Evidence map›Paper›PMID 41830434›Full record

ArticleEuropean journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery2026

Use of Inverse Probability Weighting in Cardiovascular Surgical Outcomes Research: Principles, Limitations, and Recommendations.

Zhongjian Liu, Wei-Guo Ma, Lei Liu, Prashanth Vallabhajosyula, Haibo Wang

Abstract read
In one paragraph

Article in European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Zhongjian LiuPeking University First Hospital, Peking University, Beijing 100034, China.
Wei-Guo MaDivision of Cardiac Surgery, Yale University School of Medicine, New Haven, CT 06519, United States.ORCID 0000-0003-3873-0837
Lei LiuDivision of Biostatistics, Washington University in St. Louis, St. Louis, MO 63110, United States.ORCID 0000-0003-1844-338X
Prashanth VallabhajosyulaDivision of Cardiac Surgery, Yale University School of Medicine, New Haven, CT 06519, United States.
Haibo WangClinical Research Institute/Institute of Advanced Clinical Medicine, Key Laboratory of Epidemiology of Major Diseases, Peking University, Beijing 100191, China.

Funding

National Major Science and Technology Major Projects 2021ZD0200600
6 · The paper itself

Abstract

This statistical primer presents a comprehensive introduction to the use of inverse probability of treatment weighting (IPTW), a method for rebalancing group confounders at baseline in cardiovascular surgical outcomes research. We leveraged a retrospective study comparing the outcomes of 2 different surgical approaches to aortic arch pathology to illustrate the essential aspects of performing IPTW, including basic theories, application, extreme weights, underestimated variance, heterogeneity of treatment effect, and multicollinearity. The limitations of IPTW were discussed with examples of solutions. Ten practical recommendations are made on avoiding the pitfalls in the use of IPTW. Proper use of IPTW may effectively reduce confounding bias by balancing confounders between different groups at baseline, retain a relatively large sample size, and allow for integration with other statistical methods. However, it is crucial to be fully aware of its limitations and carefully select appropriate methods to avoid improper use and data misinterpretation in cardiovascular outcomes research.

Indexed as

Cardiovascular Surgical ProceduresOutcome Assessment, Health CareAorta, ThoracicHumansProbabilityPropensity ScoreRetrospective Studiesconfounding factorinverse probability of treatment weightingoutcomes researchpropensity score

Identifiers

PMID41830434
PMCPMC13070700

What OpenQuestion holds

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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.