Evidence map›Paper›PMID 36256803›Full record

ArticleInteractive journal of medical research2022

Association of Continuously Measured Vital Signs With Respiratory Insufficiency in Hospitalized COVID-19 Patients: Retrospective Cohort Study.

Harriet M R van Goor, Lisette M Vernooij, Martine J M Breteler, Cor J Kalkman, Karin A H Kaasjager, Kim van Loon

Open access · goldAbstract read
In one paragraph

Article in Interactive journal of medical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Harriet M R van GoorDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.ORCID https://orcid.org/0000-0002-6332-1325
Lisette M VernooijDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.ORCID https://orcid.org/0000-0002-9153-087X
Martine J M BretelerDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.ORCID https://orcid.org/0000-0001-7342-0741
Cor J KalkmanDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.ORCID https://orcid.org/0000-0002-8372-6960
Karin A H KaasjagerDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.ORCID https://orcid.org/0000-0001-6958-8285
Kim van LoonDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.ORCID https://orcid.org/0000-0002-5225-8746
University Medical Center Utrecht · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundContinuous monitoring of vital signs has the potential to assist in the recognition of deterioration of patients admitted to the general ward. However, methods to efficiently process and use continuously measured vital sign data remain unclear.

objectiveThe aim of this study was to explore methods to summarize continuously measured vital sign data and evaluate their association with respiratory insufficiency in COVID-19 patients at the general ward.

methodsIn this retrospective cohort study, we included patients admitted to a designated COVID-19 cohort ward equipped with continuous vital sign monitoring. We collected continuously measured data of respiratory rate, heart rate, and oxygen saturation. For each patient, 7 metrics to summarize vital sign data were calculated: mean, slope, variance, occurrence of a threshold breach, number of episodes, total duration, and area above/under a threshold. These summary measures were calculated over timeframes of either 4 or 8 hours, with a pause between the last data point and the endpoint (the "lead") of 4, 2, 1, or 0 hours, and with 3 predefined thresholds per vital sign. The association between each of the summary measures and the occurrence of respiratory insufficiency was calculated using logistic regression analysis.

resultsOf the 429 patients that were monitored, 334 were included for analysis. Of these, 66 (19.8%) patients developed respiratory insufficiency. Summarized continuously measured vital sign data in timeframes close to the endpoint showed stronger associations than data measured further in the past (ie, lead 0 vs 1, 2, or 4 hours), and summarized estimates over 4 hours of data had stronger associations than estimates taken over 8 hours of data. The mean was consistently strongly associated with respiratory insufficiency for the three vital signs: in a 4-hour timeframe without a lead, the standardized odds ratio for heart rate, respiratory rate, and oxygen saturation was 2.59 (99% CI 1.74-4.04), 5.05 (99% CI 2.87-10.03), and 3.16 (99% CI 1.78-6.26), respectively. The strength of associations of summary measures varied per vital sign, timeframe, and lead.

conclusionsThe mean of a vital sign showed a relatively strong association with respiratory insufficiency for the majority of vital signs and timeframes. The type of vital sign, length of the timeframe, and length of the lead influenced the strength of associations. Highly associated summary measures and their combinations could be used in a clinical prediction score or algorithm for an automatic alarm system.

Indexed as

clinicalcohort studycontinuous monitoringCOVID-19datageneral wardheart ratemonitoringoxygenrespirationrespiratory insufficiencyrespiratory ratevital signvital sign monitoring

Identifiers

PMID36256803
PMCPMC9688258
OpenAlexW4306832018

What OpenQuestion holds

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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.