{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T17:03:08Z","timestamp":1789578188273,"version":"build-2803163510"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Surg Endosc"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Appendectomy is a leading pediatric surgical procedure, yet the impact of missing data handling on clinical conclusions remains unexplored in pediatric surgery. This study aimed to identify current reporting practices in the pediatric appendectomy literature and quantify how different missing-data strategies influence the identification of postoperative infectious-complication risk factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A systematic review of pediatric appendectomy literature from 2023 was conducted across PubMed and Web of Science to assess missing data reporting. Subsequently, a retrospective analysis of the National Surgical Quality Improvement Program-Pediatric (NSQIP-P) database (2015\u20132022) was performed on 142,129 cases. Five strategies were compared: available case analysis, threshold-based exclusion, complete case analysis, simple imputation, and multiple imputation. Multivariable logistic regression models identified risk factors for five infectious outcomes, including combined infectious complications, organ space infections, deep incisional infections, superficial surgical site infections, and wound dehiscence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The literature review identified 116 eligible articles, of which 54.3% failed to mention missing data. Only 7.3% used advanced statistical techniques, while 86.4% reported that a method relied on complete-case analysis. In the NSQIP-P cohort, 39.3% of records had missing values, primarily in height and race. While core predictors like American Society of Anesthesiologists (ASA) class and operative duration remained stable in multivariate logistic regression analysis, variables such as preoperative white blood cell count and anthropometric measurements fluctuated in significance depending on the handling method. Complete case analysis was the most conservative, identifying the fewest significant predictors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Methodological transparency regarding missing data is critically lacking in pediatric surgical research. Because the choice of data-handling strategy significantly alters the identification of clinical risk factors, researchers should prioritize multiple imputation over simple exclusion methods. Journals must mandate rigorous reporting of missingness to ensure the reliability of evidence-based surgical guidelines.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00464-026-13123-7","type":"journal-article","created":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T19:56:03Z","timestamp":1785182163000},"page":"8068-8080","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Missing data handling in pediatric appendectomy research: current practices and National Surgical Quality Improvement Program (NSQIP) analysis"],"prefix":"10.1007","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-6511-9666","authenticated-orcid":false,"given":"Ayaka","family":"Tsutsumi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tong","family":"Si","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joanne","family":"Salas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Hargrave","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grace","family":"Trello","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priya","family":"Reddy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Nash","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikita","family":"Kohli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shin","family":"Miyata","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,27]]},"reference":[{"key":"13123_CR1","unstructured":"Barrett ML, Hines AL, Andrews RM (2013) Trends in rates of perforated appendix, 2001\u20132010: statistical brief #159. 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