Evidence map›Paper›PMID 33596676›Full record

ArticleStroke2021

Dynamic Detection of Delayed Cerebral Ischemia: A Study in 3 Centers.

Murad Megjhani, Kalijah Terilli, Miriam Weiss, Jude Savarraj, Li Hui Chen, Ayham Alkhachroum, David J Roh, Sachin Agarwal, E Sander Connolly, Angela Velazquez and 5 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Stroke, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 3 pooled it
–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

26 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  14. A generalizable physiological model for detection of Delayed Cerebral Ischemia using Federated Learning.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2023
    Article
  15. Review
  16. Article
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  19. Spontaneous subarachnoid haemorrhage.Lancet (London, England) · 2022
    Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Murad Megjhani *Department of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.
Kalijah Terilli *Department of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.
Miriam WeissDepartment of Neurosurgery, RWTH Aachen University, Germany (M.W., G.A.S.).
Jude SavarrajDepartment of Neurology, McGovern Medical School, UT Health, Houston, TX (J.S., H.A.C.).
Li Hui ChenDepartment of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.
Ayham AlkhachroumDepartment of Neurology, University of Miami, FL (A.A.).
David J RohDepartment of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.
Sachin AgarwalDepartment of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.
E Sander ConnollyDepartment of Neurosurgery (E.S.C.), Columbia University Irving Medical Center, New York.
Angela VelazquezDepartment of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.
Amelia BoehmeDepartment of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.
Jan ClaassenDepartment of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.
HuiMahn A ChoiDepartment of Neurology, McGovern Medical School, UT Health, Houston, TX (J.S., H.A.C.).
Gerrit A SchubertDepartment of Neurosurgery, RWTH Aachen University, Germany (M.W., G.A.S.).
Soojin ParkDepartment of Neurology (M.M., K.T., H.C., D.J.R., S.A., A.V., A.B., J.C., S.P.), Columbia University Irving Medical Center, New York.

Funding

Miami Clinical and Translational Science InstituteUL1TR002736 · NCATS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, KOBETZ, ERIN N · 2018 to 2022
$23.2M
Miami Clinical and Translational Science InstituteUL1TR000460 · NCATS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI SACCO, RALPH L. · 2012 to 2016
$16.9M
Multiparametric Prediction of Vasospasm after Subarachnoid HemorrhageK01ES026833 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PARK, SOOJIN · 2015 to 2019
$1.1M
NCATS NIH HHS UL1 TR000460NCATS NIH HHS UL1 TR002736NIEHS NIH HHS K01 ES026833
6 · The paper itself

Abstract

background and purposeDelayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage negatively impacts long-term recovery but is often detected too late to prevent damage. We aim to develop hourly risk scores using routinely collected clinical data to detect DCI.

methodsA DCI classification model was trained using vital sign measurements (heart rate, blood pressure, respiratory rate, and oxygen saturation) and demographics routinely collected for clinical care. Twenty-two time-varying physiological measures were computed including mean, SD, and cross-correlation of heart rate time series with each of the other vitals. Classification was achieved using an ensemble approach with L2-regularized logistic regression, random forest, and support vector machines models. Classifier performance was determined by area under the receiver operating characteristic curves and confusion matrices. Hourly DCI risk scores were generated as the posterior probability at time

resultsThree hundred ten patients were included in the training model (median, 54 years old [interquartile range, 45-65]; 80.2% women, 28.4% Hunt and Hess scale 4-5, 38.7% Modified Fisher Scale 3-4); 101 (33%) developed DCI with a median onset day 6 (interquartile range, 5-8). Classification accuracy before DCI onset was 0.83 (interquartile range, 0.76-0.83) area under the receiver operating characteristic curve. Risk scores applied to external institution datasets correctly predicted 64% and 91% of DCI events as early as 12 hours before clinical detection, with 2.7 and 1.6 true alerts for every false alert.

conclusionsAn hourly risk score for DCI derived from routine vital signs may have the potential to alert clinicians to DCI, which could reduce neurological injury.

Indexed as

Machine LearningAgedBrain IschemiaFemaleHumansMaleMiddle AgedNeurophysiological MonitoringRisk FactorsSubarachnoid Hemorrhageblood pressureheart ratemachine learningrespiratory ratesubarachnoid hemorrhage

Identifiers

PMID33596676
PMCPMC8247633

What OpenQuestion holds

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Read underepoch 390

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.