Evidence map›Paper›PMID 39440100›Full record

ArticleInternational journal of general medicine2024

Development of a Predictive Nomogram Model for Early Deep Vein Thrombosis in Postoperative Spontaneous Intracerebral Hemorrhage Patients.

Linjun Tang, Yong Xu, Liangwei Wang, Jingjing Pan, Yong Wu

Abstract read
In one paragraph

Article in International journal of general medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Risk Prediction Models for Deep Vein Thrombosis in Patients With Spontaneous Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
    Pooled it
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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

5 authors.

Linjun TangDepartment of Neurosurgery, The Second People's Hospital of Wuhu, Wuhu, People's Republic of China.
Yong XuDepartment of Neurosurgery, The Second People's Hospital of Wuhu, Wuhu, People's Republic of China.
Liangwei WangDepartment of Neurosurgery, The Second People's Hospital of Wuhu, Wuhu, People's Republic of China.
Jingjing PanDepartment of Neurosurgery, The Second People's Hospital of Wuhu, Wuhu, People's Republic of China.
Yong WuDepartment of Neurosurgery, The Second People's Hospital of Wuhu, Wuhu, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study explores risk determinants for participants' lower extremities deep vein thrombosis (DVT) in the perioperative phase after spontaneous intracerebral hemorrhage (SICH), thereby informing more effective clinical prevention and treatment strategies. Methods: During the period spanning October 2021 to March 2024, clinical data from 96 participants who received surgical treatment for spontaneous cerebral hemorrhage was analyzed in a retrospective study. Participants were classified into DVT and negative-DVT groups within the first week post-surgery. We used univariate logistic regression and multivariate logistic regression analyses to assess the impact of various clinical variables on DVT. A nomogram model was constructed to forecast the occurrence of early DVT following SICH surgery. The model's performance was assessed and validated using receiver operating characteristic (ROC) curves and bootstrap resampling. Results: Among the 96 participants, 46 developed DVT. Significant differences were noted in age, D-dimer levels, fibrinogen degradation products, Caprini scores, and total surgical bleeding volume between the groups. Multivariate analysis revealed that Caprini score (the values of OR, 95% CI, and P are 1.962, 1.124-3.424, and 0.018, respectively) and total surgical bleeding volume (the values of OR, 95% CI, and P are 1.010, 1.002-1.018, and 0.017, respectively) were risk variables contributing to DVT occurrence. The area under the receiver operating characteristic curve was 0.918 (95% CI, 0.821-0.988). The calibration curve showed good prediction accuracy. Conclusion: The Caprini score and total surgical bleeding volume are meaningful self-reliant risk variables contributing to DVT occurrence in postoperative participants with SICH. We have created a straightforward and efficient model to predict early DVT post-SICH surgery. This model serves as a valuable clinical tool for evaluating individual risk and enhancing decision-making processes.

Indexed as

caprini scorelower extremities deep vein thrombosisperioperative postoperative periodspontaneous intracerebral hemorrhagetotal surgical bleeding volume

Identifiers

PMID39440100
PMCPMC11495207

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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.