric measurements (weight and height). Multilevel logistic regression was used for data analysis. RESULTS: The prevalence of underweight, overweight and obesity in adolescents in this study were 14.9, 18 and 7.1%, respectively. More than 15% of the students reported sleep disturbance and poor sleep quality. After adjusting for confounders, reduced (<7 h/day) total sleep duration (OR=1.73, 95% CI=1.21-2.47), weekend sleep duration (OR=1.46, 95% CI=1.00-2.12), and night sleep duration (OR=1.55, 95% CI=1.06-2.28) were found to be significantly associated with overweight or obesity in Bangladeshi adolescents. Similarly, significant positive associations were evident between short duration of total sleep (OR=0.33, 95% CI=0.20-0.54), weekday sleep (OR=0.55, 95% CI=0.35-0.84), weekend sleep (OR=0.53, 95% CI=0.31-0.89), and night sleep (OR=0.56, 95% CI=0.36-0.87), and underweight in study participants. Adolescents with short sleep duration were found less likely to be underweight and more likely to be overweight/obese. CONCLUSIONS: Study findings denoted short sleep duration to be associated with overweight/obesity and underweight among adolescents of Bangladesh. Adequate sleep may therefore serve as an effective obesity prevention strategy in the growing stages.

The Effect of Caregiver-Facilitated Pain Management Interventions in Hospitalized Patients on Patient, Caregiver, Provider, and Health System Outcomes: A Systematic Review.

CONTEXT: Alternative pain management interventions involving caregivers may be valuable adjuncts to conventional pain management interventions. OBJECTIVES: Use systematic review methodology to examine caregiver-facilitated pain management interventions in a hospital setting and whether they improve patient, caregiver, provider, or health system outcomes. METHODS: We searched MEDLINE, EMBASE, PsycINFO, CINAHL, and Scopus databases from inception to April 2020. Original research on caregiver-facilitated pain management interventions in hospitalized settings (i.e., any age) were included and categorized into three caregiver engagement strategies: inform (e.g., pain education), activate (e.g., prompt caregiver action), and collaborate (encourage caregiver's interaction with providers). RESULTS: Of 61 included studies, most investigated premature (n = 27 of 61; 44.3%) and full-term neonates (n = 19 of 61; 31.1%). Interventions were classified as activate (n = 46 of 61; 75.4%), inform-activate-collaborate (n = 6 of 61; 9.8%), inform-activate (n = 5 of 61; 8.2%), activate-collaborate (n = 3 of 61; 4.9%), or inform (n = 1 of 61; 1.6%) caregiver engagement strategies. Interventions that included an activate engagement strategy improved pain outcomes in adults (18-64 years) (e.g., self-reported pain, n = 4 of 5; 80%) and neonates (e.g., crying, n = 32 of 41; 73.0%) but not children or older adults (65 years and older). Caregiver outcomes (e.g., pain knowledge) were improved by inform-activate engagement strategies (n = 3 of 3). Interventions did not improve provider (e.g., satisfaction) or health system (e.g., hospital length of stay) outcomes. Most studies were of low (n = 36 of 61; 59.0%) risk of bias. CONCLUSION: Caregiver-facilitated pain management interventions using an activate engagement strategy may be effective in reducing pain of hospitalized neonates. Caregiver-facilitated pain management interventions improved pain outcomes in most adult studies; however, the number of studies of adults is small warranting caution pending further studies.

Disease-specific out-of-pocket healthcare expenditure in urban Bangladesh: A Bayesian analysis.

BACKGROUND: Because of the rapid increase of non-communicable diseases (NCDs) and high burden of healthcare-related financial issues in Bangladesh, there is a concern that out-of-pocket (OOP) payments related to illnesses may become a major burden on household. It is crucial to understand what are the major illnesses responsible for high OPP at the household level to help policymakers prioritize key areas of actions to protect the household from 100% financial hardship for seeking health care as part of universal health coverage. OBJECTIVES: We first estimated the costs of illnesses among a population in urban Bangladesh, and then assessed the household financial burden associated with these illnesses. METHOD: A cross-sectional survey of 1593 randomly selected households was carried out in Bangladesh (urban area of Rajshahi city), in 2011. Catastrophic expenditure was estimated at 40% threshold of household capacity to pay. We employed the Bayesian two-stage hurdle model and Bayesian logistic regression model to estimate age-adjusted average cost and the incidence of household financial catastrophe for each illness, respectively. RESULTS: Overall, approximately 45% of the population of Bangladesh had at least one episode of illness. The age-sex-adjusted average medical expenses and catastrophic health care expenditure among the households were TK 621 and 8%, respectively. Households spent the highest amount of money 7676.9 on paralysis followed by liver disease (TK 2695.4), injury (TK 2440.0), mental disease (TK 2258.0), and tumor (TK 2231.2). These diseases were also responsible for higher incidence of financial catastrophe. Our study showed that 24% of individuals who suffered typhoid incurred catastrophic expenditure followed by liver disease (12.3%), tumor (12.1%), heart disease (8.4%), injury (7.9%), mental disease (7.9%), cataract (7.1%), and paralysis (6.5%). CONCLUSION: The study findings suggest that chronic illnesses were responsible for high costs and high catastrophic expenditures in Bangladesh. Effective risk pooling mechanism might reduce household financial burden related to illnesses. Chronic illness related to NCDs is the major cause of OOP. It is also important to consider prioritizing vulnerable population by subsidizing the high health care cost for some of the chronic illnesses.

Threshold phenomena with respect to the initiation of depopulation in a simple model of foot-and-mouth disease.

Depopulation is one of the important interventions for the outbreak of animal diseases. Simulation models using actual case scenarios conclude that early depopulation is the most efficient in preventing the spread of foot-and-mouth disease (FMD). However, the long delay in its initiation was often seen in the actual cases and the theoretical analyses of FMD epidemiology with depopulation needs further elaboration. Here, we investigated the qualitative features of epidemic models when depopulation at a fixed capacity was delayed. We built a simple deterministic model for FMD based on state-transition, the SEIIR model whose unit is a single farm. The model settings and parameters were determined using the data from the 2010 epidemic in Miyazaki, Japan. By numerical calculation, we showed the existence of the threshold phenomenon with respect to delays in the initiation of depopulation and if the initiation of full-fledged depopulation surpasses the certain critical timing, the final size of the epidemic rapidly increases leading to a "catastrophic situation". We also revealed the mechanism of the threshold phenomenon from the relationship between the depopulation capacity and the increasing rate of infection. Although it can be delayed with lower transmission coefficients, the threshold phenomenon still exists. Thus, the existence of the critical timing for depopulation appears to be a universal feature of FMD epidemiology when depopulation is used as the main treatment for disease control.

Trends and projections of universal health coverage indicators in Ghana, 1995-2030: A national and subnational study.

Ghana has made significant stride towards universal health coverage (UHC) by implementing the National Health Insurance Scheme (NHIS) in 2003. This paper investigates the progress of UHC indicators in Ghana from 1995 to 2015 and makes future predictions up to 2030 to assess the probability of achieving UHC targets. National representative surveys of Ghana were used to assess health service coverage and financial risk protection. The analyses estimated the coverage of 13 prevention and four treatment service indicators at the national level and across wealth quintiles. In addition, we calculated catastrophic health payments and impoverishment to assess financial hardship and used a Bayesian regression model to estimate trends and future projections as well as the probabilities of achieving UHC targets by 2030. Wealth-based inequalities and regional disparities were also assessed. At the national level, 14 out of the 17 health service indicators are projected to reach the target of 80% coverage by 2030. Across wealth quintiles, inequalities were observed amongst most indicators with richer groups obtaining more coverage than their poorer counterparts. Subnational analysis revealed while all regions will achieve the 80% coverage target with high probabilities for the prevention services, the same cannot be applied to the treatment services. In 2015, the proportion of households that suffered catastrophic health payments and impoverishment at a threshold of 25% non-food expenditure were 1.9% (95%CrI: 0.9-3.5) and 0.4% (95%CrI: 0.2-0.8), respectively. These are projected to reduce to 0.4% (95% CrI: 0.1-1.3) and 0.2% (0.0-0.5) respectively by 2030. Inequality measures and subnational assessment revealed that catastrophic expenditure experienced by wealth quintiles and regions are not equal. Significant improvements were seen in both health service coverage and financial risk protection over the years. However, inequalities across wealth quintiles and regions continue to be cause of concerns. Further efforts are needed to narrow these gaps.