ArticleHand (New York, N.Y.)2022
Impact of Missing Data on Identifying Risk Factors for Postoperative Complications in Hand Surgery.
Article in Hand (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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.
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.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Missing data handling in pediatric appendectomy research: current practices and National Surgical Quality Improvement Program (NSQIP) analysis.Surgical endoscopy · 2026Pooled it
- Risk analysis index demonstrates superior predictive performance compared to traditional frailty metrics in elderly female patients undergoing inpatient total shoulder arthroplasty.Arthroplasty (London, England) · 2026Article
- The Modified Five-Item Frailty Index to Predict Hand and Wrist Surgical Repair Postoperative Outcomes: An ACS-NSQIP Analysis of 11 369 Patients.Hand (New York, N.Y.) · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe mismanagement of missing data in large clinical databases may lead to inaccurate findings. The purpose of this study was to demonstrate the effects of missing data on hand surgery research findings using an analysis of postoperative morbidity in patients undergoing hospital-based hand surgery.
methodsThe National Surgical Quality Improvement Program database was queried for patients undergoing common hand and upper extremity surgery between 2011 and 2016. Major and minor postoperative complications were identified. Demographics, comorbidity, and preoperative laboratory values were identified, and the percentage missing of each was tabulated. To demonstrate how missing data can alter analysis results, these variables were evaluated for an association with major complications using multivariable regression on 3 separate cohorts: (1) all patients; (2) all patients after exclusion of any patient entry with >10% of missing data; and (3) after removal of any patient entry with any missing data.
resultsGroups 1, 2, and 3 had 48 370, 23 118, and 6280 patients, respectively. There were 14 variables associated with increased odds of major complications in group 1, yet only 10 and 9 variables for groups 2 and 3, respectively. Six variables were associated with increased major complications across all 3 groups, whereas only 1 was associated with decreased odds of major complications across all groups.
conclusionsFiltering patient cohorts according to the amount of missing patient information affected analyses of predictors for major complications associated with hospital-based hand surgery. These findings highlight the importance of considering and addressing missing data in large database studies.
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