Individualized risk of surgical-site infection: an application of the breast reconstruction risk assessment score

John Y.S. Kim; Nima Khavanin; Sumanas W. Jordan; Jon P. ver Halen; Alexei S. Mlodinow; Kevin P. Bethke; Seema A. Khan; Nora M. Hansen; Albert Losken; Neil A Fine

doi:10.1097/PRS.0000000000000439

Individualized risk of surgical-site infection: an application of the breast reconstruction risk assessment score

John Y.S. Kim, Nima Khavanin, Sumanas W. Jordan, Jon P. ver Halen, Alexei S. Mlodinow, Kevin P. Bethke, Seema A. Khan, Nora M. Hansen, Albert Losken, Neil A Fine

Research output: Contribution to journal › Article › peer-review

33 Scopus citations

Abstract

BACKGROUND: Risk factors for surgical-site infection following beast reconstruction have been thoroughly investigated at a population level. However, traditional population-based measures may not always capture the nuances of individual patients. The authors aimed to develop a validated breast reconstruction risk assessment calculator for surgical-site infection that informs risk at an individual level.

METHODS: Mastectomies with immediate reconstruction (n = 16,069) from 2005 to 2011 were identified from the National Surgical Quality Improvement Program database. A multiple logistic regression model was created for postoperative surgical-site infection. Hosmer-Lemeshow, C statistic, and Brier score were computed to assess model performance. Bootstrap analysis validated the model.

RESULTS: A robust, validated risk model for surgical-site infection was developed using 11 covariates. The model Hosmer-Lemeshow p value was 0.371, the Brier score was 0.0357, and the C statistic was 0.682 (optimism-corrected C statistic, 0.678). The distribution of individual risks demonstrated a positive skew. Population-derived risk underestimated or overestimated individual risk by at least 1.5-fold in nearly one-fifth of all patients.

CONCLUSIONS: The breast reconstruction risk assessment score risk calculator for surgical-site infection mitigates the potentially inaccurate interpolation of population-based risk to individual patients. The authors concomitantly developed an online interface-accessible by patients and surgeons alike-to quantify a patient's risk for surgical-site infection, better informing evidence-based decisions and managing patient expectations.

CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.

Original language	English (US)
Pages (from-to)	351e-362e
Journal	Plastic and reconstructive surgery
Volume	134
Issue number	3
DOIs	https://doi.org/10.1097/PRS.0000000000000439
State	Published - Sep 1 2014

ASJC Scopus subject areas

Surgery

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10.1097/PRS.0000000000000439

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Kim, J. Y. S., Khavanin, N., Jordan, S. W., ver Halen, J. P., Mlodinow, A. S., Bethke, K. P., Khan, S. A., Hansen, N. M., Losken, A., & Fine, N. A. (2014). Individualized risk of surgical-site infection: an application of the breast reconstruction risk assessment score. Plastic and reconstructive surgery, 134(3), 351e-362e. https://doi.org/10.1097/PRS.0000000000000439

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abstract = "BACKGROUND: Risk factors for surgical-site infection following beast reconstruction have been thoroughly investigated at a population level. However, traditional population-based measures may not always capture the nuances of individual patients. The authors aimed to develop a validated breast reconstruction risk assessment calculator for surgical-site infection that informs risk at an individual level.METHODS: Mastectomies with immediate reconstruction (n = 16,069) from 2005 to 2011 were identified from the National Surgical Quality Improvement Program database. A multiple logistic regression model was created for postoperative surgical-site infection. Hosmer-Lemeshow, C statistic, and Brier score were computed to assess model performance. Bootstrap analysis validated the model.RESULTS: A robust, validated risk model for surgical-site infection was developed using 11 covariates. The model Hosmer-Lemeshow p value was 0.371, the Brier score was 0.0357, and the C statistic was 0.682 (optimism-corrected C statistic, 0.678). The distribution of individual risks demonstrated a positive skew. Population-derived risk underestimated or overestimated individual risk by at least 1.5-fold in nearly one-fifth of all patients.CONCLUSIONS: The breast reconstruction risk assessment score risk calculator for surgical-site infection mitigates the potentially inaccurate interpolation of population-based risk to individual patients. The authors concomitantly developed an online interface-accessible by patients and surgeons alike-to quantify a patient's risk for surgical-site infection, better informing evidence-based decisions and managing patient expectations.CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.",

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doi = "10.1097/PRS.0000000000000439",

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AU - Kim, John Y.S.

AU - Khavanin, Nima

AU - Jordan, Sumanas W.

AU - ver Halen, Jon P.

AU - Mlodinow, Alexei S.

AU - Bethke, Kevin P.

AU - Khan, Seema A.

AU - Hansen, Nora M.

AU - Losken, Albert

AU - Fine, Neil A

PY - 2014/9/1

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N2 - BACKGROUND: Risk factors for surgical-site infection following beast reconstruction have been thoroughly investigated at a population level. However, traditional population-based measures may not always capture the nuances of individual patients. The authors aimed to develop a validated breast reconstruction risk assessment calculator for surgical-site infection that informs risk at an individual level.METHODS: Mastectomies with immediate reconstruction (n = 16,069) from 2005 to 2011 were identified from the National Surgical Quality Improvement Program database. A multiple logistic regression model was created for postoperative surgical-site infection. Hosmer-Lemeshow, C statistic, and Brier score were computed to assess model performance. Bootstrap analysis validated the model.RESULTS: A robust, validated risk model for surgical-site infection was developed using 11 covariates. The model Hosmer-Lemeshow p value was 0.371, the Brier score was 0.0357, and the C statistic was 0.682 (optimism-corrected C statistic, 0.678). The distribution of individual risks demonstrated a positive skew. Population-derived risk underestimated or overestimated individual risk by at least 1.5-fold in nearly one-fifth of all patients.CONCLUSIONS: The breast reconstruction risk assessment score risk calculator for surgical-site infection mitigates the potentially inaccurate interpolation of population-based risk to individual patients. The authors concomitantly developed an online interface-accessible by patients and surgeons alike-to quantify a patient's risk for surgical-site infection, better informing evidence-based decisions and managing patient expectations.CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.

AB - BACKGROUND: Risk factors for surgical-site infection following beast reconstruction have been thoroughly investigated at a population level. However, traditional population-based measures may not always capture the nuances of individual patients. The authors aimed to develop a validated breast reconstruction risk assessment calculator for surgical-site infection that informs risk at an individual level.METHODS: Mastectomies with immediate reconstruction (n = 16,069) from 2005 to 2011 were identified from the National Surgical Quality Improvement Program database. A multiple logistic regression model was created for postoperative surgical-site infection. Hosmer-Lemeshow, C statistic, and Brier score were computed to assess model performance. Bootstrap analysis validated the model.RESULTS: A robust, validated risk model for surgical-site infection was developed using 11 covariates. The model Hosmer-Lemeshow p value was 0.371, the Brier score was 0.0357, and the C statistic was 0.682 (optimism-corrected C statistic, 0.678). The distribution of individual risks demonstrated a positive skew. Population-derived risk underestimated or overestimated individual risk by at least 1.5-fold in nearly one-fifth of all patients.CONCLUSIONS: The breast reconstruction risk assessment score risk calculator for surgical-site infection mitigates the potentially inaccurate interpolation of population-based risk to individual patients. The authors concomitantly developed an online interface-accessible by patients and surgeons alike-to quantify a patient's risk for surgical-site infection, better informing evidence-based decisions and managing patient expectations.CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.

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Individualized risk of surgical-site infection: an application of the breast reconstruction risk assessment score

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