Perioperative risk prediction in the era of enhanced recovery: a comparison of POSSUM, ACPGBI, and E-PASS scoring systems in major surgical procedures of the colorectal surgeon

More than 30 Years of POSSUM: Are Scoring Systems Still Relevant Today for Colorectal Surgery?

BACKGROUND

The Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) weights the patient's individual health status and the extent of the surgical procedure to estimate the probability of postoperative complications and death of general surgery patients. The variations Portsmouth-POSSUM (P-POSSUM) and colorectal POSSUM (CR-POSSUM) were developed for estimating mortality in patients with low perioperative risk and for patients with colorectal carcinoma, respectively. The aim of the present study was to evaluate the significance of POSSUM, P-POSSUM, and CR-POSSUM in two independent colorectal cancer cohorts undergoing surgery, with an emphasis on laparoscopic procedures.

METHODS

For each patient, an individual physiological score (PS) and operative severity score (OS) was attributed to calculate the predicted morbidity and mortality, respectively. Logistic regression analysis was used to evaluate the possible correlation between the subscores and the probability of postoperative complications and mortality.

RESULTS

The POSSUM equation significantly overpredicted postoperative morbidity, and all three scoring systems considerably overpredicted in-hospital mortality. However, the POSSUM score identified patients at risk of anastomotic leakage, sepsis, and the need for reoperation. Logistic regression analysis demonstrated a strong correlation between the subscores and the probability of postoperative complications and mortality, respectively.

CONCLUSION

Our results suggest that the three scoring systems are too imprecise for the estimation of perioperative complications and mortality of patients undergoing colorectal surgery in the present day. Since the subscores proved valid, a revision of the scoring systems could increase their reliability in the clinical setting.

Effect of Pharmacoprophylaxis on Postoperative Outcomes in Adult Elective Colorectal Surgery: A Multi-Center Retrospective Cohort Study within an Enhanced Recovery after Surgery Framework

BACKGROUND

The application of enhanced recovery after surgery principles decreases postoperative complications (POCs), length of stay (LOS), and readmissions. Pharmacoprophylaxis decreases morbidity, but the effect of specific regimens on clinical outcomes is unclear.

METHODS AND MATERIALS

Records of 476 randomly selected adult patients who underwent elective colorectal surgeries (ECRS) at 10 US hospitals were abstracted. Primary outcomes were surgical site infection (SSI), venous thromboembolism (VTE), postoperative nausea and vomiting (PONV), pain, and ileus rates. Secondary outcomes included LOS and 7- and 30-day readmission rates.

RESULTS

POC rates were SSI (3.4%), VTE (1.5%), PONV (47.9%), pain (58.1%), and ileus (16.1%). Cefazolin 2 g/metronidazole 500 mg and ertapenem 1 g were associated with the shortest LOS; cefotetan 2 g and cefoxitin 2 g with the longest LOS. No SSI occurred with ertapenem and cefotetan. More Caucasians than Blacks received oral antibiotics before intravenous antibiotics without impact. Enoxaparin 40 mg subcutaneously daily was the most common inpatient and discharge VTE prophylaxis. All in-hospital VTEs occurred with unfractionated heparin. Most received rescue rather than around-the-clock antiemetics. Scopolamine patches, spinal opioids, and IV lidocaine continuous infusion were associated with lower PONV. Transversus abdominis plane block with long-acting local anesthetics, celecoxib, non-anesthetic ketamine bolus, ketorolac IV, lidocaine IV, and pregabalin were associated with lower in-hospital pain severity rates. Gabapentinoids and alvimopan were associated with lower ileus rates. Acetaminophen, alvimopan, famotidine, and lidocaine patches were associated with shorter LOS.

CONCLUSIONS

Significant differences in pharmacotherapy regimens that may improve primary and secondary outcomes in ECRS were identified. In adult ECRS, cefotetan or ertapenem may be better regimens for preventing in-hospital SSI, while ertapenem or C/M may lead to shorter LOS. The value of OA to prevent SSI was not demonstrated. Inpatient enoxaparin, compared to UFH, may reduce VTE rates with a similar LOS. A minority of patients had a documented PONV risk assessment, and a majority used as-needed rather than around-the-clock strategies. Preoperative scopolamine patches continued postoperatively may lower PONV and PDNV severity and shorter LOS. Alvimopan may reduce ileus and shorten LOS. Anesthesia that includes TAP block, ketorolac IV, and pregabalin use may lead to reduced pain rates. Acetaminophen, alvimopan, famotidine, and lidocaine patches may shorten LOS. Given the challenges of pain management and the incidence of PONV/PDNV found in this study, additional studies should be conducted to determine optimal opioid-free anesthesia and the benefit of newer antiemetics on patient outcomes. Moreover, future research should identify latent pharmacotherapy variables that impact patient outcomes, correlate pertinent laboratory results, and examine the impact of order or care sets used for ECRS at study hospitals.

Risk factors for in-hospital mortality after emergency colorectal surgery in octogenarians: results of a cohort study from a referral center

PURPOSE

The objective of this study was to investigate predictive factors of mortality in emergency colorectal surgery in octogenarian patients.

METHODS

It is a retrospective cohort study conducted at a single-institution tertiary referral center. Consecutive patients who underwent emergency colorectal surgery between January 2015 and January 2020 were identified. The primary endpoint was 30-day mortality. Univariate and multivariate analyses were performed using a logistic regression model.

RESULTS

A total of 111 patients were identified (43 men, 68 women). Mean age was 85.7 ± 3.7 years (80-96). Main diagnoses included complicated sigmoiditis in 38 patients (34.3%), cancer in 35 patients (31.5%), and ischemic colitis in 31 patients (27.9%). An ASA score of 3 or higher was observed in 88.3% of patients. The mean Charlson score was 5.9. The Possum score was 35.9% for mortality and 79.3% for morbidity. The 30-day mortality rate was 25.2%. Univariate analysis of preoperative risk factors for mortality shows that the history of valvular heart disease (p = 0.008), intensive care unit provenance (p = 0.003), preoperative sepsis (p < 0.001), diagnosis of ischemic colitis (p = 0.012), creatinine (p = 0.006) and lactate levels (p = 0.01) were significantly associated with 30-day mortality, and patients coming from home had a lower 30-day mortality rate (p = 0.018). Intraoperative variables associated with 30-day mortality included ileostomy creation (p = 0.022) and temporary laparostomy (p = 0.004). At multivariate analysis, only lactate (p = 0.032) and creatinine levels (p = 0.027) were found to be independent predictors of 30-day mortality, home provenance was an independent protective factor (p = 0.004). Mean follow-up was 3.4 years. Survival at 1 and 3 years was 57.6 and 47.7%.

CONCLUSION

Emergency colorectal surgery is challenging. However, age should not be a contraindication. The 30-day mortality rate (25.2%) is one of the lowest in the literature. Hyperlactatemia (> 2mmol/L) and creatinine levels appear to be independent predictors of mortality.

External validation of the Codman score in colorectal surgery: a pragmatic tool to drive quality improvement

AIM

The simple six-variable Codman score is a tool designed to reduce the complexity of contemporary risk-adjusted postoperative mortality rate predictions. We sought to externally validate the Codman score in colorectal surgery.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) participant user file and colectomy targeted dataset of 2020 were merged. A Codman score (composed of six variables: age, American Society of Anesthesiologists score, emergency status, degree of sepsis, functional status and preoperative blood transfusion) was assigned to every patient. The primary outcome was in-hospital mortality and secondary outcome was morbidity at 30 days. Logistic regression analyses were performed using the Codman score and the ACS NSQIP mortality and morbidity algorithms as independent variables for the primary and secondary outcomes. The predictive performance of discrimination area under receiver operating curve (AUC) and calibration of the Codman score and these algorithms were compared.

RESULTS

A total of 40 589 patients were included and a Codman score was generated for 40 557 (99.02%) patients. The median Codman score was 3 (interquartile range 1-4). To predict mortality, the Codman score had an AUC of 0.92 (95% CI 0.91-0.93) compared to the NSQIP mortality score 0.93 (95% CI 0.92-0.94). To predict morbidity, the Codman score had an AUC of 0.68 (95% CI 0.66-0.68) compared to the NSQIP morbidity score 0.72 (95% CI 0.71-0.73). When body mass index and surgical approach was added to the Codman score, the performance was no different to the NSQIP morbidity score. The calibration of observed versus expected predictions was almost perfect for both the morbidity and mortality NSQIP predictions, and only well fitted for Codman scores of less than 4 and greater than 7.

CONCLUSION

We propose that the six-variable Codman score is an efficient and actionable method for generating validated risk-adjusted outcome predictions and comparative benchmarks to drive quality improvement in colorectal surgery.

Development and internal validation of a model for postoperative morbidity in adults undergoing major elective colorectal surgery: the peri-operative quality improvement programme (PQIP) colorectal risk model

Over 1.5 million major surgical procedures take place in the UK NHS each year and approximately 25% of patients develop at least one complication. The most widely used risk-adjustment model for postoperative morbidity in the UK is the physiological and operative severity score for the enumeration of mortality and morbidity. However, this model was derived more than 30 years ago and now overestimates the risk of morbidity. In addition, contemporary definitions of some model predictors are markedly different compared with when the tool was developed. A second model used in clinical practice is the American College of Surgeons National Surgical Quality Improvement Programme risk model; this provides a risk estimate for a range of postoperative complications. This model, widely used in North America, is not open source and therefore cannot be applied to patient populations in other settings. Data from a prospective multicentre clinical dataset of 118 NHS hospitals (the peri-operative quality improvement programme) were used to develop a bespoke risk-adjustment model for postoperative morbidity. Patients aged ≥ 18 years who underwent colorectal surgery were eligible for inclusion. Postoperative morbidity was defined using the postoperative morbidity survey at postoperative day 7. Thirty-one candidate variables were considered for inclusion in the model. Death or morbidity occurred by postoperative day 7 in 3098 out of 11,646 patients (26.6%). Twelve variables were incorporated into the final model, including (among others): Rockwood clinical frailty scale; body mass index; and index of multiple deprivation quintile. The C-statistic was 0.672 (95%CI 0.660-0.684), with a bootstrap optimism corrected C-statistic of 0.666 at internal validation. The model demonstrated good calibration across the range of morbidity estimates with a mean slope gradient of predicted risk of 0.959 (95%CI 0.894-1.024) with an index-corrected intercept of -0.038 (95%CI -0.112-0.036) at internal validation. Our model provides parsimonious case-mix adjustment to quantify risk of morbidity on postoperative day 7 for a UK population of patients undergoing major colorectal surgery. Despite the C-statistic of &lt; 0.7, our model outperformed existing risk-models in widespread use. We therefore recommend application in case-mix adjustment, where incorporation into a continuous monitoring tool such as the variable life adjusted display or exponentially-weighted moving average-chart could support high-level monitoring and quality improvement of risk-adjusted outcome at the population level.

Ideal algorithms in healthcare: Explainable, dynamic, precise, autonomous, fair, and reproducible

Established guidelines describe minimum requirements for reporting algorithms in healthcare; it is equally important to objectify the characteristics of ideal algorithms that confer maximum potential benefits to patients, clinicians, and investigators. We propose a framework for ideal algorithms, including 6 desiderata: explainable (convey the relative importance of features in determining outputs), dynamic (capture temporal changes in physiologic signals and clinical events), precise (use high-resolution, multimodal data and aptly complex architecture), autonomous (learn with minimal supervision and execute without human input), fair (evaluate and mitigate implicit bias and social inequity), and reproducible (validated externally and prospectively and shared with academic communities). We present an ideal algorithms checklist and apply it to highly cited algorithms. Strategies and tools such as the predictive, descriptive, relevant (PDR) framework, the Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence (SPIRIT-AI) extension, sparse regression methods, and minimizing concept drift can help healthcare algorithms achieve these objectives, toward ideal algorithms in healthcare.

OUP accepted manuscript

Background

As the outcome of modern colorectal cancer (CRC) surgery has significantly improved over the years, however, renewed and adequate risk stratification for mortality is important to identify high-risk patients. This population-based study was conducted to analyse postoperative outcomes in patients with CRC and to create a risk model for 30-day mortality.

Methods

Data from the Dutch Colorectal Audit were used to assess differences in postoperative outcomes (30-day mortality, hospital stay, blood transfusion, postoperative complications) in patients with CRC treated from 2009 to 2017. Time trends were analysed. Clinical variables were retrieved (including stage, age, sex, BMI, ASA grade, tumour location, timing, surgical approach) and a prediction model with multivariable regression was computed for 30-day mortality using data from 2009 to 2014. The predictive performance of the model was tested among a validation cohort of patients treated between 2015 and 2017.

Results

The prediction model was obtained using data from 51 484 patients and the validation cohort consisted of 32 926 patients. Trends of decreased length of postoperative hospital stay and blood transfusions were found over the years. In stage I–III, postoperative complications declined from 34.3 per cent to 29.0 per cent (P < 0.001) over time, whereas in stage IV complications increased from 35.6 per cent to 39.5 per cent (P = 0.010). Mortality decreased in stage I–III from 3.0 per cent to 1.4 per cent (P < 0.001) and in stage IV from 7.6 per cent to 2.9 per cent (P < 0.001). Eight factors, including stage, age, sex, BMI, ASA grade, tumour location, timing, and surgical approach were included in a 30-day mortality prediction model. The results on the validation cohort documented a concordance C statistic of 0.82 (95 per cent c.i. 0.80 to 0.83) for the prediction model, indicating good discriminative ability.

Conclusion

Postoperative outcome improved in all stages of CRC surgery in the Netherlands. The developed model accurately predicts postoperative mortality risk and is clinically valuable for decision-making.

A Prediction Model for Severe Complications after Elective Colorectal Cancer Surgery in Patients of 70 Years and Older

Introduction Older patients have an increased risk of morbidity and mortality after colorectal cancer (CRC) surgery. Existing CRC surgical prediction models have not incorporated geriatric predictors, limiting applicability for preoperative decision-making. The objective was to develop and internally validate a predictive model based on preoperative predictors, including geriatric characteristics, for severe postoperative complications after elective surgery for stage I-III CRC in patients ≥70 years.

PATIENTS AND METHODS

A prospectively collected database contained 1088 consecutive patients from five Dutch hospitals (2014-2017) with 171 severe complications (16%). The least absolute shrinkage and selection operator (LASSO) method was used for predictor selection and prediction model building. Internal validation was done using bootstrapping.

RESULTS

A geriatric model that included gender, previous DVT or pulmonary embolism, COPD/asthma/emphysema, rectal cancer, the use of a mobility aid, ADL assistance, previous delirium and polypharmacy showed satisfactory discrimination with an AUC of 0.69 (95% CI 0.73-0.64); the AUC for the optimism corrected model was 0.65. Based on these predictors, the eight-item colorectal geriatric model (GerCRC) was developed.

CONCLUSION

The GerCRC is the first prediction model specifically developed for older patients expected to undergo CRC surgery. Combining tumour- and patient-specific predictors, including geriatric predictors, improves outcome prediction in the heterogeneous older population.

Validation of the Surgical Outcome Risk Tool (SORT) for Predicting Postoperative Mortality in Colorectal Cancer Patients Undergoing Surgery and Subgroup Analysis

BACKGROUND

The accurate evaluation of perioperative risk is crucial to facilitate the shared decision-making process. Surgical outcome risk tool (SORT) has been developed to provide enhanced and more feasible identification of high-risk surgical patients. Nonetheless, SORT has not been validated for patients with colorectal cancer undergoing surgery. Our aim was to determine whether SORT can accurately predict mortality after surgery for colorectal cancer and to compare it with traditional risk models.

METHOD

526 patients undergoing surgery performed by a colorectal surgical team in a single Greek tertiary hospital (2011-2019) were included. Five risk models were evaluated: (1) SORT, (2) Physiology and Operative Severity Score for the enumeration of Mortality and Morbidity (POSSUM), (3) Portsmouth POSSUM (P-POSSUM), (4) Colorectal POSSUM (CR-POSSUM), and (5) the Association of Great Britain and Ireland (ACPGBI) score. Model accuracy was assessed by observed to expected (O:E) ratios, and area under Receiver Operating Characteristic curve (AUC).

RESULTS

Ten patients (1.9%) died within 30 days of surgery. SORT was associated with an excellent level of discrimination [AUC:0.81 (95% CI:0.68-0.94); p = 0.001] and provided the best performing calibration of all models in the entire dataset analysis (H-L:2.82; p = 0.83). Nonetheless, SORT underestimated mortality. SORT model demonstrated excellent discrimination and calibration predicting perioperative mortality in patients undergoing (1) open surgery, (2) emergency/acute surgery, and (3) in cases with colon-located cancer.

CONCLUSION

SORT is an easily adopted risk-assessment tool, associated with enhanced accuracy, that could be implemented in the perioperative pathway of patients undergoing surgery for colorectal cancer.

Nomograms for morbidity and mortality after oncologic colon resection in the enhanced recovery era: results from a multicentric prospective national study

PURPOSE

Predicting postoperative complications and mortality is important to plan the surgical strategy. Different scores have been proposed before to predict them but none of them have been yet implemented into the routine clinical practice because their difficulties and low accuracy with new surgical strategies and enhanced recovery. The main aim of this study is to identify risk factors for postoperative morbidity and mortality after colonic resection (CR) without protective stomas, in order to develop a comprehensive, up-to-date, simple, reliable, and applicable model for the preoperative assessment of patients with colon cancer.

METHODS

Multivariable analysis was performed to identify risk factors for 60-day morbidity and mortality. Coefficients derived from the regression model were used in the nomograms to predict morbidity and mortality.

RESULTS

Three thousand one hundred ninety-three patients from 52 hospitals were included into the analysis. Sixty-day postoperative complications rate was 28.3% and the mortality rate was 3%. In multivariable analysis the independent risk factors for postoperative complications were age, male gender, liver and pulmonary diseases, obesity, preoperative albumin, anticoagulant treatment, open surgery, intraoperative complications, and urgent surgery. Independent risk factors for mortality were age, preoperative albumin anticoagulant treatment, and intraoperative complications.

CONCLUSIONS

Risk factors for morbidity and mortality after CR for cancer were identified and two easy predictive tools were developed. Both of them could provide important information for preoperative consultation and surgical planning in the time of enhance recovery.

Mysteries, Epistemological Modesty, and Artificial Intelligence in Surgery

Life is filled with puzzles and mysteries, and we often fail to recognize the difference. As described by Gregory Treverton and Malcolm Gladwell, puzzles are solved by gathering and assimilating all relevant data in a logical, linear fashion, as in deciding which antibiotic to prescribe for an infection. In contrast, mysteries remain unsolved until all relevant data are analyzed and interpreted in a way that appreciates their depth and complexity, as in determining how to best modulate the host immune response to infection. When investigating mysteries, we often fail to appreciate their depth and complexity. Instead, we gather and assimilate more data, treating the mystery like a puzzle. This strategy is often unsuccessful. Traditional approaches to predictive analytics and phenotyping in surgery use this strategy.

Artificial Intelligence and Surgical Decision-making

Importance

Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes that artificial intelligence should be used to augment surgical decision-making.

Observations

Surgical decision-making is dominated by hypothetical-deductive reasoning, individual judgment, and heuristics. These factors can lead to bias, error, and preventable harm. Traditional predictive analytics and clinical decision-support systems are intended to augment surgical decision-making, but their clinical utility is compromised by time-consuming manual data management and suboptimal accuracy. These challenges can be overcome by automated artificial intelligence models fed by livestreaming electronic health record data with mobile device outputs. This approach would require data standardization, advances in model interpretability, careful implementation and monitoring, attention to ethical challenges involving algorithm bias and accountability for errors, and preservation of bedside assessment and human intuition in the decision-making process.

Conclusions and Relevance

Integration of artificial intelligence with surgical decision-making has the potential to transform care by augmenting the decision to operate, informed consent process, identification and mitigation of modifiable risk factors, decisions regarding postoperative management, and shared decisions regarding resource use.

Application of POSSUM and P-POSSUM in Surgical Risk Assessment of Elderly Patients Undergoing Hepatobiliary and Pancreatic Surgery

Purpose

To investigate the efficacy and accuracy of the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) and Portsmouth-POSSUM (P-POSSUM) scoring systems in the risk assessment of postoperative complications and death in elderly patients undergoing hepatobiliary and pancreatic surgery.

Patients and Methods

Using POSSUM and P-POSSUM, 274 elderly patients undergoing hepatobiliary and pancreatic surgery were evaluated, and the complications and deaths predicted by the systems were compared with the actual situation. The accuracy and predictive ability of POSSUM and P-POSSUM were evaluated using chi-squared and t-tests, consistency of predicted and actual complication rates (observed/expected, OE ratio), and receiver operating characteristic (ROC) curve.

Results

The complication rate predicted by POSSUM (R1) was 22.57%, while the actual postoperative complication rate was 17.88% (P>0.05). The mortality rate predicted by POSSUM (R2) was 4.61%, while the actual rate was 1.09% (P<0.05). The mortality rate predicted by P-POSSUM (R) was 1.42%, while the actual rate was 1.09% (P>0.05). Patients with complications had higher physiology scores (PS), operative severity scores (OS), and POSSUM scores than those without complications (P<0.05). Furthermore, PS, OS, and POSSUM scores were higher in the mortality group than in the survival group. However, the number of individuals in the mortality group was too small to accurately reflect the overall situation. Stratified analysis showed that consistency of the OE ratio in different subgroups was close to 1. The ROC curve showed that the area under the curve for the complication rate predicted by POSSUM was 0.76.

Conclusion

Although the postoperative mortality rate was higher than the actual value, POSSUM could accurately predict the postoperative complication rate in elderly patients undergoing hepatobiliary and pancreatic surgery. The P-POSSUM accurately predicted the postoperative mortality rate in this population. Patients with complications had higher POSSUM scores.

Low value of second-look endoscopy for detecting residual colorectal cancer after endoscopic removal

BACKGROUND AND AIMS

Endoscopic resection is often feasible for submucosal invasive colorectal cancers (T1 CRCs) and usually judged as complete. If histology casts doubt on the radicality of resection margins, adjuvant surgical resection is advised, although residual intramural cancer is found in only 5% to 15% of patients. We assessed the sensitivity of biopsy specimens from the resection area for residual intramural cancer as a potential tool to estimate the preoperative risk of residual intramural cancer in patients without risk factors for lymph node metastasis (LNM).

METHODS

In this multicenter prospective cohort study, patients with complete endoscopic resection of T1 CRC, scheduled for adjuvant resection due to pathologically unclear resection margins, but absent risk factors for LNM, were asked to consent to second-look endoscopy with biopsies. The results were compared with the pathology results of the surgical resection specimen (criterion standard).

RESULTS

One hundred three patients were included. In total, 85% of resected lesions were unexpectedly malignant, and 45% were removed using a piecemeal resection technique. Sixty-four adjuvant surgical resections and 39 local full-thickness resections were performed. Residual intramural cancer was found in 7 patients (6.8%). Two of these patients had cancer in second-look biopsy specimens, resulting in a sensitivity of 28% (95% confidence interval, <58%). The preoperative risk of residual intramural cancer in the case of negative biopsy specimens was not significantly reduced (P = .61).

CONCLUSIONS

The sensitivity of second-look endoscopy with biopsies for residual intramural cancer after endoscopic resection of CRC is low. Therefore, it should not be used in the decision whether or not to perform adjuvant resection. (Clinical trial registration number: NCT02328664.).

Intelligent, Autonomous Machines in Surgery

Surgeons perform two primary tasks: operating and engaging patients and caregivers in shared decision-making. Human dexterity and decision-making are biologically limited. Intelligent, autonomous machines have the potential to augment or replace surgeons. Rather than regarding this possibility with denial, ire, or indifference, surgeons should understand and steer these technologies. Closer examination of surgical innovations and lessons learned from the automotive industry can inform this process. Innovations in minimally invasive surgery and surgical decision-making follow classic S-shaped curves with three phases: (1) introduction of a new technology, (2) achievement of a performance advantage relative to existing standards, and (3) arrival at a performance plateau, followed by replacement with an innovation featuring greater machine autonomy and less human influence. There is currently no level I evidence demonstrating improved patient outcomes using intelligent, autonomous machines for performing operations or surgical decision-making tasks. History suggests that if such evidence emerges and if the machines are cost effective, then they will augment or replace humans, initially for simple, common, rote tasks under close human supervision and later for complex tasks with minimal human supervision. This process poses ethical challenges in assigning liability for errors, matching decisions to patient values, and displacing human workers, but may allow surgeons to spend less time gathering and analyzing data and more time interacting with patients and tending to urgent, critical-and potentially more valuable-aspects of patient care. Surgeons should steer these technologies toward optimal patient care and net social benefit using the uniquely human traits of creativity, altruism, and moral deliberation.

Impact of age on feasibility and short-term outcomes of ERAS after laparoscopic colorectal resection

BACKGROUND

There is still large debate on feasibility and advantages of fast-track protocols in elderly population after colorectal surgery.

AIM

To investigate the impact of age on feasibility and short-term results of enhanced recovery protocol (ERP) after laparoscopic colorectal resection.

METHODS

Data from 225 patients undergoing laparoscopic colorectal resection and ERP between March 2014 and July 2018 were retrospectively analyzed. Three groups were considered according to patients’ age: Group A, 65 years old or less, Group B, 66 to 75 years old and Group C, 76 years old or more. Clinic and pathological data were compared amongst groups together with post-operative outcomes including post-operative overall and surgery-specific complications, mortality and readmission rate. Differences in post-operative length of stay and adherence to ERP’s items were evaluated in the three study groups.

RESULTS

Among the 225 patients, 112 belonged to Group A, 57 to Group B and 56 to Group C. Thirty-day overall morbidity was 32.9% whilst mortality was nihil. Though the percentage of complications progressively increased with age (25.9% vs 36.8% vs 42.9%), no differences were observed in the rate of major complications (4.5% vs 3.5% vs 1.8%), prolonged post-operative ileus (6.2% vs 12.2% vs 10.7%) and anastomotic leak (2.7% vs 1.8% vs 1.8%). Significant differences in recovery outcomes between groups were observed such as delayed urinary catheter removal (P = 0.032) and autonomous deambulation (P = 0.013) in elderly patients. Although discharge criteria were achieved later in older patients (3 d vs 3 d vs 4 d, P = 0.040), post-operative length of stay was similar in the 3 groups (5 d vs 6 d vs 6 d).

CONCLUSION

ERPs can be successfully and safely applied in elderly undergoing laparoscopic colorectal resection.

Single Nucleotide Polymorphisms and Post-operative Complications Following Major Gastrointestinal Surgery: a Systematic Review and Meta-analysis

BACKGROUND

The human genome is an under-researched area of pre-operative risk stratification. Studies of genetic polymorphisms and their associations with acute post-operative complications in gastrointestinal surgery have reported statistically significant results, but have varied in methodology, genetic variations studied, and conclusions reached. To provide clarity, we conducted a systematic review and meta-analysis of single nucleotide polymorphisms and their association with post-operative complications after major gastrointestinal surgery.

METHODS

We performed a literature search using Ovid MEDLINE and Web of Science databases. Studies were included if they investigated genetic polymorphisms and their associations with post-operative complications after major gastrointestinal surgery. We extracted clinical and genetic data from each paper and assessed for quality against the STrengthening the REporting of Genetic Association Studies (STREGA) guidelines. Odds ratios were presented, with 95% confidence intervals, to assess strengths of association. We conducted a meta-analysis on TNF-α-308, which had been assessed in three papers.

RESULTS

Our search returned 68 papers, of which 5 were included after screening and full-text review. Twenty-two different single nucleotide polymorphisms (SNPs) were investigated in these studies. We found that all papers were genetic association studies, and had selected SNPs related to inflammation. The outcome investigated was most commonly post-operative infection, but also anastomotic leak and other non-infectious complications. Statistically significant associations were found for TNF-α-308, IL-10-819, PTGS2-765 and IFN-γ-874. There was significant variability in study quality and methodology. We conducted a meta-analysis on associations between the TNF-α-308 polymorphism and post-operative infection and report an OR of 1.18 (CI 0.27-5.21).

CONCLUSIONS

We found biologically plausible associations between SNPs involved in inflammation and post-operative infection, but the available data were too limited and of insufficient quality to reach definitive conclusions. Further work is needed, including genome-wide association studies (GWAS).