A clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the NHSN/SIR risk model: a multicenter case–control study
IntroductionSurgical site infection (SSI) is one of the most common surgical-related complications worldwide, particularly in developing countries. SSI is responsible for mortality, long hospitalization period, and a high economic burden.MethodThis hospital-based case–control study was conducted in...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Surgery |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fsurg.2023.1189220/full |
| _version_ | 1827813818105856000 |
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| author | Niloufar Taherpour Niloufar Taherpour Yadollah Mehrabi Arash Seifi Seyed Saeed Hashemi Nazari Seyed Saeed Hashemi Nazari |
| author_facet | Niloufar Taherpour Niloufar Taherpour Yadollah Mehrabi Arash Seifi Seyed Saeed Hashemi Nazari Seyed Saeed Hashemi Nazari |
| author_sort | Niloufar Taherpour |
| collection | DOAJ |
| description | IntroductionSurgical site infection (SSI) is one of the most common surgical-related complications worldwide, particularly in developing countries. SSI is responsible for mortality, long hospitalization period, and a high economic burden.MethodThis hospital-based case–control study was conducted in six educational hospitals in Tehran, Iran. A total of 244 patients at the age of 18–85 years who had undergone open reduction and internal fixation (ORIF) surgery were included in this study. Among the 244 patients, 122 patients who developed SSIs were selected to be compared with 122 non-infected patients used as controls. At the second stage, all patients (n = 350) who underwent ORIF surgery in a hospital were selected for an estimation of the standardized infection ratio (SIR). A logistic regression model was used for predicting the most important factors associated with the occurrence of SSIs. Finally, the performance of the ORIF prediction model was evaluated using discrimination and calibration indices. Data were analyzed using R.3.6.2 and STATA.14 software.ResultsKlebsiella (14.75%) was the most frequently detected bacterium in SSIs following ORIF surgery. The results revealed that the most important factors associated with SSI following an ORIF procedure were found to be elder age, elective surgery, prolonged operation time, American Society of Anesthesiologists score of ≥2, class 3 and 4 wound, and preoperative blood glucose levels of >200 mg/dl; while preoperative higher hemoglobin level (g/dl) was found to be a protective factor. The evidence for the interaction effect between age and gender, body mass index and gender, and age and elective surgery were also observed. After assessing the internal validity of the model, the overall performance of the models was found to be good with an area under the curve of 95%. The SIR of SSI for ORIF surgery in the selected hospital was 0.66 among the patients aged 18–85 years old.ConclusionNew risk prediction models can help in detecting high-risk patients and monitoring the infection rate in hospitals based on their infection prevention and control programs. Physicians using prediction models can identify high-risk patients with these factors prior to ORIF procedure. |
| first_indexed | 2024-03-11T23:37:25Z |
| format | Article |
| id | doaj.art-ecd3f892a494431cae3c1afb9828a858 |
| institution | Directory Open Access Journal |
| issn | 2296-875X |
| language | English |
| last_indexed | 2024-03-11T23:37:25Z |
| publishDate | 2023-09-01 |
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| series | Frontiers in Surgery |
| spelling | doaj.art-ecd3f892a494431cae3c1afb9828a8582023-09-19T21:51:21ZengFrontiers Media S.A.Frontiers in Surgery2296-875X2023-09-011010.3389/fsurg.2023.11892201189220A clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the NHSN/SIR risk model: a multicenter case–control studyNiloufar Taherpour0Niloufar Taherpour1Yadollah Mehrabi2Arash Seifi3Seyed Saeed Hashemi Nazari4Seyed Saeed Hashemi Nazari5Infectious Diseases and Tropical Medicine Research Center, Shahid Beheshti University of Medical Sciences, Tehran, IranDepartment of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, IranDepartment of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, IranDepartment of Infectious Diseases, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, IranInfectious Diseases and Tropical Medicine Research Center, Shahid Beheshti University of Medical Sciences, Tehran, IranPrevention of Cardiovascular Disease Research Center, Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, IranIntroductionSurgical site infection (SSI) is one of the most common surgical-related complications worldwide, particularly in developing countries. SSI is responsible for mortality, long hospitalization period, and a high economic burden.MethodThis hospital-based case–control study was conducted in six educational hospitals in Tehran, Iran. A total of 244 patients at the age of 18–85 years who had undergone open reduction and internal fixation (ORIF) surgery were included in this study. Among the 244 patients, 122 patients who developed SSIs were selected to be compared with 122 non-infected patients used as controls. At the second stage, all patients (n = 350) who underwent ORIF surgery in a hospital were selected for an estimation of the standardized infection ratio (SIR). A logistic regression model was used for predicting the most important factors associated with the occurrence of SSIs. Finally, the performance of the ORIF prediction model was evaluated using discrimination and calibration indices. Data were analyzed using R.3.6.2 and STATA.14 software.ResultsKlebsiella (14.75%) was the most frequently detected bacterium in SSIs following ORIF surgery. The results revealed that the most important factors associated with SSI following an ORIF procedure were found to be elder age, elective surgery, prolonged operation time, American Society of Anesthesiologists score of ≥2, class 3 and 4 wound, and preoperative blood glucose levels of >200 mg/dl; while preoperative higher hemoglobin level (g/dl) was found to be a protective factor. The evidence for the interaction effect between age and gender, body mass index and gender, and age and elective surgery were also observed. After assessing the internal validity of the model, the overall performance of the models was found to be good with an area under the curve of 95%. The SIR of SSI for ORIF surgery in the selected hospital was 0.66 among the patients aged 18–85 years old.ConclusionNew risk prediction models can help in detecting high-risk patients and monitoring the infection rate in hospitals based on their infection prevention and control programs. Physicians using prediction models can identify high-risk patients with these factors prior to ORIF procedure.https://www.frontiersin.org/articles/10.3389/fsurg.2023.1189220/fullsurgical site infectionORIF surgeryprediction modelstandardized infection rationosocomial infection |
| spellingShingle | Niloufar Taherpour Niloufar Taherpour Yadollah Mehrabi Arash Seifi Seyed Saeed Hashemi Nazari Seyed Saeed Hashemi Nazari A clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the NHSN/SIR risk model: a multicenter case–control study Frontiers in Surgery surgical site infection ORIF surgery prediction model standardized infection ratio nosocomial infection |
| title | A clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the NHSN/SIR risk model: a multicenter case–control study |
| title_full | A clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the NHSN/SIR risk model: a multicenter case–control study |
| title_fullStr | A clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the NHSN/SIR risk model: a multicenter case–control study |
| title_full_unstemmed | A clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the NHSN/SIR risk model: a multicenter case–control study |
| title_short | A clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the NHSN/SIR risk model: a multicenter case–control study |
| title_sort | clinical prediction model for predicting the surgical site infection after an open reduction and internal fixation procedure considering the nhsn sir risk model a multicenter case control study |
| topic | surgical site infection ORIF surgery prediction model standardized infection ratio nosocomial infection |
| url | https://www.frontiersin.org/articles/10.3389/fsurg.2023.1189220/full |
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