ArticleAging2024
Synergistic insights: the integrated role of CT/CTP and clinical parameters in hemorrhagic transformation prediction.
Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Early Predictive Accuracy of Machine Learning for Hemorrhagic Transformation in Acute Ischemic Stroke: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Novel Computed Tomography Perfusion and Laboratory Indices as Predictors of Long-Term Outcome and Survival in Acute Ischemic Stroke.Neurology international · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute ischemic stroke presents significant challenges in healthcare, notably due to the risk and poor prognosis associated with hemorrhagic transformation (HT). Currently, there is a notable gap in the early clinical stage for a valid and reliable predictive model for HT.
methodsThis single-center retrospective study analyzed data from 224 patients with acute ischemic stroke due to large vessel occlusion. We collected comprehensive clinical data, CT, and CTP parameters. A predictive model for HT was developed, incorporating clinical indicators alongside imaging data, and its efficacy was evaluated using decision curve analysis and calibration curves. In addition, we have also built a free browser-based online calculator based on this model for HT prediction.
resultsThe study identified atrial fibrillation and hypertension as significant risk factors for HT. Patients with HT showed more extensive initial ischemic damage and a smaller ischemic penumbra. Our novel predictive model, integrating clinical indicators with CT and CTP parameters, demonstrated superior predictive value compared to models based solely on clinical indicators.
conclusionsThe research highlighted the intricate interplay of clinical and imaging parameters in HT post-thrombectomy. It established a multifaceted predictive model, enhancing the understanding and management of acute ischemic stroke. Future studies should focus on validating this model in broader cohorts, further investigating the causal relationships, and exploring the nuanced effects of these parameters on patient outcomes post-stroke.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.