A dynamic nomogram predicting nosocomial infections in patients after colon cancer surgery
ObjectiveNosocomial infections are one of the severe postoperative complications that compromise perioperative safety in patients with colon cancer. However, there are limited studies on constructing visual risk prediction screening tools for nosocomial infections in these patients. The objective of...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1528036/full |
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| author | Xue Yao Shuhui Wang Anning Lu Yun Xu Na Li |
| author_facet | Xue Yao Shuhui Wang Anning Lu Yun Xu Na Li |
| author_sort | Xue Yao |
| collection | DOAJ |
| description | ObjectiveNosocomial infections are one of the severe postoperative complications that compromise perioperative safety in patients with colon cancer. However, there are limited studies on constructing visual risk prediction screening tools for nosocomial infections in these patients. The objective of this study is to construct a nomogram for predicting the risk of nosocomial infections among patients after colon cancer surgery.MethodsTotal 1146 patients after colon cancer surgery were selected and divided into a training set and a validation set. After identifying the most significant predictors through LASSO regression and logistic regression, the model was presented as static and dynamic nomogram. AUC was used to evaluate the discrimination of model. Calibration was evaluated by means of calibration curves. Decision and impact curves were applied to evaluate the clinical validity.Results110 patients (9.60%) suffered nosocomial infections following colon cancer surgery. Peak temperature on the second postoperative day, Braden score on the first postoperative day, duration of retention of abdominal drains, ASA class, surgical type and postoperative complications were correlated with nosocomial infections. The nomogram composed of these predictors demonstrated good discrimination, calibration and clinical benefit in both the training and validation sets.ConclusionRisk predictors are important breakthroughs for healthcare workers in nosocomial infections prevention and control initiatives. The dynamic nomogram built in this study may be helpful for healthcare personnel to identify the risk of nosocomial infections among patients after colon cancer surgery. |
| format | Article |
| id | doaj-art-e3dede43c8964e049ee02093f8a232f6 |
| institution | DOAJ |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj-art-e3dede43c8964e049ee02093f8a232f62025-08-20T02:55:02ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-02-011510.3389/fonc.2025.15280361528036A dynamic nomogram predicting nosocomial infections in patients after colon cancer surgeryXue Yao0Shuhui Wang1Anning Lu2Yun Xu3Na Li4Department of Joint Surgery, Weifang People’s Hospital, Weifang, Shandong, ChinaDepartment of Infection Prevention and Control, Qilu Hospital of Shandong University, Jinan, Shandong, ChinaSchool of Nursing, Shandong Second Medical University, Weifang, Shandong, ChinaDepartment of Joint Surgery, Weifang People’s Hospital, Weifang, Shandong, ChinaDepartment of Joint Surgery, Weifang People’s Hospital, Weifang, Shandong, ChinaObjectiveNosocomial infections are one of the severe postoperative complications that compromise perioperative safety in patients with colon cancer. However, there are limited studies on constructing visual risk prediction screening tools for nosocomial infections in these patients. The objective of this study is to construct a nomogram for predicting the risk of nosocomial infections among patients after colon cancer surgery.MethodsTotal 1146 patients after colon cancer surgery were selected and divided into a training set and a validation set. After identifying the most significant predictors through LASSO regression and logistic regression, the model was presented as static and dynamic nomogram. AUC was used to evaluate the discrimination of model. Calibration was evaluated by means of calibration curves. Decision and impact curves were applied to evaluate the clinical validity.Results110 patients (9.60%) suffered nosocomial infections following colon cancer surgery. Peak temperature on the second postoperative day, Braden score on the first postoperative day, duration of retention of abdominal drains, ASA class, surgical type and postoperative complications were correlated with nosocomial infections. The nomogram composed of these predictors demonstrated good discrimination, calibration and clinical benefit in both the training and validation sets.ConclusionRisk predictors are important breakthroughs for healthcare workers in nosocomial infections prevention and control initiatives. The dynamic nomogram built in this study may be helpful for healthcare personnel to identify the risk of nosocomial infections among patients after colon cancer surgery.https://www.frontiersin.org/articles/10.3389/fonc.2025.1528036/fullcolon cancernosocomial infectionspredictionnomogrammodel |
| spellingShingle | Xue Yao Shuhui Wang Anning Lu Yun Xu Na Li A dynamic nomogram predicting nosocomial infections in patients after colon cancer surgery Frontiers in Oncology colon cancer nosocomial infections prediction nomogram model |
| title | A dynamic nomogram predicting nosocomial infections in patients after colon cancer surgery |
| title_full | A dynamic nomogram predicting nosocomial infections in patients after colon cancer surgery |
| title_fullStr | A dynamic nomogram predicting nosocomial infections in patients after colon cancer surgery |
| title_full_unstemmed | A dynamic nomogram predicting nosocomial infections in patients after colon cancer surgery |
| title_short | A dynamic nomogram predicting nosocomial infections in patients after colon cancer surgery |
| title_sort | dynamic nomogram predicting nosocomial infections in patients after colon cancer surgery |
| topic | colon cancer nosocomial infections prediction nomogram model |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1528036/full |
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