Evidence map›Paper›PMID 39162840›Full record

ArticleJournal of clinical monitoring and computing2024

Prognostic value of heart rate variability for risk of serious adverse events in continuously monitored hospital patients.

Nikolaj Aagaard, Markus Harboe Olsen, Oliver Wiik Rasmussen, Katja K Grønbaek, Jesper Mølgaard, Camilla Haahr-Raunkjaer, Mikkel Elvekjaer, Eske K Aasvang, Christian S Meyhoff

Abstract read
In one paragraph

Article in Journal of clinical monitoring and computing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Nikolaj AagaardDepartment of Anaesthesia and Intensive Care, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark. nikolaj.aagaard.01@regionh.dk.
Markus Harboe OlsenDepartment of Anaesthesia and Intensive Care, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
Oliver Wiik RasmussenBiomedical Engineering, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
Katja K GrønbaekDepartment of Anaesthesia and Intensive Care, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
Jesper MølgaardDepartment of Anaesthesia, CKO, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
Camilla Haahr-RaunkjaerDepartment of Anaesthesia, CKO, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
Mikkel ElvekjaerDepartment of Anaesthesia and Intensive Care, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
Eske K Aasvang *Department of Anaesthesia, CKO, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
Christian S Meyhoff *Department of Anaesthesia and Intensive Care, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.

Funding

Novo Nordisk Fonden NNF21SA0069370
6 · The paper itself

Abstract

Technological advances allow continuous vital sign monitoring at the general ward, but traditional vital signs alone may not predict serious adverse events (SAE). This study investigated continuous heart rate variability (HRV) monitoring's predictive value for SAEs in acute medical and major surgical patients. Data was collected from four prospective observational studies and two randomized controlled trials using a single-lead ECG. The primary outcome was any SAE, secondary outcomes included all-cause mortality and specific non-fatal SAE groups, all within 30 days. Subgroup analyses of medical and surgical patients were performed. The primary analysis compared the last 24 h preceding an SAE with the last 24 h of measurements in patients without an SAE. The area under a receiver operating characteristics curve (AUROC) quantified predictive performance, interpretated as low prognostic ability (0.5-0.7), moderate prognostic ability (0.7-0.9), or high prognostic ability (> 0.9). Of 1402 assessed patients, 923 were analysed, with 297 (32%) experiencing at least one SAE. The best performing threshold had an AUROC of 0.67 (95% confidence interval (CI) 0.63-0.71) for predicting cardiovascular SAEs. In the surgical subgroup, the best performing threshold had an AUROC of 0.70 (95% CI 0.60-0.81) for neurologic SAE prediction. In the medical subgroup, thresholds for all-cause mortality, cardiovascular, infectious, and neurologic SAEs had moderate prognostic ability, and the best performing threshold had an AUROC of 0.85 (95% CI 0.76-0.95) for predicting neurologic SAEs. Predicting SAEs based on the accumulated time below thresholds for individual continuously measured HRV parameters demonstrated overall low prognostic ability in high-risk hospitalized patients. Certain HRV thresholds had moderate prognostic ability for prediction of specific SAEs in the medical subgroup.

Indexed as

ElectrocardiographyHeart RateROC CurveAdultAgedAged, 80 and overArea Under CurveFemaleHumansMaleMiddle AgedMonitoring, PhysiologicPredictive Value of TestsPrognosisProspective StudiesVital SignsAcute medical diseaseContinuous vital sign monitoringHeart rate variabilityMajor surgerySerious adverse events

Identifiers

PMID39162840
PMCPMC11604769

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.