Evidence map›Paper›PMID 30462671›Full record

ArticlePloS one2018

Clinical cascades as a novel way to assess physical readiness of facilities for the care of small and sick neonates in Kenya and Uganda.

Melissa C Morgan, Hilary Spindler, Harriet Nambuya, Grace M Nalwa, Gertrude Namazzi, Peter Waiswa, Phelgona Otieno, John Cranmer, Dilys M Walker

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

9 authors.

Melissa C MorganDepartment of Pediatrics, University of California San Francisco, San Francisco, California, United States of America.ORCID 0000-0003-3457-8452
Hilary SpindlerInstitute of Global Health Sciences, University of California San Francisco, San Francisco, California, United States of America.
Harriet NambuyaDepartment of Pediatrics, Jinja Regional Referral Hospital, Jinja, Uganda.
Grace M NalwaDepartment of Pediatrics and Child Health, Maseno University, Maseno, Kenya.
Gertrude NamazziMaternal, Newborn and Child Health Centre of Excellence, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda.
Peter WaiswaMaternal, Newborn and Child Health Centre of Excellence, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda.
Phelgona OtienoCenter for Clinical Research, Kenya Medical Research Institute, Nairobi, Kenya.
John CranmerSchool of Nursing, Emory University, Atlanta, Georgia, United States of America.ORCID 0000-0001-7053-9157
Dilys M WalkerInstitute of Global Health Sciences, University of California San Francisco, San Francisco, California, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlobally, there were 2.7 million neonatal deaths in 2015. Significant mortality reduction could be achieved by improving care in low- and middle-income countries (LMIC), where the majority of deaths occur. Determining the physical readiness of facilities to identify and manage complications is an essential component of strategies to reduce neonatal mortality.

methodsWe developed clinical cascades for 6 common neonatal conditions then utilized these to assess 23 health facilities in Kenya and Uganda at 2 time-points in 2016 and 2017. We calculated changes in resource availability over time by facility using McNemar's test. We estimated mean readiness and loss of readiness for the 6 conditions and 3 stages of care (identification, treatment, monitoring-modifying treatment). We estimated overall mean readiness and readiness loss across all conditions and stages. Finally, we compared readiness of facilities with a newborn special care unit (NSCU) to those without using the two-sample test of proportions.

resultsThe cascade model estimated mean readiness of 26.3-26.6% across the 3 stages for all conditions. Mean readiness ranged from 11.6% (respiratory distress-apnea) to 47.8% (essential newborn care) across both time-points. The model estimated overall mean readiness loss of 30.4-31.9%. There was mild to moderate variability in the timing of readiness loss, with the majority occurring in the identification stage. Overall mean readiness was higher among facilities with a NSCU (36.8%) compared to those without (20.0%).

conclusionThe cascade model provides a novel approach to quantitatively assess physical readiness for neonatal care. Among 23 facilities in Kenya and Uganda, we identified a consistent pattern of 30-32% readiness loss across cascades and stages. This aggregate measure could be used to monitor and compare readiness at the facility-, health system-, or national-level. Estimates of readiness and loss of readiness may help guide strategies to improve care, prioritize resources, and promote neonatal survival in LMICs.

Indexed as

Health FacilitiesInfant CareFemaleHumansInfantInfant MortalityInfant, NewbornInfant, Newborn, DiseasesIntensive Care, NeonatalIntensive Care Units, NeonatalKenyaMaleNurseries, HospitalPerinatal DeathPregnancyUganda

Identifiers

PMID30462671
PMCPMC6248954

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LicenceCC BY
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Registered trials

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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.