Derivation and validation of a novel risk assessment tool to identify children aged 2–59 months at risk of hospitalised pneumonia-related mortality in 20 countries

Differentiating mortality risk of individual infants and children to improve survival: opportunity for impact

Children are not born equal in their likelihood of survival. The risk of mortality is highest during and shortly after birth. In the immediate postnatal period and beyond, perinatal events, nutrition, infections, family and environmental exposures, and health services largely determine the risk of death. We argue that current public health programmes do not fully acknowledge this spectrum of risk or respond accordingly. As a result, opportunities to improve the care, survival, and development of children in resource-poor settings are overlooked. Children at high risk of mortality are underidentified and commonly treated using guidelines that do not differentiate care according to the magnitude or drivers of those risks. Children at low risk of mortality are often provided with more intensive care than needed, disproportionately using limited health-care resources with minimal or no benefits. Declines in newborn, infant, and child mortality rates globally are slowing, and further reductions are likely to be incrementally more difficult to achieve once simple, high impact interventions have been universally implemented. Currently, 63 countries have rates of neonatal mortality that are off track to meet the Sustainable Development Goal 2030 target of 12 deaths per 1000 livebirths or less, and 54 countries have rates of mortality in children younger than 5 years that are off track to meet the target of 25 deaths per 1000 livebirths or less. If these targets are to be met, a change of approach is needed to address infant and child mortality and for health-care systems to more efficiently address residual mortality.

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

CONTEXT

Pneumonia is a leading cause of death in young infants.

OBJECTIVES

To evaluate the efficacy of different antibiotic regimens to treat young infant pneumonia on critical clinical outcomes.

DATA SOURCES

MEDLINE, Embase, CINAHL, World Health Organization (WHO) Global Index Medicus, Cochrane Central Registry of Trials.

STUDY SELECTION

We included randomized controlled trials of young infants aged 0 to 59 days with pneumonia (population) comparing the efficacy of antibiotic regimens (intervention) with alternate regimens or management (control) on clinical outcomes.

DATA EXTRACTION

We extracted data and assessed risk of bias in duplicate. We used Grading of Recommendations, Assessment, Development, and Evaluation to assess certainty of evidence.

LIMITATIONS

Trials were heterogeneous, which precluded data pooling.

RESULTS

Of 2601 publications screened, 10 randomized controlled trials were included. Seven trials were hospital-based (n = 869) and 3 were nonhospital-based (n = 4329). No hospital-based trials evaluated WHO-recommended first-choice regimens. One trial found the WHO-recommended second-choice antibiotic, cefotaxime, to have similar rates of treatment success as non-WHO-recommended regimens of either amoxicillin-clavulanate (RR 0.99, 95% confidence interval 0.82-1.10) or amoxicillin-clavulanate/cefotaxime (RR 1.02, 95% confidence interval 0.86-1.12). Among 3 nonhospital-based trials comparing oral amoxicillin to alternate regimens to treat isolated tachypnea among infants aged 7-59 days, there were no differences in treatment failure between amoxicillin and alternate regimens. Certainty of evidence was low or very low for all primary outcomes.

CONCLUSIONS

We found limited evidence to support the superiority of any single antibiotic regimen over alternate regimens to treat young infant pneumonia.

Clinicopathological discrepancies in the diagnoses of childhood causes of death in the CHAMPS network: An analysis of antemortem diagnostic inaccuracies

INTRODUCTION

Determining aetiology of severe illness can be difficult, especially in settings with limited diagnostic resources, yet critical for providing life-saving care. Our objective was to describe the accuracy of antemortem clinical diagnoses in young children in high-mortality settings, compared with results of specific postmortem diagnoses obtained from Child Health and Mortality Prevention Surveillance (CHAMPS).

METHODS

We analysed data collected during 2016-2022 from seven sites in Africa and South Asia. We compared antemortem clinical diagnoses from clinical records to a reference standard of postmortem diagnoses determined by expert panels at each site who reviewed the results of histopathological and microbiological testing of tissue, blood, and cerebrospinal fluid. We calculated test characteristics and 95% CIs of antemortem clinical diagnostic accuracy for the 10 most common causes of death. We classified diagnostic discrepancies as major and minor, per Goldman criteria later modified by Battle.

RESULTS

CHAMPS enrolled 1454 deceased young children aged 1-59 months during the study period; 881 had available clinical records and were analysed. The median age at death was 11 months (IQR 4-21 months) and 47.3% (n=417) were female. We identified a clinicopathological discrepancy in 39.5% (n=348) of deaths; 82.3% of diagnostic errors were major. The sensitivity of clinician antemortem diagnosis ranged from 26% (95% CI 14.6% to 40.3%) for non-infectious respiratory diseases (eg, aspiration pneumonia, interstitial lung disease, etc) to 82.2% (95% CI 72.7% to 89.5%) for diarrhoeal diseases. Antemortem clinical diagnostic specificity ranged from 75.2% (95% CI 72.1% to 78.2%) for diarrhoeal diseases to 99.0% (95% CI 98.1% to 99.6%) for HIV.

CONCLUSIONS

Antemortem clinical diagnostic errors were common for young children who died in areas with high childhood mortality rates. To further reduce childhood mortality in resource-limited settings, there is an urgent need to improve antemortem diagnostic capability through advances in the availability of diagnostic testing and clinical skills.

Clinical applications of artificial intelligence in identification and management of bacterial infection: Systematic review and meta-analysis

Pneumonia is declared a global emergency public health crisis in children less than five age and the geriatric population. Recent advancements in deep learning models could be utilized effectively for the timely and early diagnosis of pneumonia in immune-compromised patients to avoid complications. This systematic review and meta-analysis utilized PRISMA guidelines for the selection of ten articles included in this study. The literature search was done through electronic databases including PubMed, Scopus, and Google Scholar from 1st January 2016 till 1 July 2023. Overall studies included a total of 126,610 images and 1706 patients in this meta-analysis. At a 95% confidence interval, for pooled sensitivity was 0.90 (0.85-0.94) and I2 statistics 90.20 (88.56 - 91.92). The pooled specificity for deep learning models' diagnostic accuracy was 0.89 (0.86---0.92) and I2 statistics 92.72 (91.50 - 94.83). I2 statistics showed low heterogeneity across studies highlighting consistent and reliable estimates, and instilling confidence in these findings for researchers and healthcare practitioners. The study highlighted the recent deep learning models single or in combination with high accuracy, sensitivity, and specificity to ensure reliable use for bacterial pneumonia identification and differentiate from other viral, fungal pneumonia in children and adults through chest x-rays and radiographs.

Identifying neonates at risk for post-discharge mortality in Dar es Salaam, Tanzania, and Monrovia, Liberia: Derivation and internal validation of a novel risk assessment tool

INTRODUCTION

The immediate period after hospital discharge carries a large burden of childhood mortality in sub-Saharan Africa. Our objective was to derive and internally validate a risk assessment tool to identify neonates discharged from the neonatal ward at risk for 60-day post-discharge mortality.

METHODS

We conducted a prospective observational cohort study of neonates discharged from Muhimbili National Hospital in Dar es Salaam, Tanzania, and John F Kennedy Medical Centre in Monrovia, Liberia. Research staff called caregivers to ascertain vital status up to 60 days after discharge. We conducted multivariable logistic regression analyses with best subset selection to identify socioeconomic, demographic, clinical, and anthropometric factors associated with post-discharge mortality. We used adjusted log coefficients to assign points to each variable and internally validated our tool with bootstrap validation with 500 repetitions.

RESULTS

There were 2344 neonates discharged and 2310 (98.5%) had post-discharge outcomes available. The median (IQR) age at discharge was 8 (4, 15) days; 1238 (53.6%) were male. In total, 71 (3.1%) died during follow-up (26.8% within 7 days of discharge). Leaving against medical advice (adjusted OR [aOR] 5.62, 95% CI 2.40 to 12.10) and diagnosis of meconium aspiration (aOR 6.98, 95% CI 1.69 to 21.70) conferred the greatest risk for post-discharge mortality. The risk assessment tool included nine variables (total possible score=63) and had an optimism corrected area under the receiver operating characteristic curve of 0.77 (95% CI 0.75 to 0.80). A score of ≥6 was most optimal (sensitivity 68.3% [95% CI 64.8% to 71.5%], specificity 72.1% [95% CI 71.5% to 72.7%]).

CONCLUSIONS

A small number of factors predicted all-cause, 60-day mortality after discharge from neonatal wards in Tanzania and Liberia. After external validation, this risk assessment tool may facilitate clinical decision making for eligibility for discharge and the direction of resources to follow-up high risk neonates.

Community-Acquired Pneumonia in Children

ABSTRACT

Community-acquired pneumonia (CAP) is the most common cause of childhood mortality globally. In the United States, CAP is a leading cause of pediatric hospitalization and antibiotic use and is associated with substantial morbidity. There has been a dramatic shift in microbiological etiologies for CAP in children over time as pneumococcal pneumonia has become less common and viral etiologies have become predominant. There is no commonly agreed on approach to the diagnosis of CAP in children. When indicated, antimicrobial treatment should consist of narrow-spectrum antibiotics. In this article, we will describe the current understanding of the microbiological etiologies, clinical presentation, diagnostic approach, risk factors, treatment, and future directions in the diagnosis and management of pediatric CAP.

Burden, predictors, and outcome of unconsciousness among under-five children hospitalized for community-acquired pneumonia: A retrospective study from a developing country

Despite the reduction of death from pneumonia over recent years, pneumonia has still been the leading infectious cause of death in under-five children for the last several decades. Unconsciousness is a critical condition in any child resulting from any illness. Once it occurs during a pneumonia episode, the outcome is perceived to be fatal. However, data on children under five with pneumonia having unconsciousness are scarce. We've retrospectively analyzed the data of under-five children admitted at the in-patient ward of Dhaka Hospital of icddr,b during 1 January 2014 and 31 December 2017 with World Health Organization classified pneumonia or severe pneumonia. Children presented with or without unconsciousness were considered as cases and controls respectively. Among a total of 3,876 children fulfilling the inclusion criteria, 325 and 3,551 were the cases and the controls respectively. A multivariable logistic regression analysis revealed older children (8 months vs. 7.9 months) (adjusted odds ratio, aOR 1.02, 95% CI: 1.004-1.04, p = 0.015), hypoxemia (aOR 3.22, 95% CI: 2.39-4.34, p<0.001), severe sepsis (aOR 4.46, 95% CI: 3.28-6.06, p<0.001), convulsion (aOR 8.90, 95% CI: 6.72-11.79, p<0.001), and dehydration (aOR 2.08, 95% CI: 1.56-2.76, p<0.001) were found to be independently associated with the cases. The cases more often had a fatal outcome than the controls (23% vs. 3%, OR 9.56, 95% CI: 6.95-13.19, p<0.001). If the simple predicting factors of unconsciousness in children under five hospitalized for pneumonia with different severity can be initially identified and adequately treated with prompt response, pneumonia-related deaths can be reduced more effectively, especially in resource-limited settings.

Prognostic accuracy of biomarkers of immune and endothelial activation in Mozambican children hospitalized with pneumonia

Pneumonia is a leading cause of child mortality. However, currently we lack simple, objective, and accurate risk-stratification tools for pediatric pneumonia. Here we test the hypothesis that measuring biomarkers of immune and endothelial activation in children with pneumonia may facilitate the identification of those at risk of death. We recruited children <10 years old fulfilling WHO criteria for pneumonia and admitted to the Manhiça District Hospital (Mozambique) from 2010 to 2014. We measured plasma levels of IL-6, IL-8, Angpt-2, sTREM-1, sFlt-1, sTNFR1, PCT, and CRP at admission, and assessed their prognostic accuracy for in-hospital, 28-day, and 90-day mortality. Healthy community controls, within same age strata and location, were also assessed. All biomarkers were significantly elevated in 472 pneumonia cases versus 80 controls (p<0.001). IL-8, sFlt-1, and sTREM-1 were associated with in-hospital mortality (p<0.001) and showed the best discrimination with AUROCs of 0.877 (95% CI: 0.782 to 0.972), 0.832 (95% CI: 0.729 to 0.935) and 0.822 (95% CI: 0.735 to 0.908), respectively. Their performance was superior to CRP, PCT, oxygen saturation, and clinical severity scores. IL-8, sFlt-1, and sTREM-1 remained good predictors of 28-day and 90-day mortality. These findings suggest that measuring IL-8, sFlt-1, or sTREM-1 at hospital presentation can guide risk-stratification of children with pneumonia, which could enable prioritized care to improve survival and resource allocation.

Assembling a global database of child pneumonia studies to inform WHO pneumonia management algorithm: Methodology and applications

Background

The existing World Health Organization (WHO) pneumonia case management guidelines rely on clinical symptoms and signs for identifying, classifying, and treating pneumonia in children up to 5 years old. We aimed to collate an individual patient-level data set from large, high-quality pre-existing studies on pneumonia in children to identify a set of signs and symptoms with greater validity in the diagnosis, prognosis, and possible treatment of childhood pneumonia for the improvement of current pneumonia case management guidelines.

Methods

Using data from a published systematic review and expert knowledge, we identified studies meeting our eligibility criteria and invited investigators to share individual-level patient data. We collected data on demographic information, general medical history, and current illness episode, including history, clinical presentation, chest radiograph findings when available, treatment, and outcome. Data were gathered separately from hospital-based and community-based cases. We performed a narrative synthesis to describe the final data set.

Results

Forty-one separate data sets were included in the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) database, 26 of which were hospital-based and 15 were community-based. The PREPARE database includes 285 839 children with pneumonia (244 323 in the hospital and 41 516 in the community), with detailed descriptions of clinical presentation, clinical progression, and outcome. Of 9185 pneumonia-related deaths, 6836 (74%) occurred in children <1 year of age and 1317 (14%) in children aged 1-2 years. Of the 285 839 episodes, 280 998 occurred in children 0-59 months old, of which 129 584 (46%) were 2-11 months of age and 152 730 (54%) were males.

Conclusions

This data set could identify an improved specific, sensitive set of criteria for diagnosing clinical pneumonia and help identify sick children in need of referral to a higher level of care or a change of therapy. Field studies could be designed based on insights from PREPARE analyses to validate a potential revised pneumonia algorithm. The PREPARE methodology can also act as a model for disease database assembly.