Evidence map›Paper›PMID 41840526›Full record

ArticleBMC neurology2026

Development and validation of a prognostic model for neurological deterioration in acute posterior circulation cerebral infarction.

Zedan Guo, Qian Zhang, Jiani Wu, Li Yi

Abstract readValidation Study
In one paragraph

Article in BMC neurology, 2026. 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

4 authors.

Zedan Guo *PKU-Shenzhen Clinical Institute of Shantou University Medical College, Shenzhen, Guangdong province, China.
Qian Zhang *School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong province, China.
Jiani WuDepartment of Medical Administration, Peking University Shenzhen Hospital, Peking University, Shenzhen, Guangdong province, China.
Li YiDepartment of Neurology, Peking University Shenzhen Hospital, Peking University, Lianhua Road 1120, Futian District, Shenzhen, Guangdong Province, CN-518036, China. yilitj@hotmail.com.

Funding

National Natural Science Foundation of China 22067015Shenzhen Science and Technology Innovation Program JCYJ20190822090801701
6 · The paper itself

Abstract

backgroundNeurological deterioration occurs in 8%-40% of patients with acute posterior circulation cerebral infarction (APCCI), leading to higher disability and mortality. We developed and validated a prognostic model integrating dynamic physiological indicators and quantitative neuroimaging indicators for early risk stratification.

methodsWe retrospectively enrolled patients with APCCI from Peking University Shenzhen Hospital into training set (n = 447) and testing set (n = 94). The model incorporates quantitative neuroimaging (mean apparent diffusion coefficient value (MAV) of infarct lesions) and dynamic physiological monitoring (systolic blood pressure variability), combining qualitative and quantitative approaches to better characterize infarction and hemodynamic instability. A nomogram was constructed and evaluated using discrimination, calibration, and clinical decision curve analysis (DCA).

resultsThe model demonstrated moderate discrimination, with an AUC of 0.74 (95% CI: 0.62–0.86) in the testing set, and ideal calibration (Brier score 0.15). DCA confirmed superior clinical benefit within an 8%–56% threshold range. Both MAV and blood pressure variability were significant predictors, highlighting their added prognostic value beyond conventional factors.

conclusionsThe prognostic model effectively identifies APCCI patients at risk of neurological deterioration by incorporating innovative neuroimaging and dynamic monitoring indicators. Temporal validation shows promising performance in the validation cohort, and further multi-center validation is warranted for clinical adoption.

Indexed as

Cerebral InfarctionInfarction, Posterior Cerebral ArteryAgedFemaleHumansMaleMiddle AgedNeuroimagingNomogramsPrognosisRetrospective StudiesCerebral InfarctionNeurological DeteriorationNomogramPosterior CirculationPrognosis model

Identifiers

PMID41840526
PMCPMC13107863

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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.