Evidence map›Paper›PMID 36000537›Full record

ArticleCNS neuroscience & therapeutics2022

ANAID-ICH nomogram for predicting unfavorable outcome after intracerebral hemorrhage.

Jiawen Li, Dong Luo, Feifei Peng, Qi Kong, Huawei Liu, Meiyuan Chen, Lusha Tong, Feng Gao

Abstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Nomogram Predicting 90-Day Readmission in Patients with Diabetes: A Prospective Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. 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

8 authors.

Jiawen LiDepartment of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.ORCID 0000-0003-2689-0710
Dong LuoDepartment of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Feifei PengDepartment of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Qi KongDepartment of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Huawei LiuDepartment of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Meiyuan ChenDepartment of Neurology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.
Lusha TongDepartment of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Feng GaoDepartment of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDiffusion-weighted imaging lesions (DWILs) are associated with unfavorable outcome in intracerebral hemorrhage (ICH). We proposed a novel predictive nomogram incorporating DWILs.

methodsA total of 738 patients with primary ICH in a tertiary hospital were prospectively enrolled as a training cohort. DWILs were defined as remote focal hyperintensities on DWI corresponding to low intensities on apparent diffusion coefficient images and remote from the focal hematoma. The outcome of interest was modified Rankin Scale scores of 4-6 at 90 days after onset. Multivariate logistic regression was used to construct a nomogram. Model performance was tested in the training cohort and externally validated with respect to discrimination, calibration, and clinical usefulness in another institute. Additionally, the nomogram was compared with the ICH score in terms of predictive ability.

resultsOverall, 153 (20.73%) and 23 (15.54%) patients developed an unfavorable outcome in the training and validation cohorts, respectively. The multivariate analysis revealed that age, National Institutes of Health Stroke Scale (NIHSS) score, anemia, infratentorial location, presence of DWILs, and prior ICH were associated with unfavorable outcome. Our ANAID-ICH nomogram was constructed according to the aforementioned variables; the area under the receiver operating characteristic curve was 0.842 and 0.831 in the training and validation sets, respectively. With regard to the 90-day outcome, the nomogram showed a significantly higher predictive value than the ICH score in both cohorts.

conclusionsThe ANAID-ICH nomogram comprising age, NIHSS score, anemia, infratentorial location, presence of DWILs, and prior ICH may facilitate the identification of patients at higher risk for an unfavorable outcome.

Indexed as

Cerebral HemorrhageNomogramsHematomaHumansPrognosisRetrospective StudiesROC Curvecerebral hemorrhagemagnetic resonance imagingnomogramprognosis

Identifiers

PMID36000537
PMCPMC9627367

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.