Evidence map›Paper›PMID 32308891›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2019

Lagged Correlations among Physiological Variables as Indicators of Consciousness in Stroke Patients.

Tahsin T Yavuz, Jan Claassen, Samantha Kleinberg

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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

3 authors.

Tahsin T YavuzStevens Institute of Technology, Hoboken, NJ.
Jan ClaassenColumbia University, New York, NY.
Samantha KleinbergStevens Institute of Technology, Hoboken, NJ.

Funding

BIGDATA: Causal Inference in Large-Scale Time Series with Rare and Latent EventsR01LM011826 · NLM · THE TRUSTEES OF THE STEVENS INSTITUTE OF TECHNOLOGY · PI KLEINBERG, SAMANTHA · 2013 to 2024
$3.3M
NLM NIH HHS R01 LM011826
6 · The paper itself

Abstract

Consciousness is a highly significant indicator of an ICU patient's condition but there is still no method to automatically measure it. Instead, time consuming and subjective assessments are used. However, many brain and physiologic variables are measured continuously in neurological ICU, and could be used as indicators for consciousness. Since many biological variables are highly correlated to maintain homeostasis, we examine whether changes in time lags between correlated variables may relate to changes in consciousness. We introduce new methods to identify changes in the time lag of correlations, which better handle noisy multimodal physiological data and fluctuating lags. On neurological ICU data from subarachnoid hemorrhage patients, we find that correlations among variables related to brain physiology or respiration have significantly longer lags inpatients with decreased levels of consciousness than in patients with higher levels of consciousness. This suggests that physiological data could potentially be used to automatically assess consciousness.

Indexed as

ConsciousnessHumansIntensive Care UnitsModels, BiologicalPatient AcuityResearch DesignStrokeSubarachnoid HemorrhageUnconsciousness

Identifiers

PMID32308891
PMCPMC7153151

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.