Evidence map›Paper›PMID 36518690›Full record

ArticlePlastic and reconstructive surgery. Global open2022

Venous Thromboembolism Risk Assessment Models in Plastic Surgery: A Systematic Review and Meta-Analysis.

Mohamed Amir Mrad, Abdullah A Al Qurashi, Qutaiba N M Shah Mardan, Abdulrahman Abdulaziz Al Ghamdi, Faisal Ali Al Jabr, Ahmed Abdullah Almenhali, Abdullah AlMansour, Aroub Al Maghrabi, Abdulaziz Khalid Allhybi, Reyan Hatem Merdad and 1 more

Open access · goldAbstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 8 citations in OpenAlex.

  1. [Independent Risk Factors for Venous Thromboembolism After Gynecological Surgery and the Predictive Value of Postoperative D-Dimer].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026
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  8. CatBoost Machine Learning Model for Thrombosis Risk Prediction in Critically Ill Cancer Patients: A MIMIC-IV Database Study.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
    Observational
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

11 authors at 6 institutions in 1 country.

Mohamed Amir MradPlastic and Reconstructive Surgery Section, Department of Surgery, King Faisal Specialist Hospital & Research Centre, Riyadh, Saudi Arabia.
Abdullah A Al QurashiCollege of Medicine, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
Qutaiba N M Shah MardanABAS Medical Centre, Riyadh, Saudi Arabia.
Abdulrahman Abdulaziz Al GhamdiCollege of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Faisal Ali Al JabrKing Faisal University, Al Ahsa, Saudi Arabia.
Ahmed Abdullah AlmenhaliFaculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Abdullah AlMansourCollege of Medicine, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
Aroub Al MaghrabiCollege of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Abdulaziz Khalid AllhybiCollege of Medicine, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
Reyan Hatem MerdadCollege of Medicine, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
Abdulqader Alaa'adeenCollege of Medicine, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
King Saud bin Abdulaziz University for Health Sciences · SAAlfaisal University · SAImam Abdulrahman Bin Faisal University · SAKing Abdulaziz University · SAKing Faisal Specialist Hospital & Research Centre · SAKing Faisal University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Postoperative venous thromboembolism (VTE) is the most common complication of plastic surgery procedures. Diverse risk assessment models (RAMs) exist to stratify patients by VTE risk, but due to a lack of high-quality evidence and heterogeneity in RAM data, there is no recommendation regarding RAM that can be used for plastic surgery patients. This study compares the reliability and outcomes of Caprini and American Society of Anesthesiologists (ASA) physical status classification RAMs used in plastic surgery to help surgeons stratify the risk of VTE. Methods: MEDLINE and Embase databases were searched between February 2010 and December 2021. All published English articles that report the incidence of VTE stratified by a RAM among patients who underwent plastic surgery were included. The results of the presented meta-analysis were pooled using a random-effects model. Results: The database search revealed 809 articles, out of which eight studies (n = 1,348,606) were eligible. Out of the eight studies, six utilized the Caprini score, and three utilized ASA score. Super-high-risk patients were significantly more likely to present with VTE than their high-risk [odds ratio (OR), 2.92; 95% confidence interval (CI), 1.26-6.78], medium-risk (OR, 5.29; 95% CI, 2.38-11.79), or low-risk counterparts (OR, 10.00; 95% CI, 2.32-43.10) at Caprini score. High-risk patients in ASA score showed significant increase in VTE incidents (OR, 2.72; 95% CI, 1.10-6.72). Conclusions: Both Caprini and ASA RAMs showed compelling evidence of efficacy in our study. However, the Caprini RAM is more predictive of postoperative VTE incidents in high-risk plastic surgery patients than the ASA grading system.

Identifiers

PMID36518690
PMCPMC9742083
OpenAlexW4311823167

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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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.