Colorectal preOperative Surgical Score (CrOSS) for mortality in major colorectal surgery

Machine learning-based prediction of postoperative mortality in emergency colorectal surgery: A retrospective, multicenter cohort study using Tokushukai medical database

Background

Although prognostic factors associated with mortality in patients with emergency colorectal surgery have been identified, an accurate mortality risk assessment is still necessary to determine the range of therapeutic resources in accordance with the severity of patients. We established machine-learning models to predict in-hospital mortality for patients who had emergency colorectal surgery using clinical data at admission and attempted to identify prognostic factors associated with in-hospital mortality.

Methods

This retrospective cohort study included adult patients undergoing emergency colorectal surgery in 42 hospitals between 2012 and 2020. We employed logistic regression and three supervised machine-learning models: random forests, gradient-boosting decision trees (GBDT), and multilayer perceptron (MLP). The area under the receiver operating characteristics curve (AUROC) was calculated for each model. The Shapley additive explanations (SHAP) values are also calculated to identify the significant variables in GBDT.

Results

There were 8792 patients who underwent emergency colorectal surgery. As a result, the AUROC values of 0.742, 0.782, 0.814, and 0.768 were obtained for logistic regression, random forests, GBDT, and MLP. According to SHAP values, age, colorectal cancer, use of laparoscopy, and some laboratory variables, including serum lactate dehydrogenase serum albumin, and blood urea nitrogen, were significantly associated with in-hospital mortality.

Conclusion

We successfully generated a machine-learning prediction model, including GBDT, with the best prediction performance and exploited the potential for use in evaluating in-hospital mortality risk for patients who undergo emergency colorectal surgery.

Estimating postoperative mortality in colorectal surgery- a systematic review of risk prediction models

PURPOSE

Risk prediction models are frequently used to support decision-making in colorectal surgery but can be inaccurate. Machine learning (ML) is becoming increasingly popular, and its application may increase predictive accuracy. We compared conventional risk prediction models for postoperative mortality (based on regression analysis) with ML models to determine the benefit of the latter approach.

METHODS

The study was registered in PROSPERO(CRD42022364753). Following the PRISMA guidelines, a systematic search of three databases (MEDLINE, EMBASE, WoS) was conducted (from 1/1/2000 to 29/09/2022). Studies were included if they reported the development of a risk model to estimate short-term postoperative mortality for patients undergoing colorectal surgery. Discrimination and calibration performance metrics were compared. Studies were evaluated against CHARMS and TRIPOD criteria.

RESULTS

3,052 articles were screened, and 45 studies were included. The total sample size was 1,356,058 patients. Six studies used ML techniques for model development. Most studies (n = 42) reported the area under the receiver operating characteristic curve (AUROC) as a measure of discrimination. There was no significant difference in the mean AUROC values between regression models (0.833 s.d. ± 0.52) and ML (0.846 s.d. ± 0.55), p = 0.539. Calibration statistics, which measure the agreement between predicted estimates and observed outcomes, were less consistent. Risk of bias assessment found most concerns in the data handling and analysis domains of eligible studies.

CONCLUSIONS

Our study showed comparable predictive performance between regression and ML methods in colorectal surgery. Integration of ML in colorectal risk prediction is promising but further refinement of the models is required to support routine clinical adoption.

Contextual Validation of the Prediction of Postoperative Complications of Colorectal Surgery by the "ACS NSQIP ® Risk Calculator" in a Tunisian Center

CONTEXT

Models for predicting individual risks of surgical complications are advantageous for operative decision making and the nature of postoperative management procedures.

OBJECTIVE

Validate the "ACS NSQIP® Risk Calculator" in the prediction of postoperative complications during colorectal cancer surgery, operated during the years 2015 to 2019.

METHODS

this is a prognostic validation study of the "ACS NSQIP®" applied retrospectively to patients operated on for colorectal cancer in the surgical department of Farhat Hached hospital, during the 2015 and 2019 5-year term. Three levels of adjustment. Discrimination and calibration were carried out mainly by ROC curves (AUC ⩾ 0.8).

RESULTS

In this study, 129 patients were included with a sex ratio of 1.22 and a median age of 62 years. The most common operative procedure was low segmental colectomy with colorectal anastomosis. Thirty-seven patients (28.7%) had at least one postoperative complication. The prediction and cuts-off points values of mortality (AUC = 0.858; CI95% [0.570-0.960]; Cuts-off points = 1.8%), cardiac complications (AUC = 0.824; CI95% [0.658-0.990]; Cuts-off points = 1.8%), thromboembolic complications (AUC = 0.802; CI95% [0.617-0.987]; Cuts-off point = 3.1%), and renal insufficiency (AUC = 0.802; CI95% [ 0.623-0.981]; Cuts-off point = 1.2%) were adjusted according to level 1 of the calculator.

CONCLUSION

This work contextualized the prediction of postoperative complications in colorectal surgery in the university general surgery department of Farhat Hached in Sousse (Tunisia), making it possible to improve the quality and safety of surgical care. The application of the Tunisian mini calculator is recommended as well as the generalization of validation following the development of a generic calculator for all operating procedures.

A Novel Nomogram for Early Identification and Intervention in Colorectal Cancer Patients at Risk for Malnutrition

BACKGROUND

Malnutrition is under-recognized in cancer patients and can lead to poor treatment outcomes. We aim to develop an outpatient-focused score based on the Malnutrition Screening Tool (MST) to help identify colorectal cancer (CRC) profiles at high risk for malnutrition.

METHODS

506 CRC patients during initial outpatient oncology consultation at our tertiary referral outpatient oncology clinic completed the MST. Objective and subjective data were collected through chart review. Data gathered are as follows: demographics, anthropometrics, laboratory values, patient-reported symptoms, MST score, cancer history, performance status, socioeconomic status, and Charlson Comorbidity. Predictors of malnutrition were identified by logistic regression. Receiver operating curve (ROC), area under the curve (AUC), and our model's predictability were determined.

RESULTS

Significant predictors of malnutrition are as follows: younger age (20-39 vs >40 years) (P = .007), normal-to-low body mass index at presentation (P = .019), Eastern Cooperative Oncology Group classification 2-3 (P = .012), metastatic disease (P = .046), albumin <3.0 g/dL (P = .033), fatigue (P < .001), and change in stool/bowel habits (P = .002). In our derived malnutrition score, risk of malnutrition increased from 11% for score 0, to 100% for scores 9-10. Receiver operating curve showed AUC .745 (95% CI, .697-.793).

DISCUSSION

An outpatient clinic-derived malnutrition score obtained from objective and patient-reported variables may facilitate identification of CRC patients at highest risk for malnutrition. Rapid identification and intervention in high-risk patients may improve treatment recovery, therapy tolerance, and quality of life. Our tool requires external validation before application in clinical practice.

Machine Learning-based Model for Predicting Postoperative Complications among Patients with Colonic Perforation: A Retrospective study

Objectives:

Surgery for colonic perforation has high morbidity and mortality rates. Predicting complications preoperatively would help improve short-term outcomes; however, no predictive risk stratification model exists to date. Therefore, the current study aimed to determine risk factors for complications after colonic perforation surgery and use machine learning to construct a predictive model.

Methods:

This retrospective study included 51 patients who underwent emergency surgery for colorectal perforation. We investigated the connection between overall complications and several preoperative indicators, such as lactate and the Glasgow Prognostic Score. Moreover, we used the classification and regression tree (CART), a machine-learning method, to establish an optimal prediction model for complications.

Results:

Overall complications occurred in 32 patients (62.7%). Multivariate logistic regression analysis identified high lactate levels [odds ratio (OR), 1.86; 95% confidence interval (CI), 1.07-3.22; p = 0.027] and hypoalbuminemia (OR, 2.56; 95% CI, 1.06-6.25; p = 0.036) as predictors of overall complications. According to the CART analysis, the albumin level was the most important parameter, followed by the lactate level. This prediction model had an area under the curve (AUC) of 0.830.

Conclusions:

Our results determined that both preoperative albumin and lactate levels were valuable predictors of postoperative complications among patients who underwent colonic perforation surgery. The CART analysis determined optimal cutoff levels with high AUC values to predict complications, making both indicators clinically easier to use for decision making.

Postoperative complications and hospital costs following small bowel resection surgery

BACKGROUND

Postoperative complications after major gastrointestinal surgery are a major contributor to hospital costs. Thus, reducing postoperative complications is a key target for cost-containment strategies. We aimed to evaluate the relationship between postoperative complications and hospital costs following small bowel resection.

METHODS

Postoperative complications were recorded for 284 adult patients undergoing major small bowel resection surgery between January 2013 and June 2018. Complications were defined and graded according to the Clavien-Dindo classification system. In-hospital cost of index admission was calculated using an activity-based costing methodology; it was reported in US dollars at 2019 rates. Regression modeling was used to investigate the relationships among a priori selected perioperative variables, complications, and costs.

FINDINGS

The overall complication prevalence was 81.6% (95% CI: 85.7-77.5). Most complications (69%) were minor, but 22.9% of patients developed a severe complication (Clavien-Dindo grades III or IV). The unadjusted median total hospital cost for patients with any complication was 70% higher than patients without complications (median [IQR] USD 19,659.64 [13,545.81-35,407.14] vs. 11,551.88 [8,849.46-15,329.87], P < 0.001). The development of 1, 2, 3, and ≥ 4 complications increased hospital costs by 11%, 41%, 50%, and 195%, respectively. Similarly, more severe complications incurred higher hospital costs (P < 0.001). After adjustments were made (for the Charlson Comorbidity Index, anemia, surgical urgency and technique, intraoperative fluid administration, blood transfusion, and hospital readmissions), a greater number and increased severity of complications were associated with a higher adjusted median hospital cost. Patients who experienced complications had an adjusted additional median cost of USD 4,187.10 (95% CI: 1,264.89-7,109.31, P = 0.005) compared to those without complications.

CONCLUSIONS

Postoperative complications are a key target for cost-containment strategies. Our findings demonstrate a high prevalence of postoperative complications following small bowel resection surgery and quantify their associated increase in hospital costs.

TRIAL REGISTRATION

Australian Clinical Trials Registration number: 12620000322932.

Predictive Model of the Risk of In-Hospital Mortality in Colorectal Cancer Surgery, Based on the Minimum Basic Data Set

BACKGROUND

Various models have been proposed to predict mortality rates for hospital patients undergoing colorectal cancer surgery. However, none have been developed in Spain using clinical administrative databases and none are based exclusively on the variables available upon admission. Our study aim is to detect factors associated with in-hospital mortality in patients undergoing surgery for colorectal cancer and, on this basis, to generate a predictive mortality score.

METHODS

A population cohort for analysis was obtained as all hospital admissions for colorectal cancer during the period 2008-2014, according to the Spanish Minimum Basic Data Set. The main measure was actual and expected mortality after the application of the considered mathematical model. A logistic regression model and a mortality score were created, and internal validation was performed.

RESULTS

115,841 hospitalization episodes were studied. Of these, 80% were included in the training set. The variables associated with in-hospital mortality were age (OR: 1.06, 95%CI: 1.05-1.06), urgent admission (OR: 4.68, 95% CI: 4.36-5.02), pulmonary disease (OR: 1.43, 95%CI: 1.28-1.60), stroke (OR: 1.87, 95%CI: 1.53-2.29) and renal insufficiency (OR: 7.26, 95%CI: 6.65-7.94). The level of discrimination (area under the curve) was 0.83.

CONCLUSIONS

This mortality model is the first to be based on administrative clinical databases and hospitalization episodes. The model achieves a moderate-high level of discrimination.

Predictors of overall survival following extended radical resections for locally advanced and recurrent pelvic malignancies

PURPOSE

In an era of personalised medicine, there is an overwhelming effort for predicting patients who will benefit from extended radical resections for locally advanced pelvic malignancy. However, there is paucity of data on the effect of comorbidities and postoperative complications on long-term overall survival (OS). The aim of this study was to define predictors of 1-year and 5-year OS.

METHODS

Data were collected from prospective databases at two high-volume institutions specialising in beyond TME surgery for locally advanced and recurrent pelvic malignancies between 1990 and 2015. The primary outcome measures were 1-year and 5-year OS.

RESULTS

A total of 646 consecutive extended radical resections were performed between 1990 and 2015. The majority were female patients (371, 57.4%) and the median age was 63 years (range 19-89 years). One-year OS, primary rectal adenocarcinoma had the best survival while recurrent colon cancer had the worse survival (p = 0.047). The 5-year OS between primary and recurrent cancers were 64.7% and 53%, respectively (p = 0.004). Poor independent prognostic markers for 5-year OS were increasing ASA score, cardiovascular disease, recurrent cancers, ovarian cancers, pulmonary embolus and acute respiratory distress syndrome. A positive survival benefit was demonstrated with preoperative radiotherapy (HR 0.55; 95% CI 0.4-0.75, p < 0.001).

CONCLUSION

Patient comorbidities and specific complications can influence long-term survival following extended radical resections. This study highlights important predictors, enabling clinicians to better inform patients of the potential short- and long-term outcomes in the management of locally advanced and recurrent pelvic malignancy.

Risk prediction models for postoperative outcomes of colorectal cancer surgery in the older population - a systematic review

BACKGROUND

An increasing number of patients with Colorectal Cancer (CRC) is 65 years or older. We aimed to systematically review existing clinical prediction models for postoperative outcomes of CRC surgery, study their performance in older patients and assess their potential for preoperative decision making.

METHODS

A systematic search in Pubmed and Embase for original studies of clinical prediction models for outcomes of CRC surgery. Bias and relevance for preoperative decision making with older patients were assessed using the CHARMS guidelines.

RESULTS

26 prediction models from 25 publications were included. The average age of included patients ranged from 61 to 76. Two models were exclusively developed for 65 and older. Common outcomes were mortality (n = 10), anastomotic leakage (n = 7) and surgical site infections (n = 3). No prediction models for quality of life or physical functioning were identified. Age, gender and ASA score were common predictors; 12 studies included intraoperative predictors. For the majority of the models, bias for model development and performance was considered moderate to high.

CONCLUSIONS

Prediction models are available that address mortality and surgical complications after CRC surgery. Most models suffer from methodological limitations, and their performance for older patients is uncertain. Models that contain intraoperative predictors are of limited use for preoperative decision making. Future research should address the predictive value of geriatric characteristics to improve the performance of prediction models for older patients.

The hospital costs of complications following colonic resection surgery: A retrospective cohort study

Background

Colonic resection is a common surgical procedure associated with a high rate of postoperative complications. The aim of this observational study is to estimate the in-hospital costs of complications and to identify perioperative variables associated with complication development following colon resection surgery.

Materials and methods

We conducted a single-centre cohort study with retrospective data collection of 487 patients undergoing colonic resection surgery between 2013 and 2018. Postoperative complications were graded according to the Clavien-Dindo classification system. In-hospital cost of index admission is reported in 2019 United States Dollars. Regression modelling was used to investigate the relationship of a priori selected perioperative variables and presence of complications and costs.

Results

Overall complication prevalence was 69.6% (95%CI:65.5%–73.7%). Median [interquartile range] cost of patients with postoperative complications was significantly increased as compared to patients without complications ($17,963 [13,533:25,178] vs $12,578 [10,196:16,140]; p < 0.0001). Clavien-Dindo Grade I, II, III and IV complications increased costs by 15.8%, 36.8%, 169.4% and 240.1% respectively (p < 0.0001). Presence of complications was significantly associated with Charlson Comorbidity Index (Odds ratio (OR) per 1-unit increase: 1.09; 95%CI:1.02 to 1.17), preoperative albumin levels (OR per 1-unit increase: 0.94; 95%CI:0.90 to 0.98) and open as compared to laparoscopic resection (OR: 2.41; 95%CI:1.32 to 4.42).

Conclusions

There is a high prevalence of complications following colonic resection surgery. Postoperative complications, including minor complications (Clavien-Dindo Grade I-II), were associated with a significant increase in hospital costs and are a key target for cost containment strategies.

•

Almost 7 out of every 10 patients experienced one or more complications.

•

Most complications were minor (Clavien-Dindo grade I-II).

•

Minor complications significantly increased costs by over 20%.

•

Major complications resulted in an exponential increase in costs and length of stay.

•

Charlson Comorbidity Index and hypoalbuminemia are associated with complications.

Screening and systematic follow-up for cardiopulmonary comorbidity in elective surgery for colorectal cancer: a randomised feasibility study

BACKGROUND

One third of patients with colorectal cancer (CRC) have comorbidity, which impairs their postoperative outcomes. Scoring systems may predict mortality, but there is limited evidence of effective interventions in high-risk patients. Our aim was to test a trial setup to assess the effect of extra postoperative medical visits and follow-up on 1-year mortality and other outcomes in patients with cardiopulmonary risk factors undergoing elective surgery for colorectal tumours.

METHODS

Patients preoperatively screened positive for cardiopulmonary comorbidity were eligible. On postoperative day 4, they were randomised to either routine follow-up (RFU) or RFU with one extra medical visit and additional visits to the Cardiology and Respiratory Medicine Clinics 1 and 3 months postoperatively. The primary outcome measure was 1-year mortality; secondary outcome measures were length of stay (LOS), complications, and readmissions.

RESULTS

Of 673 screened patients 326 (48%) were found eligible, 108 declined participation, and 198 were randomised. Postoperative medical problems and/or need for intervention were found in 15-23% of the patients at the extra medical visits. The 90-day mortality was 0 and the 1-year mortality only 2.6% with no differences between the two groups. LOS and complication rates did not differ, but there were significantly fewer readmissions in the intervention group.

CONCLUSIONS

The 1-year mortality after elective CRC surgery was low, even in the presence of cardiopulmonary risk factors. There was no evidence of reduced mortality with additional medical follow-up in these patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02328365 registered 31 December 2014 (retrospectively registered).

CCR-CARESS score for predicting operative mortality in patients with colorectal cancer

BACKGROUND

The aim of this study was to assess factors associated with outcomes after surgery for colorectal cancer and to design and internally validate a simple score for predicting perioperative mortality.

METHODS

Patients undergoing surgery for primary invasive colorectal cancer in 22 centres in Spain between June 2010 and December 2012 were included. Clinical variables up to 30 days were collected prospectively. Multiple logistic regression techniques were applied and a risk score was developed. The Hosmer-Lemeshow test was applied and the area under the receiver operating characteristic (ROC) curve (AUC, with 95 per cent c.i.) was estimated.

RESULTS

A total of 2749 patients with a median age of 68·5 (range 24-97) years were included; the male : female ratio was approximately 2 : 1. Stage III tumours were diagnosed in 32·6 per cent and stage IV in 9·5 per cent. Open surgery was used in 39·3 per cent, and 3·6 per cent of interventions were urgent. Complications were most commonly infectious or surgical, and 25·5 per cent of patients had a transfusion during the hospital stay. The 30-day postoperative mortality rate was 1·9 (95 per cent c.i. 1·4 to 2·4) per cent. Predictive factors independently associated with mortality were: age 80 years or above (odds ratio (OR) 2·76), chronic obstructive pulmonary disease (COPD) (OR 3·62) and palliative surgery (OR 10·46). According to the categorical risk score, a patient aged 80 years or more, with COPD, and who underwent palliative surgery would have a 23·5 per cent risk of death within 30 days of the intervention.

CONCLUSION

Elderly patients with co-morbidity and palliative intention of surgery have an unacceptably high risk of death.

Risk Factors Associated With Circumferential Resection Margin Positivity in Rectal Cancer: A Binational Registry Study

BACKGROUND

Rectal cancer outcomes have improved with the adoption of a multidisciplinary model of care. However, there is a spectrum of quality when viewed from a national perspective, as highlighted by the Consortium for Optimizing the Treatment of Rectal Cancer data on rectal cancer care in the United States.

OBJECTIVE

The aim of this study was to assess and identify predictors of circumferential resection margin involvement for rectal cancer across Australasia.

DESIGN

A retrospective study from a prospectively maintained binational colorectal cancer database was interrogated.

SETTINGS

This study is based on a binational colorectal cancer audit database.

PATIENTS

Clinical information on all consecutive resected rectal cancer cases recorded in the registry from 2007 to 2016 was retrieved, collated, and analyzed.

MAIN OUTCOME MEASURES

The primary outcome measure was positive circumferential resection margin, measured as a resection margin ≤1 mm.

RESULTS

A total of 3367 patients were included, with 261 (7.5%) having a positive circumferential resection margin. After adjusting for hospital and surgeon volume, hierarchical logistic regression analysis identified a 6-variable model encompassing the independent predictors, including urgent operation, abdominoperineal resection, open technique, low rectal cancer, T3 to T4, and N1 to N2. The accuracy of the model was 92.3%, with an receiver operating characteristic of 0.783 (p < 0.0001). The quantitative risk associated with circumferential resection margin positivity ranged from <1% (no risk factors) to 43% (6 risk factors).

LIMITATIONS

This study was limited by the lack of recorded long-term outcomes associated with circumferential resection margin positivity.

CONCLUSIONS

The rate of circumferential resection margin involvement in patients undergoing rectal cancer resection in Australasia is low and is influenced by a number of factors. Risk stratification of outcome is important with the increasing demand for publicly accessible quality data. See Video Abstract at http://links.lww.com/DCR/A512.

Validity of the CR-POSSUM model in surgery for colorectal cancer in Spain (CCR-CARESS study) and comparison with other models to predict operative mortality

Background

To validate and recalibrate the CR- POSSUM model and compared its discriminatory capacity with other European models such as POSSUM, P-POSSUM, AFC or IRCS to predict operative mortality in surgery for colorectal cancer.

Methods

Prospective multicenter cohort study from 22 hospitals in Spain. We included patients undergoing planned or urgent surgery for primary invasive colorectal cancers between June 2010 and December 2012 (N = 2749). Clinical data were gathered through medical chart review. We validated and recalibrated the predictive models using logistic regression techniques. To calculate the discriminatory power of each model, we estimated the areas under the curve - AUC (95% CI). We also assessed the calibration of the models by applying the Hosmer-Lemeshow test.

Results

In-hospital mortality was 1.5% and 30-day mortality, 1.7%. In the validation process, the discriminatory power of the CR-POSSUM for predicting in-hospital mortality was 73.6%. However, in the recalibration process, the AUCs improved slightly: the CR-POSSUM reached 75.5% (95% CI: 67.3–83.7). The discriminatory power of the CR-POSSUM for predicting 30-day mortality was 74.2% (95% CI: 67.1–81.2) after recalibration; among the other models the POSSUM had the greatest discriminatory power, with an AUC of 77.0% (95% CI: 68.9–85.2). The Hosmer-Lemeshow test showed good fit for all the recalibrated models.

Conclusion

The CR-POSSUM and the other models showed moderate capacity to discriminate the risk of operative mortality in our context, where the actual operative mortality is low. Nevertheless the IRCS might better predict in-hospital mortality, with fewer variables, while the CR-POSSUM could be slightly better for predicting 30-day mortality.

Trail registration

Registered at: ClinicalTrials.gov Identifier: NCT02488161

Electronic supplementary material

The online version of this article (10.1186/s12913-018-2839-x) contains supplementary material, which is available to authorized users.

Systematic review of the feasibility of laparoscopic reoperation for early postoperative complications following colorectal surgery

Background

Returning to the operating theatre for management of early postoperative complications after colorectal surgery is an important key performance indicator. Laparoscopic surgery has benefits that may be useful in surgical emergencies. This study explored the evidence for the advantages of laparoscopic reoperation.

Methods

A systematic review was performed to identify publications reporting the outcomes of laparoscopy as a mode of reoperation for the management of early postoperative complications of colorectal surgery. The main outcomes examined were 30-day mortality, 30-day morbidity, length of hospital stay, second reoperation rate, ICU admission and stoma formation at reoperation.

Results

After screening 3657 citations, ten non-randomized cohort studies were identified (1137 reoperations). Laparoscopic reoperation was equivalent to or better than open reoperation, with lower rates of 30-day mortality (0–4·4 versus 0–13·6 per cent), 30-day morbidity (6–40 versus 30–80 per cent), length of stay (mean(s.d.) 15·8(2·8) versus 29·1(14·5) days), ICU admission and duration of stay in the ICU. Anastomotic leak was the most common indication, after which more patients received a defunctioning loop stoma instead of an end stoma at laparoscopic than open reoperation.

Conclusion

Laparoscopic reoperation is feasible in selected patients, with the advantages of improved short-term outcomes.

Predictors of Morbidity and Mortality After Surgery for Intestinal Perforation

Purpose

An intestinal perforation is a rare condition, but has a high mortality rate, even after immediate surgical intervention. The clinical predictors of postoperative morbidity and mortality are still not well established, so this study attempted to identify risk factors for postoperative morbidity and mortality after surgery for an intestinal perforation.

Methods

We retrospectively analyzed the cases of 117 patients who underwent surgery for an intestinal perforation at a single institution in Korea from November 2008 to June 2014. Factors related with postoperative mortality at 1 month and other postoperative complications were investigated.

Results

The mean age of enrolled patients was 66.0 ± 15.8 years and 66% of the patients were male. Fifteen patients (13%) died within 1 month after surgical treatment. Univariate analysis indicated that patient-related factors associated with mortality were low systolic and diastolic blood pressure, low serum albumin, low serum protein, low total cholesterol, and high blood urea nitrogen; the surgery-related factor associated with mortality was feculent ascites. Multivariate analysis using a logistic regression indicated that low systolic blood pressure and feculent ascites independently increased the risk for mortality; postoperative complications were more likely in both females and those with low estimated glomerular filtration rates and elevated serum C-reactive protein levels.

Conclusion

Various factors were associated with postoperative clinical outcomes of patients with an intestinal perforation. Morbidity and mortality following an intestinal perforation were greater in patients with unstable initial vital signs, poor nutritional status, and feculent ascites.

Implications of preoperative hypoalbuminemia in colorectal surgery

Serum albumin has traditionally been used as a quantitative measure of a patient’s nutritional status because of its availability and low cost. While malnutrition has a clear definition within both the American and European Societies for Parenteral and Enteral Nutrition clinical guidelines, individual surgeons often determine nutritional status anecdotally. Preoperative albumin level has been shown to be the best predictor of mortality after colorectal cancer surgery. Specifically in colorectal surgical patients, hypoalbuminemia significantly increases the length of hospital stay, rates of surgical site infections, enterocutaneous fistula risk, and deep vein thrombosis formation. The delay of surgical procedures to allow for preoperative correction of albumin levels in hypoalbuminemic patients has been shown to improve the morbidity and mortality in patients with severe nutritional risk. The importance of preoperative albumin levels and the patient’s chronic inflammatory state on the postoperative morbidity and mortality has led to the development of a variety of surgical scoring systems to predict outcomes efficiently. This review attempts to provide a systematic overview of albumin and its role and implications in colorectal surgery.