Evidence map›Paper›PMID 37231686›Full record

ArticleEuropean stroke journal2023

Prediction of delayed reperfusion in patients with incomplete reperfusion following thrombectomy.

Adnan Mujanovic, Robin Brigger, Christoph C Kurmann, Felix Ng, Mattia Branca, Tomas Dobrocky, Thomas R Meinel, Daniel Windecker, William Almiri, Lorenz Grunder and 9 more

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European stroke journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
1.9field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. 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

19 authors at 2 institutions in 2 countries.

Adnan MujanovicDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.ORCID 0000-0002-6839-7134
Robin BriggerDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.ORCID 0000-0001-7847-7720
Christoph C KurmannDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Felix NgDepartment of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
Mattia BrancaCTU Bern, University of Bern, Bern, Switzerland.
Tomas DobrockyDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Thomas R MeinelDepartment of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.ORCID 0000-0002-0647-9273
Daniel WindeckerDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
William AlmiriDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Lorenz GrunderDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Morin BeyelerDepartment of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.ORCID 0000-0001-5911-7957
David J SeiffgeDepartment of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.ORCID 0000-0003-3890-3849
Sara Pilgram-PastorDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Marcel ArnoldDepartment of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Eike I PiechowiakDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Bruce CampbellDepartment of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
Jan GrallaDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Urs FischerDepartment of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Johannes KaesmacherDepartment of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
University of Bern · CHThe Royal Melbourne Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe clinical course of patients with incomplete reperfusion after thrombectomy, defined as an expanded Thrombolysis in Cerebral Infarction (eTICI) score of 2a-2c, is heterogeneous. Patients showing delayed reperfusion (DR) have good clinical outcomes, almost comparable to patients with ad-hoc TICI3 reperfusion. We aimed to develop and internally validate a model that predicts DR occurrence in order to inform physicians about the likelihood of a benign natural disease progression. PATIENTS AND

methodsSingle-center registry analysis including all consecutive, study-eligible patients admitted between 02/2015 and 12/2021. Preliminary variable selection for the prediction of DR was performed using bootstrapped stepwise backward logistic regression. Interval validation was performed with bootstrapping and the final model was developed using a random forests classification algorithm. Model performance metrics are reported with discrimination, calibration, and clinical decision curves. Primary outcome was concordance statistics as a measure of goodness of fit for the occurrence of DR.

resultsA total of 477 patients (48.8% female, mean age 74 years) were included, of whom 279 (58.5%) showed DR on 24 follow-up. The model's discriminative ability for predicting DR was adequate (C-statistics 0.79 [95% CI: 0.72-0.85]). Variables with strongest association with DR were: atrial fibrillation (aOR 2.06 [95% CI: 1.23-3.49]), Intervention-To-Follow-Up time (aOR 1.06 [95% CI: 1.03-1.10]), eTICI score (aOR 3.49 [95% CI: 2.64-4.73]), and collateral status (aOR 1.33 [95% CI: 1.06-1.68]). At a risk threshold of

conclusionsThe model presented here shows fair predictive accuracy for estimating chances of DR after incomplete thrombectomy. This may inform treating physicians on the chances of a favorable natural disease progression if no further reperfusion attempts are made.

Indexed as

StrokeAgedCerebral InfarctionDisease ProgressionFemaleHumansMaleReperfusionThrombectomydecision curvesdelayed reperfusionincomplete reperfusionPerfusion Imagingprediction model

Identifiers

PMID37231686
PMCPMC10334170
OpenAlexW4360853918

What OpenQuestion holds

Textmetadata
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.