ArticleBMJ paediatrics open2024
Development and evaluation of a clinical guideline for a paediatric telemedicine service in a low-resource setting.
Article in BMJ paediatrics open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03943654 (Novel Approach to Improve Patient Care and Diarrheal Disease Research Using Mobile Technology), which is not on this map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Novel Approach to Improve Patient Care and Diarrheal Disease Research Using Mobile Technology
Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Pathways to optimize a pediatric telemedicine and medication delivery service: a multi-level qualitative study in Haiti.BMC health services research · 2025Article
- Evaluation of a Scalable Design for a Pediatric Telemedicine and Medication Delivery Service: A Prospective Cohort Study in Haiti.The American journal of tropical medicine and hygiene · 2025Article
- Development of an AI-enabled predictive model to identify the 'sick child' at a pediatric telemedicine and medication delivery service in Haiti.medRxiv : the preprint server for health sciences · 2025Article
- Needs assessment and prioritization of key medical specialties: A telemedicine roadmap based on a mixed-methods framework.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 3 institutions in 2 countries.
Funding
Abstract
objectiveTo develop and evaluate a guideline for a paediatric telemedicine and medication delivery service (TMDS).
methodsA clinical guideline for paediatric telemedicine was derived from the World Health (WHO) Organization
resultsA total of 391 cases were enrolled. Among the 320 cases with paired examinations, no general WHO danger signs were identified during in-person examinations; 5 cases (2%) required hospital referral due to problem-specific danger signs or other reasons for escalation. Cohen's kappa for the virtual designation of mild cases was 0.78 (95% CI: 0.69 to 0.87). The sensitivity and specificity of a virtually reported fever were 91% (95% CI: 87% to 96%) and 69% (95% CI: 62% to 76%), respectively; the sensitivity and specificity of virtually reported 'fast breathing' were 47% (95% CI: 21% to 72%) and 89% (95% CI: 85% to 94%), respectively. Kappa for 'no' and 'some' dehydration indicated moderate congruence between virtual and in-person examinations (0.69; 95% CI: 0.41 to 0.98). At 10 days, 273 (95%) of the 287 cases reached by phone were better/recovered.
conclusionCritical components of the virtual examination (triage, danger signs and dehydration assessment) performed well despite varied performance among the problem-specific components. The study and associated resources represents formative steps towards an evidence-based paediatric telemedicine guideline built on WHO clinical principles. In-person examinations for select cases were important to address limitations with virtual examinations and identify cases for escalation. TRIAL REGISTRATION NUMBER: NCT03943654.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.