Evidence map›Paper›PMID 41948359›Full record

ArticleDigital health

Evaluation of a novel technology for newborn resuscitation: A visual display of time since birth, video-audio recording, and ergonomic resuscitation equipment: A prospective observational design.

Omkar Basnet, So Yeon Joyce Kong, Helge Myklebust, Sunil Mani Pokharel, Ashish Kc

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Omkar BasnetResearch Division, Golden Community, Lalitpur, Nepal.
So Yeon Joyce KongStrategic Research, Laerdal Medical, Stavanger, Norway.ORCID https://orcid.org/0000-0001-5106-7342
Helge MyklebustStrategic Research, Laerdal Medical, Stavanger, Norway.
Sunil Mani PokharelDepartment of Obstetrics and Gynaecology, Bharatpur Hospital, Chitwan, Nepal.
Ashish KcSchool of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.ORCID https://orcid.org/0000-0002-0541-4486

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Despite advancements in technologies, the quality of intrapartum care has consistently not improved. This study evaluates the potential efficacy of a novel technology for newborn resuscitation, which provides a visual display of time since birth, video-audio recording, and ergonomic resuscitation equipment, on healthcare providers' performance during ventilation in Nepal. Method: This study utilized a prospective observational design conducted over 3 years at a referral hospital in Nepal. All infants who did not cry within 30 seconds of birth were included, and their ventilation performance was assessed across two phases: SUSTAIN (baseline phase) and Pre-MALA (pilot implementation phase). Ventilation performance was measured through direct observation and video annotation, with the median time to first ventilation compared between the two phases using the Mann-Whitney U test and generalized linear mixed model regression. Results: A total of 164 newborn ventilation events were observed, with 78 during the SUSTAIN phase and 86 during Pre-MALA phase. Direct observation was done in both phases, while video-recording annotation was also conducted during Pre-MALA phase. The median time to first ventilation significantly decreased from 84.3 seconds (interquartile range (IQR): 55.4-114.0) during SUSTAIN to 48.2 seconds (IQR: 33.5-85.0) during Pre-MALA (p < 0.001). The duration of suctioning before ventilation was reduced by 17.8 seconds (adjusted coefficient = -17.8; 95% CI; -23.1, -11.8) and time to first ventilation was reduced by 33 seconds (adjusted coefficient = -33.2; 95% CI; -51.1, -15.4) during Pre-MALA. Conclusion: The result suggests that novel technology during resuscitation can reduce time to first ventilation and unnecessary suctioning in a clinical setting. Further large-scale evaluations are needed to fully assess the potential impact on neonatal care.

Indexed as

Machine Learning Application (MALA)quality improvementreal-time feedbackventilation

Identifiers

PMID41948359
PMCPMC13051146

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.