Evidence map›Paper›PMID 38858713›Full record

ArticleBMC musculoskeletal disorders2024

Risk factor analysis and establishment of a nomogram model to predict blood loss during total knee arthroplasty.

Yikai Liu, Jiangshan Ai, Xue Teng, Zhenchao Huang, Haoshen Wu, Zian Zhang, Wenzhe Wang, Chang Liu, Haining Zhang

Registry-linked trialAbstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07174895 (Efficacy of Tranexamic Acid With/Without Drain in Knee Arthroplasty), which is not on this map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 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.

NCT07174895 nacompletednot on this map

Efficacy of Tranexamic Acid With/Without Drain in Knee Arthroplasty: A Study From Northwest Syria

TypeinterventionalSponsorIdlib UniversityRan2021 to 2025Enrolled192ConditionsOsteoarthritis, KneeArmsIntra-articular Tranexamic Acid + Suction Drainage, Intra-articular Tranexamic Acid, Suction Drainage Only
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. 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

9 authors.

Yikai Liu *Department of Joint Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Jiangshan Ai *Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Xue Teng *Department of Operating Room, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Zhenchao HuangDepartment of Joint Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Haoshen WuDepartment of Joint Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Zian ZhangDepartment of Joint Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Wenzhe WangDepartment of Joint Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Chang LiuDepartment of Joint Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Haining ZhangDepartment of Joint Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China. zhanghaining1976@126.com.

Funding

National Natural Science Foundation of China 81672197
6 · The paper itself

Abstract

purposeThe risk factors for excessive blood loss and transfusion during total knee arthroplasty (TKA) remain unclear. The present study aimed to determine the risk factors for excessive blood loss and establish a predictive model for postoperative blood transfusion.

methodsThis retrospective study included 329 patients received TKA, who were randomly assigned to a training set (n = 229) or a test set (n = 100). Univariate and multivariate linear regression analyses were used to determine risk factors for excessive blood loss. Univariate and multivariate logistic regression analyses were used to determine risk factors for blood transfusion. R software was used to establish the prediction model. The accuracy and stability of the models were evaluated using calibration curves, consistency indices, and receiver operating characteristic (ROC) curve analysis.

resultsRisk factors for excessive blood loss included timing of using a tourniquet, the use of drainage, preoperative ESR, fibrinogen, HCT, ALB, and free fatty acid levels. Predictors in the nomogram included timing of using a tourniquet, the use of drainage, the use of TXA, preoperative ESR, HCT, and albumin levels. The area under the ROC curve was 0.855 (95% CI, 0.800 to 0.910) for the training set and 0.824 (95% CI, 0.740 to 0.909) for the test set. The consistency index values for the training and test sets were 0.855 and 0.824, respectively.

conclusionsRisk factors for excessive blood loss during and after TKA were determined, and a satisfactory and reliable nomogram model was designed to predict the risk for postoperative blood transfusion.

Indexed as

Arthroplasty, Replacement, KneeBlood Loss, SurgicalBlood TransfusionNomogramsAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk AssessmentRisk FactorsBlood lossNomogramPrediction modelRisk factorTotal knee arthroplasty

Identifiers

PMID38858713
PMCPMC11163717

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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.