Evidence map›Paper›PMID 35411018›Full record

ArticleJournal of perinatology : official journal of the California Perinatal Association2022

Diagnosis and management of cardiopulmonary events in very low birth weight infants close to discharge: a quality improvement initiative.

Jennifer L N Holman, Tinisha M Lambeth, Jennifer F Check, Mario A Rojas

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Article in Journal of perinatology : official journal of the California Perinatal Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 95% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 2 countries.

Jennifer L N HolmanDivision of Neonatology, Department of Pediatrics, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, NC, USA. jholman@wakehealth.edu.ORCID http://orcid.org/0000-0002-0550-7260
Tinisha M LambethDepartment of Academic Nursing, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Jennifer F CheckDivision of Neonatology, Department of Pediatrics, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, NC, USA.
Mario A RojasColombian Neonatal Association (ASCON), Bogota, Colombia.
Wake Forest University · USIndustrial University of Santander · CO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiopulmonary events (CPE) have a central, obstructive, or mixed etiology. Lack of standardized diagnosis and management of CPE may prolong the length of stay (LOS).

objectiveTo increase the accuracy of CPE diagnosis and decrease LOS by 10% for preterm infants over a 12-month period.

methodsDevelop an evidence-based algorithm to identify type of CPE, determine management approach, and evaluate cardio-respiratory monitors output. Apply model for improvement and statistical process control charts to determine special cause variation.

resultsIdentification of central apnea increased from 15 to 39% (p < 0.01). LOS decreased 26% from 52.6 days to 39.2 days, with an estimated cost savings of $13,119 per each of the 225 infants in the initiative.

conclusionAfter implementing an evidence-based algorithm for management of neonatal CPE, a significant increase in the accuracy of the diagnosis of central apnea and cost savings associated with a decrease in LOS were observed.

Indexed as

Patient DischargeSleep Apnea, CentralApneaHumansInfantInfant, NewbornInfant, PrematureInfant, Very Low Birth WeightLength of StayQuality Improvement

Identifiers

PMID35411018
OpenAlexW4223554063

What OpenQuestion holds

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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.