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Detection of clinically important colorectal surgical site infection using Bayesian network.

ABSTRACT: BACKGROUND:Despite extensive efforts to monitor and prevent surgical site infections (SSIs), real-time surveillance of clinical practice has been sparse and expensive or nonexistent. However, natural language processing (NLP) and machine learning (i.e., Bayesian network analysis) may provide the methodology necessary to approach this issue in a new way. We investigated the ability to identify SSIs after colorectal surgery (CRS) through an automated detection system using a Bayesian network. MATERIALS AND METHODS:Patients who underwent CRS from 2010 to 2012 and were captured in our institutional American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) comprised our cohort. A Bayesian network was applied to detect SSIs using risk factors from ACS-NSQIP data and keywords extracted from clinical notes by NLP. Two surgeons provided expertise informing the Bayesian network to identify clinically meaningful SSIs (CM-SSIs) occurring within 30 d after surgery. RESULTS:We used data from 751 CRS cases experiencing 67 (8.9%) SSIs and 78 (10.4%) CM-SSIs. Our Bayesian network detected ACS-NSQIP-captured SSIs with a receiver operating characteristic area under the curve of 0.827, but this value increased to 0.892 when using surgeon-identified CM-SSIs. CONCLUSIONS:A Bayesian network coupled with NLP has the potential to be used in real-time SSI surveillance. Moreover, surgeons identified CM-SSI not captured under current NSQIP definitions. Future efforts to expand CM-SSI identification may lead to improved and potentially automated approaches to survey for postoperative SSI in clinical practice.

SUBMITTER: Sohn S

PROVIDER: S-EPMC5391146 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Detection of clinically important colorectal surgical site infection using Bayesian network.

Sohn Sunghwan S Larson David W DW Habermann Elizabeth B EB Naessens James M JM Alabbad Jasim Y JY Liu Hongfang H

The Journal of surgical research 20161005

<h4>Background</h4>Despite extensive efforts to monitor and prevent surgical site infections (SSIs), real-time surveillance of clinical practice has been sparse and expensive or nonexistent. However, natural language processing (NLP) and machine learning (i.e., Bayesian network analysis) may provide the methodology necessary to approach this issue in a new way. We investigated the ability to identify SSIs after colorectal surgery (CRS) through an automated detection system using a Bayesian netwo ...[more]

PMID: 28032554

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Project description:ImportanceThere has been a resurgence of interest in the use of mechanical bowel preparation (MBP) and oral antibiotics (OAB) before elective colorectal surgery. Until now, clinical trials and meta-analyses have not compared all 4 approaches (MBP with OAB, OAB only, MBP only, or no preparation) simultaneously.ObjectiveTo perform a network meta-analysis to clarify which approach in colorectal surgery is associated with the lowest rate of surgical site infection (SSI).Data sourcesFive electronic databases were searched, including PubMed, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, ACP Journal Club. and Database of Abstracts of Review of Effectiveness from database inception to November 27, 2017.Study selectionOnly data from randomized clinical trials were included. Inclusion criteria were RCTs that reported on SSI rates or other complications based on MBP or OAB status. Quality of studies was appraised by the Cochrane Collaboration risk of bias tool.Data extraction and synthesisThe study was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.Main outcomes and measuresTotal, incisional, and organ/space SSI rates. Secondary outcomes included rates of anastomotic leak, mortality, readmissions/reoperations, urinary tract infection, and pulmonary complications.ResultsThirty-eight randomized clinical trials among 8458 patients (52.1% male) were included, providing 4 direct comparisons and 2 indirect comparisons for 8 outcome measures. On Bayesian analysis, MBP with OAB vs MBP only was associated with reduced SSI (odds ratio [OR], 0.71; 95% equal-tail credible interval [CrI], 0.57-0.88). There was no significant difference between MBP with OAB vs OAB only (OR, 0.95; 95% CrI, 0.56-1.62). Oral antibiotics without MBP was not associated with a statistically significant reduction in SSI compared with any other group (except for a risk reduction in organ/space SSI when indirectly compared with no preparation) (OR, 0.13; 95% CrI, 0.02-0.55). There was no difference in SSI between MBP only vs no preparation (OR, 0.84; 95% CrI, 0.69-1.02).Conclusions and relevanceIn this network meta-analysis of randomized clinical trials, MBP with OAB was associated with the lowest risk of SSI. Oral antibiotics only was ranked as second best, but the data available on this approach were limited. There was no difference between MBP only vs no preparation. In addition, there was no difference in rates of anastomotic leak, readmissions, or reoperations between any groups.

Project description:ObjectiveTo assess the relative contribution of intravenous antibiotic prophylaxis, mechanical bowel preparation, oral antibiotic prophylaxis, and combinations thereof towards the reduction of surgical site infection (SSI) incidence in elective colorectal resections.Methods and analysisA systematic search of randomised controlled trials comparing interventions to reduce SSI incidence will be conducted with predefined search terms in the following databases: MEDLINE, LILACS, Cochrane Central Register of Controlled Trials (CENTRAL) and the Cochrane Database of Systematic Reviews (CDSR). Additionally, several online databases will be searched for ongoing trials, and conference proceedings and reference lists of retrieved articles will be hand searched. The title-abstract screening will be partly performed by means of a semiautomated supervised machine learning approach, which will be trained on a subset of the identified titles and abstracts identified through traditional screening methods.The primary analysis will be a multicomponent network meta-analysis, as we expect to identify studies that investigate combinations of interventions (eg, mechanical bowel preparation combined with oral antibiotics) as well as studies that focus on individual components (mechanical bowel preparation or oral antibiotics). By means of a multicomponent network meta-analysis, we aim at estimating the effects of the separate components along the effects of the observed combinations. To account for between-trial heterogeneity, a random-effect approach will be combined with inverse variance weighting for estimation of the treatment effects. Associated 95% CIs will be calculated as well as the ranking for each component in the network using P scores. Results will be visualised by network graphics and forest plots of the overall pairwise effect estimates. Comparison-adjusted funnel plots will be used to assess publication bias.Ethics and disseminationEthical approval by the Ethical Committee of the Medical Faculty of the Martin-Luther-University Halle-Wittenberg (ID of approval: 2021-148). Results shall be disseminated directly to decision-makers (eg, surgeons, gastroenterologists, wound care specialists) by means of publication in peer-reviewed journals, presentation at conferences and through the media (eg, radio, TV, etc).Prospero registration numberCRD42021267322.

Project description:BACKGROUND:A surgical site infection (SSI) is a major post-operative complication from elective colorectal surgery; however, few studies have focused on evaluating the risk factors for SSI. This study aimed to analyze the relative correlation of medical and environmental factors as well as patient-related factors that contribute to the incidence of all types of SSI. METHODS:A retrospective search for eligible patients was conducted using the patient database of the Gastrointestinal Surgery Center of the Third Affiliated Hospital of Sun Yat-sen University from January 2011 to August 2017. Pre-operative demographic and surgical data were extracted and recoded according to the study protocol. Univariate and multivariate analyses were performed to clarify factors affecting the incidence of SSI. Propensity analysis was conducted to minimize bias in the demographic characteristics to explore the prophylactic effect of pre-operative administration of oral antibiotics. RESULTS:Univariate analysis of the baseline characteristics revealed that younger age (odds ratio [OR]: 0.378; 95% confidence interval [CI]: 0.218-0.657) and pre-operative oral antibiotic use (OR: 0.465; 95% CI: 0.255-0.850) were protective factors, while pre-operative anemia (OR: 4.591; 95% CI: 2.567-8.211), neoadjuvant chemotherapy history (OR: 2.398; 95% CI: 1.094-5.256), and longer surgical duration (OR: 2.393; 95% CI: 1.349-4.246; P?=?0.002) were identified as risk factors for SSI. Multivariate analysis indicated that age (P?=?0.003), surgical duration (P?=?0.001), and pre-operative oral antibiotic use (P?<?0.001) were independent factors that affect the incidence of SSI. Furthermore, a propensity-matched analysis confirmed the protective effect of oral antibiotic use, with a 1-day course of oral antibiotic producing a similar effect to a 3-day course. CONCLUSIONS:Age, surgical duration, and pre-operative oral antibiotic use were associated with the incidence of SSI. However, pre-operative oral antibiotic use was the only controllable factor. From the results of our study, pre-operative oral antibiotic use is recommended before elective colorectal surgery and a 1-day course is enough to provide the protective effect.

Project description:BackgroundThere is controversy regarding the maximum number of elements that can be included in a surgical site infection prevention bundle. In addition, it is unclear whether a bundle of this type can be implemented at a multicentre level.MethodsA pragmatic, multicentre cohort study was designed to analyse surgical site infection rates in elective colorectal surgery after the sequential implementation of two preventive bundle protocols. Secondary outcomes were to determine compliance with individual measures and to establish their effectiveness, duration of stay, microbiology and 30-day mortality rate.ResultsA total of 32 205 patients were included. A 50% reduction in surgical site infection was achieved after the implementation of two sequential sets of bundles: from 18.16% in the Baseline group to 10.03% with Bundle-1 and 8.19% with Bundle-2. Bundle-2 reduced superficial-surgical site infection (OR 0.74 (95% c.i. 0.58 to 0.95); P = 0.018) and deep-surgical site infection (OR 0.66 (95% c.i. 0.46 to 0.93); P = 0.018) but not organ/space-surgical site infection (OR 0.88 (95% c.i. 0.74 to 1.06); P = 0.172). Compliance increased after the addition of four measures to Bundle-2. In the multivariable analysis, for organ/space-surgical site infection, laparoscopy, oral antibiotic prophylaxis and mechanical bowel preparation were protective factors in colonic procedures, while no protective factors were found in rectal surgery. Duration of stay fell significantly over time, from 7 in the Baseline group to 6 and 5 days for Bundle-1 and Bundle-2 respectively (P < 0.001). The mortality rate fell from 1.4% in the Baseline group to 0.59% and 0.6% for Bundle-1 and Bundle-2 respectively (P < 0.001). There was an increase in Gram-positive bacteria and yeast isolation, and reduction in Gram-negative bacteria and anaerobes in organ/space-surgical site infection.ConclusionsThe addition of measures to create a final 10-measure protocol had a cumulative protective effect on reducing surgical site infection. However, organ/space-surgical site infection did not benefit from the addition. No protective measures were found for organ/space-surgical site infection in rectal surgery. Compliance with preventive measures increased from Bundle-1 to Bundle-2.

Project description:BackgroundSurgical site infection (SSI) remains a common, costly, and morbid health care-associated infection. Early detection can improve outcomes, yet previous risk models consider only baseline risk factors (BF) not incorporating a proximate and timely data source-the wound itself. We hypothesize that incorporation of daily wound assessment improves the accuracy of SSI identification compared with traditional BF alone.Study designA prospective cohort of 1,000 post open abdominal surgery patients at an academic teaching hospital were examined daily for serial features (SF), for example, wound characteristics and vital signs, in addition to standard BF, for example, wound class. Using supervised machine learning, we trained 3 Naïve Bayes classifiers (BF, SF, and BF+SF) using patient data from 1 to 5 days before diagnosis to classify SSI on the following day. For comparison, we also created a simplified SF model that used logistic regression. Control patients without SSI were matched on 5 similar consecutive postoperative days to avoid confounding by length of stay. Accuracy, sensitivity/specificity, and area under the receiver operating characteristic curve were calculated on a training and hold-out testing set.ResultsOf 851 patients, 19.4% had inpatient SSIs. Univariate analysis showed differences in C-reactive protein, surgery duration, and contamination, but no differences in American Society of Anesthesiologists scores, diabetes, or emergency surgery. The BF, SF, and BF+SF classifiers had area under the receiver operating characteristic curves of 0.67, 0.76, and 0.76, respectively. The best-performing classifier (SF) had optimal sensitivity of 0.80, specificity of 0.64, positive predictive value of 0.35, and negative predictive value of 0.93. Features most associated with subsequent SSI diagnosis were granulation degree, exudate amount, nasogastric tube presence, and heart rate.ConclusionsSerial features provided moderate positive predictive value and high negative predictive value for early identification of SSI. Addition of baseline risk factors did not improve identification. Features of evolving wound infection are discernable before the day of diagnosis, based primarily on visual inspection.

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Detection of clinically important colorectal surgical site infection using Bayesian network.

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Detection of clinically important colorectal surgical site infection using Bayesian network.

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