Training programs to improve identification of sick newborns and care-seeking from a health facility in low- and middle-income countries: a scoping review.

BACKGROUND: Most neonatal deaths occur in low- and middle-income countries (LMICs). Limited recommendations are available on the optimal personnel and training required to improve identification of sick newborns and care-seeking from a health facility. We conducted a scoping review to map the key components required to design an effective newborn care training program for community-based health workers (CBHWs) to improve identification of sick newborns and care-seeking from a health facility in LMICs. METHODS: We searched multiple databases from 1990 to March 2020. Employing iterative scoping review methodology, we narrowed our inclusion criteria as we became more familiar with the evidence base. We initially included any manuscripts that captured the concepts of "postnatal care providers," "neonates" and "LMICs." We subsequently included articles that investigated the effectiveness of newborn care provision by CBHWs, defined as non-professional paid or volunteer health workers based in communities, and their training programs in improving identification of newborns with serious illness and care-seeking from a health facility in LMICs. RESULTS: Of 11,647 articles identified, 635 met initial inclusion criteria. Among these initial results, 35 studies met the revised inclusion criteria. Studies represented 11 different types of newborn care providers in 11 countries. The most commonly studied providers were community health workers. Key outcomes to be measured when designing a training program and intervention to increase appropriate assessment of sick newborns at a health facility include high newborn care provider and caregiver knowledge of newborn danger signs, accurate provider and caregiver identification of sick newborns and appropriate care-seeking from a health facility either through caregiver referral compliance or caregivers seeking care themselves. Key components to consider to achieve these outcomes include facilitators: sufficient duration of training, refresher training, supervision and community engagement; barriers: context-specific perceptions of newborn illness and gender roles that may deter care-seeking; and components with unclear benefit: qualifications prior to training and incentives and remuneration. CONCLUSION: Evidence regarding key components and outcomes of newborn care training programs to improve CBHW identification of sick newborns and care-seeking can inform future newborn care training design in LMICs. These training components must be adapted to country-specific contexts.

Comparison of motor outcomes between preschool children with univentricular and biventricular critical heart disease not diagnosed with cerebral palsy or acquired brain injury.

This comparison study of two groups within an inception cohort aimed to compare the frequency of motor impairment between preschool children with univentricular and biventricular critical congenital heart disease (CHD) not diagnosed with cerebral palsy/acquired brain injury, describe and compare their motor profiles and explore predictors of motor impairment in each group.Children with an intellectual quotient <70 or cerebral palsy/acquired brain injury were excluded. Motor skills were assessed with the Movement Assessment Battery for Children-2. Total scores <5th percentile indicated motor impairment. Statistical analysis included χ2 test and multiple logistic regression analysis.At a mean age of 55.4 (standard deviation 3.77) months, motor impairment was present in 11.8% of those with biventricular critical CHD, and 32.4% (p < 0.001) of those with univentricular critical CHD. The greatest difference between children with biventricular and univentricular CHD was seen in total test scores 8.73(2.9) versus 6.44(2.8) (p < 0.01) and in balance skills, 8.84 (2.8) versus 6.97 (2.5) (p = 0.001). Manual dexterity mean scores of children with univentricular CHD were significantly below the general population mean (>than one standard deviation). Independent odds ratio for motor impairment in children with biventricular critical CHD was presence of chromosomal abnormality, odds ratio 10.9 (CI 2.13-55.8) (p = 0.004); and in children with univentricular critical CHD odds ratio were: postoperative day 1-5 highest lactate (mmol/L), OR: 1.65 (C1.04-2.62) (p = 0.034), and dialysis requirement any time before the 4.5-year-old assessment, OR: 7.8 (CI 1.08-56.5) (p = 0.042).Early assessment of motor skills, particularly balance and manual dexterity, allows for intervention and supports that can address challenges during the school years.

Rethinking 'essential' and 'nonessential': the developmental paediatrician's COVID-19 response.

While terms such as 'essential' and 'nonessential' used amidst the COVID-19 pandemic may serve a practical purpose, they also pose a risk of obstructing our view of the harmful indirect health consequences of this crisis. SARS-CoV-2 cases and deaths in children are minimal compared to adults, but the pandemic impacts other 'essential' aspects of children's health including child development and the associated areas of paediatric behaviour, mental health, and maltreatment. Alongside the management of severe SARS-CoV-2 cases in emergency rooms and intensive care units, continuing to care for children with developmental disabilities must also be concurrently championed as 'essential' during this crisis. The potentially devastating lifelong effects of the pandemic and isolation on an already vulnerable population demand that action be taken now. Video conferences and phone calls are 'essential' instruments we can use to continue to provide quality care for our patients.

Laparoscopic colorectal cancer resections in the obese: a systematic review.

BACKGROUND: Laparoscopic colorectal cancer operations in obese patients pose technical challenges that may negatively impact oncologic adequacy. A meta-analysis was performed to assess the oncologic outcomes of laparoscopic colorectal cancer resections in obese compared to non-obese patients. Short- and long-term outcomes were assessed secondarily. METHODS: A systematic literature search was conducted from inception until October 01, 2014. Studies that compared outcomes of laparoscopic colorectal malignant neoplasms in obese and non-obese patients were selected for meta-analysis. Studies that defined obesity as body mass index (BMI) ≥ 30 kg/m2 were included. Oncologic, operative, and postoperative outcomes were evaluated. Pooled odds ratios (OR) and weighted mean differences (WMD) with 95 % confidence intervals (CI) were calculated using fixed-effects models. For oncologic and survival outcomes, a subgroup analysis was conducted for rectal cancer and a secondary analysis was conducted for Asian studies that used a BMI cutoff of 25 kg/m2. RESULTS: Thirteen observational studies with a total of 4550 patients were included in the meta-analysis. Lymph node retrieval, distal, and circumferential margins, and 5-year disease-free and overall survival were similar in the obese and non-obese groups. Conversion rate (OR 2.11, 95 % CI 1.58-2.81), postoperative morbidity (OR 1.54, 95 % CI 1.21-1.97), wound infection (OR 2.43, 95 % CI 1.46-4.03), and anastomotic leak (OR 1.65, 95 % CI 1.01-2.71) were all significantly increased in the obese group. CONCLUSIONS: Laparoscopic colorectal cancer operations in obese patients pose an increased technical challenge as demonstrated by higher conversion rates and higher risk of postoperative complications compared to non-obese patients. Despite these challenges, oncologic adequacy of laparoscopic colorectal cancer resections is comparable in both groups.

Young Infants Clinical Signs Study 8-sign Algorithm for Identification of Sick Infants Adapted for Routine Home Visits: A Systematic Review and Critical Appraisal of its Measurement Properties.

Objective. The 8-sign algorithm adapted from the Young Infants Clinical Signs Study (YICSS) is widely used to identify sick infants during home visits (YICSS-home algorithm). We aimed to critically appraise the development and evidence of measurement properties, including sensibility, reliability, and validity, of the YICSS-home algorithm. Methods. Relevant studies were identified through a systematic literature search. Results. The YICSS-home algorithm has good sensibility. The algorithm demonstrated at least moderate inter-rater reliability and sensitivity ranging from 69% to 80%. However, the algorithm was developed among sick infants brought for care to a health facility and not initially developed for use by community health workers (CHWs) during home visits. Some important risk factors were omitted at item generation. Inter-CHW reliability and construct validity have not been estimated. Conclusion. Future research should build on the strengths of the YICSS-home algorithm and address its limitations to develop a new algorithm with improved predictive accuracy.

Clinical prediction models in children that use repeated measurements with time-varying covariates: a scoping review.

BACKGROUND: Emerging evidence suggests that clinical prediction models that use repeated (time-varying) measurements within each patient may have higher predictive accuracy than models that use patient information from a single measurement. OBJECTIVE: To determine the breadth of the published literature reporting the development of clinical prediction models in children that use time-varying predictors. DATA SOURCES: MEDLINE, EMBASE and Cochrane databases. ELIGIBILITY CRITERIA: We included studies reporting the development of a multivariable clinical prediction model in children, with or without validation, to predict a repeatedly measured binary or time-to-event outcome and utilizing at least one repeatedly measured predictor. SYNTHESIS METHODS: We categorized included studies by the method used to model time-varying predictors. RESULTS: Of 99 clinical prediction model studies that had a repeated measurements data structure, only 27 (27%) used methods that incorporated the repeated measurements as time-varying predictors in a single model. Among these 27 time-varying prediction model studies, we grouped model types into nine categories: time-dependent Cox regression, generalized estimating equations, random effects model, landmark model, joint model, neural network, K-nearest neighbor, support vector machine and tree-based algorithms. Where there was comparison of time-varying models to single measurement models, using time-varying predictors improved predictive accuracy. CONCLUSIONS: Various methods have been used to develop time-varying prediction models in children, but there is a paucity of pediatric time-varying models in the literature. Incorporating time-varying covariates in pediatric prediction models may improve predictive accuracy. Future research in pediatric prediction model development should further investigate whether incorporation of time-varying covariates improves predictive accuracy.

Efficacy of Antibiotic Regimens for Meningitis in Young Infants Aged 0-59 Days: A Systematic Review.

CONTEXT: Meningitis is associated with high mortality risk in young infants, yet the optimal treatment regimen is unclear. OBJECTIVES: To systematically evaluate the efficacy of antibiotic regimens to treat meningitis in young infants aged 0 to 59 days on critical clinical outcomes. DATA SOURCES: MEDLINE, Embase, CINAHL, WHO Global Index Medicus, and Cochrane Central Registry of Trials. STUDY SELECTION: We included randomized controlled trials (RCTs) of young infants with meningitis (population) comparing the efficacy of antibiotic regimens (interventions) with alternate regimens (control) on clinical outcomes. DATA EXTRACTION: We extracted data on study characteristics and assessed risk of bias in duplicate. Grading of Recommendations Assessment, Development, and Evaluation was used to assess certainty of evidence. RESULTS: Of 1088 studies screened, only 2 RCTs were identified. They included 168 infants from 5 countries and were conducted between 1976 and 2015. Neither study compared current World Health Organization-recommended regimens. One multisite trial from 4 countries compared intrathecal gentamicin plus systemic ampicillin/gentamicin to systemic ampicillin/gentamicin and found no difference in mortality (relative risk, 0.88; 95% confidence interval, 0.41-1.53; 1 trial, n = 98, very low certainty of evidence) or adverse events (no events in either trial arm). Another trial in India compared a 10-day versus 14-day course of antibiotics and found no difference in mortality (relative risk, 0.88; 95% confidence interval, 0.41-1.53; 1 trial, n = 98, very low certainty of evidence) or other outcomes. CONCLUSIONS: Trial data on the efficacy of antibiotic regimens in young infant meningitis are scarce. Rigorous RCTs are needed to inform recommendations for optimal antibiotic regimens for meningitis treatment in this vulnerable population, particularly within the context of changing epidemiology and increasing antimicrobial resistance.

Predictive Accuracy of Infant Clinical Sign Algorithms for Mortality in Young Infants Aged 0 to 59 Days: A Systematic Review.

CONTEXT: Clinical sign algorithms are a key strategy to identify young infants at risk of mortality. OBJECTIVE: Synthesize the evidence on the accuracy of clinical sign algorithms to predict all-cause mortality in young infants 0-59 days. DATA SOURCES: MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL Registry of Trials. STUDY SELECTION: Studies evaluating the accuracy of infant clinical sign algorithms to predict mortality. DATA EXTRACTION: We used Cochrane methods for study screening, data extraction, and risk of bias assessment. We determined certainty of evidence using Grading of Recommendations Assessment Development and Evaluation. RESULTS: We included 11 studies examining 26 algorithms. Three studies from non-hospital/community settings examined sign-based checklists (n = 13). Eight hospital-based studies validated regression models (n = 13), which were administered as weighted scores (n = 8), regression formulas (n = 4), and a nomogram (n = 1). One checklist from India had a sensitivity of 98% (95% CI: 88%-100%) and specificity of 94% (93%-95%) for predicting sepsis-related deaths. However, external validation in Bangladesh showed very low sensitivity of 3% (0%-10%) with specificity of 99% (99%-99%) for all-cause mortality (ages 0-9 days). For hospital-based prediction models, area under the curve (AUC) ranged from 0.76-0.93 (n = 13). The Score for Essential Neonatal Symptoms and Signs had an AUC of 0.89 (0.84-0.93) in the derivation cohort for mortality, and external validation showed an AUC of 0.83 (0.83-0.84). LIMITATIONS: Heterogeneity of algorithms and lack of external validation limited the evidence. CONCLUSIONS: Clinical sign algorithms may help identify at-risk young infants, particularly in hospital settings; however, overall certainty of evidence is low with limited external validation.

Diagnostic Accuracy of Clinical Sign Algorithms to Identify Sepsis in Young Infants Aged 0 to 59 Days: A Systematic Review and Meta-analysis.

CONTEXT: Accurate identification of possible sepsis in young infants is needed to effectively manage and reduce sepsis-related morbidity and mortality. OBJECTIVE: Synthesize evidence on the diagnostic accuracy of clinical sign algorithms to identify young infants (aged 0-59 days) with suspected sepsis. DATA SOURCES: MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL Registry of Trials. STUDY SELECTION: Studies reporting diagnostic accuracy measures of algorithms including infant clinical signs to identify young infants with suspected sepsis. DATA EXTRACTION: We used Cochrane methods for study screening, data extraction, risk of bias assessment, and determining certainty of evidence using Grading of Recommendations Assessment Development and Evaluation. RESULTS: We included 19 studies (12 Integrated Management of Childhood Illness [IMCI] and 7 non-IMCI studies). The current World Health Organization (WHO) 7-sign IMCI algorithm had a sensitivity of 79% (95% CI 77%-82%) and specificity of 77% (95% CI 76%-78%) for identifying sick infants aged 0-59 days requiring hospitalization/antibiotics (1 study, N = 8889). Any IMCI algorithm had a pooled sensitivity of 84% (95% CI 75%-90%) and specificity of 80% (95% CI 64%-90%) for identifying suspected sepsis (11 studies, N = 15523). When restricting the reference standard to laboratory-supported sepsis, any IMCI algorithm had a pooled sensitivity of 86% (95% CI 82%-90%) and lower specificity of 61% (95% CI 49%-72%) (6 studies, N = 14278). LIMITATIONS: Heterogeneity of algorithms and reference standards limited the evidence. CONCLUSIONS: IMCI algorithms had acceptable sensitivity for identifying young infants with suspected sepsis. Specificity was lower using a reference standard of laboratory-supported sepsis diagnosis.

Cost and cost-effectiveness of childhood cancer treatment in low-income and middle-income countries: a systematic review.

INTRODUCTION: A major barrier to improving childhood cancer survival is the perception that paediatric oncology services are too costly for low-income and middle-income country (LMIC) health systems. We conducted a systematic review to synthesise existing evidence on the costs and cost-effectiveness of treating childhood cancers in LMICs. METHODS: We searched multiple databases from their inception to March 2019. All studies reporting costs or cost-effectiveness of treating any childhood cancer in an LMIC were included. We appraised included articles using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Where possible, we extracted or calculated the cost per disability-adjusted life year (DALY) averted using reported survival and country-specific life expectancy. Cost/DALY averted was compared with per capita gross domestic product (GDP) as per WHO-Choosing Interventions that are Cost-Effective guidelines to determine cost-effectiveness. RESULTS: Of 2802 studies identified, 30 met inclusion criteria. Studies represented 22 countries and nine different malignancies. The most commonly studied cancers were acute lymphoblastic leukaemia (n=10), Burkitt lymphoma (n=4) and Wilms tumour (n=3). The median CHEERS checklist score was 18 of 24. Many studies omitted key cost inputs. Notably, only 11 studies included healthcare worker salaries. Cost/DALY averted was extracted or calculated for 12 studies and ranged from US$22 to US$4475, although the lower-end costs were primarily from studies that omitted key cost components. In all 12, cost/DALY averted through treatment was substantially less than country per capita GDP, and therefore considered very cost-effective. CONCLUSION: Many included studies did not account for key cost inputs, thus underestimating true treatment costs. Costs/DALY averted were nonetheless substantially lower than per capita GDP, suggesting that even if all relevant inputs are included, LMIC childhood cancer treatment is consistently very cost-effective. While additional rigorous economic evaluations are required, our results can inform the development of LMIC national childhood cancer strategies.