The role of preoperative albumin and white blood cell count in surgical site infections following whipple surgery

Tfaily, Mohamad Ali; Ghanem, Paola; Farran, Sarah; Dabdoub, Fatema; Kanafani, Zeina A.

doi:10.1038/s41598-022-21849-2

Cited by 9 publications

(8 citation statements)

References 56 publications

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“…In the present study, multivariable logistic regression analysis for abdominal surgery revealed that age, chronic liver disease, bowel preparation, colon surgery, pancreatic surgery, preoperative albumin level, surgical wound class, surgical approach, and colostomy/ileostomy at the end of surgery were associated with SSI following abdominal surgery. The roles of age, colon surgery, pancreatic surgery, preoperative albumin level, surgical wound class, surgical approach, and stoma in SSI are well known 17–19 . Moreover, there was an increased risk of SSI in patients with chronic liver disease after abdominal surgery.…”

Section: Discussionmentioning

confidence: 99%

“…The roles of age, colon surgery, pancreatic surgery, preoperative albumin level, surgical wound class, surgical approach, and stoma in SSI are well known. [17][18][19] Moreover, there was an increased risk of SSI in patients with chronic liver disease after abdominal surgery. In the present study, chronic hepatic dysfunction included abnormal liver enzyme concentrations, hepatocellular carcinoma, cirrhosis, and hepatitis.…”

Section: Latent Class Analysismentioning

confidence: 99%

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Identification of Risk Factors and Phenotypes of Surgical Site Infection in Patients After Abdominal Surgery

et al. 2023

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Objectives: We aimed to determine the current incidence rate and risk factors for surgical site infection (SSI) after abdominal surgery in China and to further demonstrate the clinical features of patients with SSI. Background: Contemporary epidemiology and clinical features of SSI after abdominal surgery remain poorly characterized. Methods: A prospective multicenter cohort study was conducted from March 2021 to February 2022; the study included patients who underwent abdominal surgery at 42 hospitals in China. Multivariable logistic regression analysis was performed to identify risk factors for SSI. Latent class analysis (LCA) was used to explore the population characteristics of SSI. Results: In total, 23,982 patients were included in the study, of whom 1.8% developed SSI. There was a higher SSI incidence in open surgery (5.0%) than in laparoscopic or robotic surgeries (0.9%). Multivariable logistic regression indicated that the independent risk factors for SSI after abdominal surgery were older age, chronic liver disease, mechanical bowel preparation, oral antibiotic bowel preparation, colon or pancreas surgery, contaminated or dirty wounds, open surgery, and colostomy-/ileostomy. LCA revealed 4 subphenotypes in patients undergoing abdominal surgery. Types α and β were mild subclasses with a lower SSI incidence; whereas types γ and δ were the critical subgroups with a higher SSI incidence, but their clinical features were different.Conclusions: LCA identified 4 subphenotypes in patients who underwent abdominal surgery. Types γ and δ were critical subgroups with a higher SSI incidence. This phenotype classification can be used to predict SSI after abdominal surgery.

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Section: Discussionmentioning

confidence: 99%

Section: Latent Class Analysismentioning

confidence: 99%

Identification of Risk Factors and Phenotypes of Surgical Site Infection in Patients After Abdominal Surgery

et al. 2023

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“…6,11 In addition, leukocytosis was found to be a predictor for the development of SSI, which aligns with previous research. 31 Additionally, prolonged operation duration was recognized as an independent factor for SSI development in other studies, as it increases the risk of infection due to extensive surgical procedures and incisions, prolonged anesthesia, blood loss, and weaning antimicrobial prophylaxis concentration. 6,32 Furthermore, administering antibiotics one hour before operation has been reported as a predictor for SSI in previous studies.…”

Section: Discussionmentioning

confidence: 99%

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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“…All methods were carried out in accordance with the World Medical Association Declaration of Helsinki 19 . Institutional research ethics board review and informed patient consent were not required as the data came from a large, deidentified registry, which is an accepted practice for studies based on ACS NSQIP data 20 .…”

Section: Methodsmentioning

confidence: 99%

Predicting outcomes following lower extremity open revascularization using machine learning

Li,

Verma,

Beaton

et al. 2024

Sci Rep

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Lower extremity open revascularization is a treatment option for peripheral artery disease that carries significant peri-operative risks; however, outcome prediction tools remain limited. Using machine learning (ML), we developed automated algorithms that predict 30-day outcomes following lower extremity open revascularization. The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent lower extremity open revascularization for chronic atherosclerotic disease between 2011 and 2021. Input features included 37 pre-operative demographic/clinical variables. The primary outcome was 30-day major adverse limb event (MALE; composite of untreated loss of patency, major reintervention, or major amputation) or death. Our data were split into training (70%) and test (30%) sets. Using tenfold cross-validation, we trained 6 ML models. Overall, 24,309 patients were included. The primary outcome of 30-day MALE or death occurred in 2349 (9.3%) patients. Our best performing prediction model was XGBoost, achieving an area under the receiver operating characteristic curve (95% CI) of 0.93 (0.92–0.94). The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.08. Our ML algorithm has potential for important utility in guiding risk mitigation strategies for patients being considered for lower extremity open revascularization to improve outcomes.

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The role of preoperative albumin and white blood cell count in surgical site infections following whipple surgery

Cited by 9 publications

References 56 publications

Identification of Risk Factors and Phenotypes of Surgical Site Infection in Patients After Abdominal Surgery

Identification of Risk Factors and Phenotypes of Surgical Site Infection in Patients After Abdominal Surgery

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

Predicting outcomes following lower extremity open revascularization using machine learning

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