Evidence map›Paper›PMID 36882443›Full record

ArticleScientific data2023

WAVES - The Lucile Packard Children's Hospital Pediatric Physiological Waveforms Dataset.

Daniel R Miller, Gurpreet S Dhillon, Nicholas Bambos, Andrew Y Shin, David Scheinker

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Building the future of ICU care: Is our digital foundation strong enough? A multicentre survey of Australian and New Zealand intensive care units.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2025
    Article
  2. Article
  3. 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.

Daniel R MillerStanford University; Department of Electrical Engineering, Palo Alto, CA, 94304, USA.
Gurpreet S DhillonStanford University School of Medicine; Lucile Packard Children's Hospital at Stanford; Department of Pediatrics, Division of Pediatric Cardiology, Palo Alto, CA, 94304, USA.ORCID 0000-0002-9567-7924
Nicholas BambosStanford University; Department of Electrical Engineering, Palo Alto, CA, 94304, USA.
Andrew Y ShinStanford University School of Medicine; Lucile Packard Children's Hospital at Stanford; Department of Pediatrics, Division of Pediatric Cardiology, Palo Alto, CA, 94304, USA. drewshin@stanford.edu.
David ScheinkerStanford University; Department of Management Science and Engineering, Palo Alto, CA, 94304, USA. dscheink@stanford.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

WAVES is a large, single-center dataset comprising 9 years of high-frequency physiological waveform data from patients in intensive and acute care units at a large academic, pediatric medical center. The data comprise approximately 10.6 million hours of 1 to 20 concurrent waveforms over approximately 50,364 distinct patient encounters. The data have been de-identified, cleaned, and organized to facilitate research. Initial analyses demonstrate the potential of the data for clinical applications such as non-invasive blood pressure monitoring and methodological applications such as waveform-agnostic data imputation. WAVES is the largest pediatric-focused and second largest physiological waveform dataset available for research.

Indexed as

Critical CareHospitalsChildHumans

Identifiers

PMID36882443
PMCPMC9992360

What OpenQuestion holds

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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 OpenQuestion graph.