Evidence map›Paper›PMID 37880777›Full record

Observational studyCritical care (London, England)2023

Quantitative analysis of early apparent diffusion coefficient values from MRIs for predicting neurological prognosis in survivors of out-of-hospital cardiac arrest: an observational study.

Jung A Yoon, Changshin Kang, Jung Soo Park, Yeonho You, Jin Hong Min, Yong Nam In, Wonjoon Jeong, Hong Joon Ahn, In Ho Lee, Hye Seon Jeong and 2 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Critical care (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 3 pooled it
3.1field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 3 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Guideline
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. 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

12 authors at 4 institutions in 1 country.

Jung A Yoon *Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea.
Changshin Kang *Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea.
Jung Soo ParkDepartment of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea. cpcr@cnu.ac.kr.
Yeonho YouDepartment of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea.
Jin Hong MinDepartment of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea.
Yong Nam InDepartment of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea.
Wonjoon JeongDepartment of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea.
Hong Joon AhnDepartment of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea.
In Ho LeeDepartment of Radiology, College of Medicine, Chungnam National University, 266, Munhwa-ro, Jung-gu, Daejeon, Republic of Korea.
Hye Seon JeongDepartment of Neurology, Chungnam National University Hospital, Daejeon, Republic of Korea.
Byung Kook LeeDepartment of Emergency Medicine, Chonnam National University Medical School, Chonnam National University Hospital, Gwangju, Republic of Korea.
Jae Kwang LeeDepartment of Emergency Medicine, College of Medicine, Konyang University Hospital, Daejeon, Republic of Korea.
Chungnam National University Hospital · KRChungnam National University · KRChonnam National University Hospital · KRKonyang University Hospital · KR

Funding

National Research Foundation of Korea NRF-2022R1I1A3063280
6 · The paper itself

Abstract

backgroundThis study aimed to quantitatively analyse ultra-early brain diffusion-weighted magnetic resonance imaging (DW-MRI) findings to determine the apparent diffusion coefficient (ADC) threshold associated with neurological outcomes in comatose survivors of out-of-hospital cardiac arrest (OHCA).

methodsThis retrospective study included adult survivors of comatose OHCA who underwent DW-MRI imaging scans using a 3-T MRI scanner within 6 h of the return of spontaneous circulation (ROSC). We investigated the association between neurological outcomes and ADC values obtained through voxel-based analysis on DW-MRI. Additionally, we constructed multivariable logistic regression models with pupillary light reflex (PLR), serum neuron-specific enolase (NSE), and ADC values as independent variables to predict poor neurological outcomes. The primary outcome was poor neurological outcome 6 months after ROSC, determined by the Cerebral Performance Category 3-5.

resultsOverall, 131 patients (26% female) were analysed, of whom 74 (57%) showed poor neurological outcomes. The group with a poor neurological outcome had lower mean whole brain ADC values (739.1 vs. 787.1 × 10

conclusionsIn this cohort study, early voxel-based quantitative ADC analysis after ROSC was associated with poor neurological outcomes 6 months after cardiac arrest. The mean whole brain ADC value demonstrated the highest sensitivity when the FPR was 0%, and including it in the multivariable model improved the prediction of poor neurological outcomes.

Indexed as

Out-of-Hospital Cardiac ArrestAdultCohort StudiesComaDiffusion Magnetic Resonance ImagingFemaleHumansMalePrognosisRetrospective StudiesSurvivorsBrainCardiac arrestComputed tomographyMagnetic resonance imagingPrognosis

Identifiers

PMID37880777
PMCPMC10599006
OpenAlexW4387938162

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.