Electronic clinical decision support algorithms incorporating point-of-care diagnostic tests in low-resource settings: a target product profile

Health workers in low-resource settings often lack the support and tools to follow evidence-based clinical recommendations for diagnosing, treating and managing sick patients. Digital technologies, by combining patient health information and point-of-care diagnostics with evidence-based clinical protocols, can help improve the quality of care and the rational use of resources, and save patient lives. A growing number of electronic clinical decision support algorithms (CDSAs) on mobile devices are being developed and piloted without evidence of safety or impact. Here, we present a target product profile (TPP) for CDSAs aimed at guiding preventive or curative consultations in low-resource settings. This document will help align developer and implementer processes and product specifications with the needs of end users, in terms of quality, safety, performance and operational functionality. To identify the characteristics of CDSAs, a multidisciplinary group of experts (academia, industry and policy makers) with expertise in diagnostic and CDSA development and implementation in low-income and middle-income countries were convened to discuss a draft TPP. The TPP was finalised through a Delphi process to facilitate consensus building. An agreement greater than 75% was reached for all 40 TPP characteristics. In general, experts were in overwhelming agreement that, given that CDSAs provide patient management recommendations, the underlying clinical algorithms should be human-interpretable and evidence-based. Whenever possible, the algorithm's patient management output should take into account pretest disease probabilities and likelihood ratios of clinical and diagnostic predictors. In addition, validation processes should at a minimum show that CDSAs are implementing faithfully the evidence they are based on, and ideally the impact on patient health outcomes. In terms of operational needs, CDSAs should be designed to fit within clinic workflows and function in connectivity-challenged and high-volume settings. Data collected through the tool should conform to local patient privacy regulations and international data standards

Digitalizing Clinical Guidelines: Experiences in the Development of Clinical Decision Support Algorithms for Management of Childhood Illness in Resource-Constrained Settings.

Clinical decision support systems (CDSSs) can strengthen the quality of integrated management of childhood illness (IMCI) in resource-constrained settings. Several IMCI-related CDSSs have been developed and implemented in recent years. Yet, despite having a shared starting point, the IMCI-related CDSSs are markedly varied due to the need for interpretation when translating narrative guidelines into decision logic combined with considerations of context and design choices. Between October 2019 and April 2021, we conducted a comparative analysis of 4 IMCI-related CDSSs. The extent of adaptations to IMCI varied, but common themes emerged. Scope was extended to cover a broader range of conditions. Content was added or modified to enhance precision, align with new evidence, and support rational resource use. Structure was modified to increase efficiency, improve usability, and prioritize care for severely ill children. The multistakeholder development processes involved syntheses of recommendations from existing guidelines and literature; creation and validation of clinical algorithms; and iterative development, implementation, and evaluation. The common themes surrounding adaptations of IMCI guidance highlight the complexities of digitalizing evidence-based recommendations and reinforce the rationale for leveraging standards for CDSS development, such as the World Health Organization's SMART Guidelines. Implementation through multistakeholder dialogue is critical to ensure CDSSs can effectively and equitably improve quality of care for children in resource-constrained settings

Biomarkers to Distinguish Bacterial From Viral Pediatric Clinical Pneumonia in a Malaria-Endemic Setting.

BACKGROUND: Differential etiologies of pediatric acute febrile respiratory illness pose challenges for all populations globally, but especially in malaria-endemic settings because the pathogens responsible overlap in clinical presentation and frequently occur together. Rapid identification of bacterial pneumonia with high-quality diagnostic tools would enable appropriate, point-of-care antibiotic treatment. Current diagnostics are insufficient, and the discovery and development of new tools is needed. We report a unique biomarker signature identified in blood samples to accomplish this. METHODS: Blood samples from 195 pediatric Mozambican patients with clinical pneumonia were analyzed with an aptamer-based, high-dynamic-range, quantitative assay (~1200 proteins). We identified new biomarkers using a training set of samples from patients with established bacterial, viral, or malarial pneumonia. Proteins with significantly variable abundance across etiologies (false discovery rate 90% sensitivity and >80% specificity, regardless of number of pathogen classes. Bacterial pneumonia was strongly associated with neutrophil markers-in particular, degranulation including HP, LCN2, LTF, MPO, MMP8, PGLYRP1, RETN, SERPINA1, S100A9, and SLPI. CONCLUSIONS: Blood protein signatures highly associated with neutrophil biology reliably differentiated bacterial pneumonia from other causes. With appropriate technology, these markers could provide the basis for a rapid diagnostic for field-based triage for antibiotic treatment of pediatric pneumonia

Shared elements of host-targeting pathways among apicomplexan parasites of differing lifestyles

Apicomplexans are a diverse group of obligate parasites occupying different intracellular niches that require modification to meet the needs of the parasite. To efficiently manipulate their environment, apicomplexans translocate numerous parasite proteins into the host cell. Whereas some parasites remain contained within a parasitophorous vacuole membrane (PVM) throughout their developmental cycle, others do not, a difference that affects the machinery needed for protein export. A signal-mediated pathway for protein export into the host cell has been characterized in Plasmodium parasites, which maintain the PVM. Here, we functionally demonstrate an analogous host-targeting pathway involving organellar staging prior to secretion in the related bovine parasite, Babesia bovis, a parasite that destroys the PVM shortly after invasion. Taking into account recent identification of a similar signal-mediated pathway in the coccidian parasite Toxoplasma gondii, we suggest a model in which this conserved pathway has evolved in multiple steps from signal-mediated trafficking to specific secretory organelles for controlled secretion to a complex protein translocation process across the PVM

Transcriptional categorization of the etiology of pneumonia syndrome in pediatric patients in malaria endemic areas

<p><strong><em>Background.</em></strong> Pediatric acute respiratory distress in tropical settings is very common. Bacterial pneumonia is a major contributor to morbidity and mortality and requires adequate diagnosis for correct treatment. A rapid test that could identify bacterial (vs. other) infections would have great clinical utility.</p> <p><strong><em>Methods and Findings.</em></strong> We performed RNA-Seq and analyzed the transcriptomes of 68 pediatric patients with well-characterized clinical phenotype to identify transcriptional features associated with each disease class. We refined the features to predictive models (support vector machine, elastic net) and validated those models on an independent test set of 37 patients (80 – 85% accuracy).</p> <p><strong><em>Conclusions.</em></strong> We have identified sets of genes that are differentially expressed in pediatric patients with pneumonia syndrome attributable to different infections and requiring different therapeutic interventions. This study demonstrates that human transcription signatures in infected patients recapitulate the underlying biology and provide models for predicting a bacterial diagnosis to inform treatment</p> <ul> </ul

Genetic diversity and protective efficacy of the RTS,S/AS01 malaria vaccine

The RTS,S/AS01 vaccine targets the circumsporozoite protein of Plasmodium falciparum and has partial protective efficacy against clinical and severe malaria disease in infants and children. We investigated whether the vaccine efficacy was specific to certain parasite genotypes at the circumsporozoite protein locus.; We used polymerase chain reaction-based next-generation sequencing of DNA extracted from samples from 4985 participants to survey circumsporozoite protein polymorphisms. We evaluated the effect that polymorphic positions and haplotypic regions within the circumsporozoite protein had on vaccine efficacy against first episodes of clinical malaria within 1 year after vaccination.; In the per-protocol group of 4577 RTS,S/AS01-vaccinated participants and 2335 control-vaccinated participants who were 5 to 17 months of age, the 1-year cumulative vaccine efficacy was 50.3% (95% confidence interval [CI], 34.6 to 62.3) against clinical malaria in which parasites matched the vaccine in the entire circumsporozoite protein C-terminal (139 infections), as compared with 33.4% (95% CI, 29.3 to 37.2) against mismatched malaria (1951 infections) (P=0.04 for differential vaccine efficacy). The vaccine efficacy based on the hazard ratio was 62.7% (95% CI, 51.6 to 71.3) against matched infections versus 54.2% (95% CI, 49.9 to 58.1) against mismatched infections (P=0.06). In the group of infants 6 to 12 weeks of age, there was no evidence of differential allele-specific vaccine efficacy.; These results suggest that among children 5 to 17 months of age, the RTS,S vaccine has greater activity against malaria parasites with the matched circumsporozoite protein allele than against mismatched malaria. The overall vaccine efficacy in this age category will depend on the proportion of matched alleles in the local parasite population; in this trial, less than 10% of parasites had matched alleles. (Funded by the National Institutes of Health and others.)