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.
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.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Perioperative immune trajectories in severe scoliosis surgery: a retrospective study of 2,736 patients undergoing corrective surgery for severe scoliosis.Frontiers in immunology · 2026Article
- Identifying systemic vulnerability phenotypes associated with programmed regimens in frozen embryo transfer: a secondary analysis of a multicentre randomized clinical trial.Frontiers in medicine · 2026Article
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Authors and funding
5 authors.
Funding
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.
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