Risk adjustment performance between NNIS index and NHSN model for postoperative colorectal surgical site infection: A retrospective cohort study

Sangsuwan, Tharntip; Jamulitrat, Silom; Watcharasin, Pattharapa

doi:10.1016/j.amsu.2022.103715

Cited by 4 publications

(6 citation statements)

References 18 publications

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“…The NNIS risk index is a widely recognized framework for assessing and predicting the likelihood of SSI. 9 Within our study, two elements of the NNIS exhibited statistical significance (operation duration and wound class). However, upon conducting multivariate analysis, the overall NNIS model did not yield statistical significance.…”

Section: Discussionmentioning

confidence: 52%

“…The ASA score, which reflects the patient's physical condition before the surgery, was determined through evaluation by the anesthesiologist using the ASA classification system. 9 The NNIS index considers three risk variables, each of which is worth one point: contaminated or dirty-infected surgical wound, ASA scores greater than 2, and operation length greater than T (where T is defined as the 75th percentile of the normal time for a surgical procedure). 9 The gastrointestinal cases were sorted into four categories (small bowel, large bowel, biliary, and pancreatic).…”

Section: Definitionsmentioning

confidence: 99%

“…9 The NNIS index considers three risk variables, each of which is worth one point: contaminated or dirty-infected surgical wound, ASA scores greater than 2, and operation length greater than T (where T is defined as the 75th percentile of the normal time for a surgical procedure). 9 The gastrointestinal cases were sorted into four categories (small bowel, large bowel, biliary, and pancreatic). 10 Leukocytosis was defined as a WBC count greater than 100 Â 10 9 /L and hypoalbuminemia was defined as an albumin <3.5 g/dL.…”

Section: Definitionsmentioning

confidence: 99%

“…The incidence of SSI was determined by evaluating and following up on all patients for 30 days following their surgery, by systematic visits, starting from the date of the operation. 9 It is important to note that medical complications such as pneumonia, MI, and UTI were separately documented and reported, and were not included in the definition of SSI or postoperative surgical complications. The secondary outcome was investigating the predictive factors for SSIs.…”

Section: Study Outcomesmentioning

confidence: 99%

“…The ROC curve (receiver operating characteristic curve) was utilized to evaluate the risk adjustment prediction performance of the previous NNIS risk index and the Author's model for post-gastrointestinal SSI, which contains the significant factors in multivariate analysis. 9…”

Section: Variables and Measuresmentioning

confidence: 99%

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Identification of predictive factors for surgical site infections in gastrointestinal surgeries: A retrospective cross-sectional study in a resource-limited setting

et al. 2023

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Background: Surgical site infection (SSI), albeit infrequent, drastically impact the quality of care. This article endeavors to investigate the predictive factors of SSIs following surgical interventions that involve the gastrointestinal (GI) tract within a single institution in a resource-limited setting. Methods: Over seven years from June 2015 to Oct 2022, patients who underwent GI surgery and developed SSI were retrospectively matched with an unaffected case-control cohort of patients. Standardized techniques for wound culture, laboratory evaluation of bacterial isolates, and antibiotic susceptibility tests were employed. Logistic regression analysis was utilized to investigate the predictive factors associated with 30-day postoperative SSI. Results: A total of 525 patients who underwent GI surgical procedures were included, among whom, 79 (15%) developed SSI. The majority of SSIs were superficial (67.10%), Escherichia coli was the most commonly isolated bacterium (54.4%), and a high percentage of multidrug-resistant organisms were observed (63.8%). In multivariate Cox regression analysis, illiteracy (Odds ratio [OR]:40.31; 95% confidence interval [CI]: 9.54-170.26), smoking (OR: 21.15; 95% CI: 4.63-96.67), diabetes (OR: 5.07; 95% CI: 2.27-11.35), leukocytosis (OR: 2.62; 95% CI: 1.24-5.53), hypoalbuminemia (OR: 3.70; 95% CI: 1.35-10.16), contaminated and dirty wounds (OR: 6.51; 95% CI:1.62-26.09), longer operative time (OR: 1.02; 95% CI: 1.01-1.03), emergency operations (OR: 12.58; 95% CI: 2.91-54.30), and extending antibiotic prophylaxis duration (OR: 3.01; 95% CI: 1.28-7.10) were the independent risk factors for SSI (all p < 0.05). Conclusions: This study highlights significant predictors of SSI, including illiteracy, smoking, diabetes, leukocytosis, hypoalbuminemia, contaminated and dirty wounds, longer operative time, emergency operations, and extending antibiotic prophylaxis duration. Identifying these risk factors can help surgeons adopt appropriate measures to reduce postoperative SSI and improve the quality of surgical care, especially in a resource-limited setting with no obvious and strict policy for reducing SSI.

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Section: Discussionmentioning

confidence: 52%

Section: Definitionsmentioning

confidence: 99%

Section: Definitionsmentioning

confidence: 99%

Section: Study Outcomesmentioning

confidence: 99%

Section: Variables and Measuresmentioning

confidence: 99%

See 3 more Smart Citations

Identification of predictive factors for surgical site infections in gastrointestinal surgeries: A retrospective cross-sectional study in a resource-limited setting

et al. 2023

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Prognostic models for surgical-site infection in gastrointestinal surgery: systematic review

McLean

Goel²,

Lawday

et al. 2023

British Journal of Surgery

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Background Identification of patients at high risk of surgical-site infection may allow clinicians to target interventions and monitoring to minimize associated morbidity. The aim of this systematic review was to identify and evaluate prognostic tools for the prediction of surgical-site infection in gastrointestinal surgery. Methods This systematic review sought to identify original studies describing the development and validation of prognostic models for 30-day SSI after gastrointestinal surgery (PROSPERO: CRD42022311019). MEDLINE, Embase, Global Health, and IEEE Xplore were searched from 1 January 2000 to 24 February 2022. Studies were excluded if prognostic models included postoperative parameters or were procedure specific. A narrative synthesis was performed, with sample-size sufficiency, discriminative ability (area under the receiver operating characteristic curve), and prognostic accuracy compared. Results Of 2249 records reviewed, 23 eligible prognostic models were identified. A total of 13 (57 per cent) reported no internal validation and only 4 (17 per cent) had undergone external validation. Most identified operative contamination (57 per cent, 13 of 23) and duration (52 per cent, 12 of 23) as important predictors; however, there remained substantial heterogeneity in other predictors identified (range 2–28). All models demonstrated a high risk of bias due to the analytic approach, with overall low applicability to an undifferentiated gastrointestinal surgical population. Model discrimination was reported in most studies (83 per cent, 19 of 23); however, calibration (22 per cent, 5 of 23) and prognostic accuracy (17 per cent, 4 of 23) were infrequently assessed. Of externally validated models (of which there were four), none displayed ‘good’ discrimination (area under the receiver operating characteristic curve greater than or equal to 0.7). Conclusion The risk of surgical-site infection after gastrointestinal surgery is insufficiently described by existing risk-prediction tools, which are not suitable for routine use. Novel risk-stratification tools are required to target perioperative interventions and mitigate modifiable risk factors.

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Identification of predictive factors for surgical site infections in gastrointestinal surgeries: A retrospective cross-sectional study in a resource-limited setting

Al-hajri,

Ghabisha,

Ahmed

et al. 2024

F1000Res

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Background Surgical site infection (SSI), albeit infrequent, drastically impacts the quality of care. This article endeavors to investigate the predictive factors of SSIs following surgical interventions that involve the gastrointestinal (GI) tract within a single institution in a resource-limited setting. Methods Over seven years from June 2015 to June 2022, patients who underwent GI surgery and developed SSI were retrospectively matched with an unaffected case-control cohort of patients. Standardized techniques for wound culture, laboratory evaluation of bacterial isolates, and antibiotic susceptibility tests were employed. Logistic regression analysis was utilized to investigate the predictive factors associated with 30-day postoperative SSI occurrence. Results A total of 525 patients who underwent GI surgical procedures were included, among whom, 86 (16.4%) developed SSI and the majority of SSIs were superficial (74.4%). Escherichia coli was the most commonly isolated bacterium (54.4%), and a high percentage of multidrug-resistant organisms were observed (63.8%). In multivariate Cox regression analysis, illiteracy (Odds ratio [OR]:40.31; 95% confidence interval [CI]: 9.54-170.26), smoking (OR: 21.15; 95% CI: 4.63-96.67), diabetes (OR: 5.07; 95% CI: 2.27-11.35), leukocytosis (OR: 2.62; 95% CI: 1.24-5.53), hypoalbuminemia (OR: 3.70; 95% CI: 1.35-10.16), contaminated and dirty wounds (OR: 6.51; 95% CI:1.62-26.09), longer operation duration (OR: 1.02; 95% CI: 1.01-1.03), emergency operations (OR: 12.58; 95% CI: 2.91-54.30), and extending antibiotic prophylaxis duration (OR: 3.01; 95% CI: 1.28-7.10) were the independent risk factors for SSI (all p < 0.05). Conclusions This study highlights significant predictors of SSI, including illiteracy, smoking, diabetes, leukocytosis, hypoalbuminemia, contaminated and dirty wounds, longer operative time, emergency operations, and extending antibiotic prophylaxis duration. Identifying these risk factors can help surgeons adopt appropriate measures to reduce postoperative SSI and improve the quality of surgical care, especially in a resource-limited setting with no obvious and strict policy for reducing SSI.

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Risk adjustment performance between NNIS index and NHSN model for postoperative colorectal surgical site infection: A retrospective cohort study

Cited by 4 publications

References 18 publications

Identification of predictive factors for surgical site infections in gastrointestinal surgeries: A retrospective cross-sectional study in a resource-limited setting

Identification of predictive factors for surgical site infections in gastrointestinal surgeries: A retrospective cross-sectional study in a resource-limited setting

Prognostic models for surgical-site infection in gastrointestinal surgery: systematic review

Identification of predictive factors for surgical site infections in gastrointestinal surgeries: A retrospective cross-sectional study in a resource-limited setting

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