Postoperative sepsis prediction in patients undergoing major cancer surgery

The Future of Artificial Intelligence in Surgery

Until recently, innovations in surgery were largely represented by extensions or augmentations of the surgeon's perception. This includes advancements such as the operating microscope, tumor fluorescence, intraoperative ultrasound, and minimally invasive surgical instrumentation. However, introducing artificial intelligence (AI) into the surgical disciplines represents a transformational event. Not only does AI contribute substantively to enhancing a surgeon's perception with such methodologies as three-dimensional anatomic overlays with augmented reality, AI-improved visualization for tumor resection, and AI-formatted endoscopic and robotic surgery guidance. What truly makes AI so different is that it also provides ways to augment the surgeon's cognition. By analyzing enormous databases, AI can offer new insights that can transform the operative environment in several ways. It can enable preoperative risk assessment and allow a better selection of candidates for procedures such as organ transplantation. AI can also increase the efficiency and throughput of operating rooms and staff and coordinate the utilization of critical resources such as intensive care unit beds and ventilators. Furthermore, AI is revolutionizing intraoperative guidance, improving the detection of cancers, permitting endovascular navigation, and ensuring the reduction in collateral damage to adjacent tissues during surgery (e.g., identification of parathyroid glands during thyroidectomy). AI is also transforming how we evaluate and assess surgical proficiency and trainees in postgraduate programs. It offers the potential for multiple, serial evaluations, using various scoring systems while remaining free from the biases that can plague human supervisors. The future of AI-driven surgery holds promising trends, including the globalization of surgical education, the miniaturization of instrumentation, and the increasing success of autonomous surgical robots. These advancements raise the prospect of deploying fully autonomous surgical robots in the near future into challenging environments such as the battlefield, disaster areas, and even extraplanetary exploration. In light of these transformative developments, it is clear that the future of surgery will belong to those who can most readily embrace and harness the power of AI.

Improving Statewide Post-Operative Sepsis Performance Measurement Using Hospital Risk Adjustment Within a Surgical Collaborative

Background: The Georgia Quality Improvement Program (GQIP) surgical collaborative participating hospitals have shown consistently poor performance in the post-operative sepsis category of National Surgical Quality Improvement Program data as compared with national benchmarks. We aimed to compare crude versus risk-adjusted post-operative sepsis rankings to determine high and low performers amongst GQIP hospitals. Patients and Methods: The cohort included intra-abdominal general surgery patients across 10 collaborative hospitals from 2015 to 2020. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) sepsis definition was used among all hospitals for case abstraction and NSQIP data were utilized to train and validate a multivariable risk-adjustment model with post-operative sepsis as the outcome. This model was used to rank GQIP hospitals by risk-adjusted post-operative sepsis rates. Rankings between crude and risk-adjusted post-operative sepsis rankings were compared ordinally and for changes in tertile. Results: The study included 20,314 patients with 595 cases of post-operative sepsis. Crude 30-day post-operative sepsis risk among hospitals ranged from 0.81 to 5.11. When applying the risk-adjustment model which included: age, American Society of Anesthesiology class, case complexity, pre-operative pneumonia/urinary tract infection/surgical site infection, admission status, and wound class, nine of 10 hospitals were re-ranked and four hospitals changed performance tertiles. Conclusions: Inter-collaborative risk-adjusted post-operative sepsis rankings are important to present. These metrics benchmark collaborating hospitals, which facilitates best practice exchange from high to low performers.

Development and validation of a patient-specific model to predict postoperative SIRS in older patients: A two-center study

Introduction

Postoperative systemic inflammatory response syndrome (SIRS) is common in surgical patients especially in older patients, and the geriatric population with SIRS is more susceptible to sepsis, MODS, and even death. We aimed to develop and validate a model for predicting postoperative SIRS in older patients.

Methods

Patients aged ≥65 years who underwent general anesthesia in two centers of Third Affiliated Hospital of Sun Yat-sen University from January 2015 to September 2020 were included. The cohort was divided into training and validation cohorts. A simple nomogram was developed to predict the postoperative SIRS in the training cohort using two logistic regression models and the brute force algorithm. The discriminative performance of this model was determined by area under the receiver operating characteristics curve (AUC). The external validity of the nomogram was assessed in the validation cohort.

Results

A total of 5,904 patients spanning from January 2015 to December 2019 were enrolled in the training cohort and 1,105 patients from January 2020 to September 2020 comprised the temporal validation cohort, in which incidence rates of postoperative SIRS were 24.6 and 20.2%, respectively. Six feature variables were identified as valuable predictors to construct the nomogram, with high AUCs (0.800 [0.787, 0.813] and 0.822 [0.790, 0.854]) and relatively balanced sensitivity (0.718 and 0.739) as well as specificity (0.718 and 0.729) in both training and validation cohorts. An online risk calculator was established for clinical application.

Conclusion

We developed a patient-specific model that may assist in predicting postoperative SIRS among the aged patients.

Risk Factors for Post-cardiac Surgery Infections

Background Cardiac surgery infection is a life-threatening complication associated with high morbidity and mortality. One of the main types of these infections, surgical site infections (SSIs), also called postoperative wound infections basically delayed the post-surgical recovery in many patients. These infections rarely happen within 30 days after surgery due to different risk factors. Objectives The purpose of this study is to determine the risk factors that are involved in causing post-cardiac surgical infections. Methods This study was a retrospective study. The data of postoperative cardiac patients was obtained from the Cardiology and Cardiac Surgery Center in King Fahad Armed Force Hospital, Jeddah. Data on the patients were collected from 2016 to 2021. Eligible patients were those of age 18 and greater. These patients were evaluated on basis of the pre and postoperative risk factors and were analyzed for 30 days after discharge and those that developed SSIs were identified. Results Out of the total number of 2366 patients, 151 patients (6.4%) were identified with post-surgery infections out of which 107 (4.5%) had developed superficial wound infections (SSWIs) and 44 (1.9%) had developed deep wound infections (DSWIs). Infection mainly occurs in the male population (n=88, 58.3%). Major risk factors that were the main cause of post-cardiac surgery infections were diabetes (61.5%), hypertension (56.9%), smoking (38.4%), renal failure (27.1%), and re-do operation (25.1%). Conclusion Our study has demonstrated major risk factors that are involved in the occurrence of post-cardiac surgery infections like smoking, diabetes mellitus, sex, more than one operation during a single stay, etc. In the future, the contribution of various other factors involved in the occurrence of surgical site infections and best practices and methods should be studied and implemented to prevent the occurrence of post-cardiac surgery infections. Various simple techniques can still be utilized to prevent these sorts of infections, which will decrease the mortality rate.

Tree-based, two-stage risk factor analysis for postoperative sepsis based on Sepsis-3 criteria in elderly patients: A retrospective cohort study

Background

Sepsis remains the leading cause of postoperative death in elderly patients and is defined as organ dysfunction with proven or suspected infection according to Sepsis-3 criteria. To better avoid potential non-linear associations between the risk factors, we firstly used a tree-based analytic methods to explore the putative risk factors of geriatric sepsis based on the criteria in the study.

Methods

Data of 7,302 surgical patients aged ≥ 65 years at the Third Affiliated Hospital of Sun Yat-sen University from January 2015 to September 2020 were collected. An analytic method that combined tree-based analysis with the method of Mantel-Haenszel and logistic regression was adopted to assess the association between 17 putative risk factors and postoperative sepsis defined by the Sepsis-3 guideline by controlling 16 potential confounding factors.

Results

Among the 16 potential covariates, six major confounders were statistically identified by the tree-based model, including cerebrovascular diseases, preoperative infusion of red blood cells, pneumonia, age ≥ 75, malignant tumor and diabetes. Our analysis indicated that emergency surgery increases the risk of postoperative sepsis in elderly patients by more than six times. The type of surgery is also a crucial risk factor for sepsis, particularly transplantation and neurosurgery. Other risk factors were duration of surgery > 120 min, administration of steroids, hypoalbuminemia, elevated creatinine, blood urea nitrogen, hematocrit, platelets, glucose, white blood cell count, abnormal neutrophil-to-lymphocyte ratio and elevated hsCRP-to-albumin ratio.

Conclusions

Our study uses an effective method to explore some risk factors for postoperative sepsis in elderly by adjusting many potential confounders and it can provide information for intervention design.

A nationwide study on characteristics and outcome of cancer patients with sepsis requiring intensive care

BACKGROUND

Sepsis is the leading cause of admission to the intensive care unit (ICU) for cancer patients and survival rates have historically been low. The aims of this nationwide cohort study were to describe the characteristics and outcomes of cancer patients admitted to the ICU with sepsis compared with other sepsis patients requiring ICU admission.

MATERIAL AND METHODS

This was a retrospective, observational study. All adult admissions to Icelandic ICUs during years 2006, 2008, 2010, 2012, 2014 and 2016 were screened for severe sepsis or septic shock by ACCP/SCCM criteria. Clinical characteristics and outcomes of sepsis patients with cancer were compared to those without cancer.

RESULTS

In the study period, 235 of 971 (24%) patients admitted to Icelandic ICUs because of sepsis had cancer, most often a solid tumour (100), followed by metastatic tumours (69) and haematological malignancies (66). Infections were more often hospital-acquired in cancer patients (52%) than other sepsis patients (18%, p < 0.001) and sites of infections differed, with abdominal infections being most common in patients with solid and metastatic tumours but lungs and bloodstream infections in haematological malignancies. The length of stay in the ICU was shorter for sepsis patients with metastatic disease than other sepsis patients (2 vs. 4 days, p < 0.001) and they were more likely to have treatment limitations (52 vs. 19%, p < 0.05). Median survival of patients with metastatic disease was 19 days from ICU admission. The 28-day mortality (25%) of solid tumour patients was comparable to that of sepsis patients without cancer (20%, p < 0.001).

CONCLUSIONS

Cancer is a common comorbidity in patients admitted to the ICU with sepsis. The clinical presentation and outcome differs between cancer types. Individuals with metastatic cancer were unlikely to receive prolonged invasive ICU care treatment. Comparable short-term outcome was found for patients with solid tumours and no cancer.

Lipopolysaccharide preconditioning reduces liver metastasis of Colon26 cells by enhancing antitumor activity of natural killer cells and natural killer T cells in murine liver

BACKGROUND AND AIM

Lipopolysaccharide (LPS) preconditioning drastically augments bactericidal activity but reduces the host inflammatory response. Therefore, it may be beneficial to prevent postoperative infectious complications and mitigate host damage by surgical stress. Considering its clinical application, how LPS preconditioning influences the antitumor effect in the liver is an important issue. We then investigated the effect of LPS preconditioning on antitumor activity against Colon26 tumor cells in mice.

METHODS

Lipopolysaccharide preconditioning was induced in mice by the intraperitoneal injection of 5 μg/kg LPS for three consecutive days. Intraportal inoculation of Colon26 cells, which express luminescent protein called Nano-lantern, was performed to evaluate the effect of LPS preconditioning on tumor liver metastasis. The antitumor activities of cytotoxic liver lymphocytes, especially natural killer (NK) cells and natural killer T (NKT) cells, against Colon26 cells were also examined in LPS preconditioned mice.

RESULTS

Lipopolysaccharide preconditioning remarkably prevented liver metastasis of Colon26 cells, as observed by IVIS imaging system, and prolonged survival after tumor inoculation. LPS preconditioning increased the proportions and number of liver NK cells and NKT cells and augmented their intracellular perforin and granzyme B expression, while reducing their intracellular expression of IFN-γ. An in vitro antitumor cytotoxicity assay revealed that LPS preconditioning significantly augmented antitumor cytotoxicities of the liver NK cells and NKT cells, especially NKT cells, against Colon26 cells.

CONCLUSIONS

Lipopolysaccharide preconditioning potently augmented antitumor cytotoxicity of liver NK cells and NKT cells, thereby improving mouse survival after intraportal inoculation of Colon26 tumor cells. It may be useful for perioperative care in oncological patients.

Preventing sepsis; how can artificial intelligence inform the clinical decision-making process? A systematic review

BACKGROUND AND OBJECTIVES

Sepsis is a life-threatening condition that is associated with increased mortality. Artificial intelligence tools can inform clinical decision making by flagging patients at risk of developing infection and subsequent sepsis. This systematic review aims to identify the optimal set of predictors used to train machine learning algorithms to predict the likelihood of an infection and subsequent sepsis.

METHODS

This systematic review was registered in PROSPERO database (CRD42020158685). We conducted a systematic literature review across 3 large databases: Medline, Cumulative Index of Nursing and Allied Health Literature, and Embase. Quantitative primary research studies that focused on sepsis prediction associated with bacterial infection in adults in all care settings were eligible for inclusion.

RESULTS

Seventeen articles met our inclusion criteria. We identified 194 predictors that were used to train machine learning algorithms, with 13 predictors used on average across all included studies. The most prevalent predictors included age, gender, smoking, alcohol intake, heart rate, blood pressure, lactate level, cardiovascular disease, endocrine disease, cancer, chronic kidney disease (eGFR<60 mL/min), white blood cell count, liver dysfunction, surgical approach (open or minimally invasive), and pre-operative haematocrit < 30 %. All included studies used artificial intelligence techniques, with average sensitivity 75.7 ± 17.88, and average specificity 63.08 ± 22.01.

CONCLUSION

The type of predictors influenced the predictive power and predictive timeframe of the developed machine learning algorithm. Predicting the likelihood of sepsis through artificial intelligence can help concentrate finite resources to those patients who are most at risk. Future studies should focus on developing more sensitive and specific algorithms.

Sepsis after elective surgery - Incidence, aetiology and outcome

BACKGROUND

Sepsis requiring admission to intensive care (ICU) is a rare complication of elective surgery, but is associated with high morbidity and mortality. The aim of this study was to describe the incidence and outcome of sepsis following elective surgery.

METHODS

This was a retrospective, observational study where all admissions to Icelandic ICUs during calendar years 2006, 2008, 2010, 2012, 2014 and 2016 were screened, identifing patients with sepsis following elective surgery (ACCP/SCCM criteria). The number of elective operations performed at the largest center (Landspitali) during the study years were collected. Descriptive statistics were used to assess the incidence and outcome of patients with sepsis after elective surgery.

RESULTS

During the study years, 88 patients were admitted to Icelandic ICUs with sepsis following elective surgery. Of those, 80 were operated at Landspitali, where the incidence of sepsis was 0.19% per elective procedure, highest following pancreaticoduodenectomies (14%, CI 6-25) and esophagectomies (13%, CI 4-27), but the greatest number of patients (30% (26/88)) developed sepsis after a colorectal procedure. The most common infection sources were the abdomen (65% (57/88)) and lungs/mediastinum (22% (19/88)), frequently polymicrobial (58% (36/62) of patients with cultures). The incidence of insufficient empirical antibiotics was high (50% (30/60)). The median ICU and hospital length-of-stay were 5.5 and 26 days and the 28-day and 1-year mortality rates were 16% (14/88) and 41% (36/87), respectively.

CONCLUSIONS

Incidence of sepsis following elective surgery is low in Iceland but mortality is high. Initial antimicrobial therapy needs careful consideration in these hospital-acquired, often polymicrobial infections.

Sepsis and Cerebral Dysfunction: BBB Damage, Neuroinflammation, Oxidative Stress, Apoptosis and Autophagy as Key Mediators and the Potential Therapeutic Approaches

Sepsis-associated cerebral dysfunction is complex pathophysiology, generated from primary infections that are developed elsewhere in the body. The neonates, elderly population and chronically ill and long-term hospitalized patients are predominantly vulnerable to sepsis and related cerebral damage. Generally, electrophysiological recordings, severity and sedation scales, computerized imaging and spectroscopy techniques are used for its detection and diagnosis. About the underlying mechanisms, enhanced blood-brain barrier permeability and metalloprotease activity, tight junction protein loss and endothelial cell degeneration promote the influx of inflammatory and toxic mediators into the brain, triggering cerebrovascular damage. An altered neutrophil count and phenotype further dysregulate the normal neuroimmune responses and neuroendocrine stability via modulated activation of protein kinase C-delta, nuclear factor kappa-B and sphingolipid signaling. Glial activation, together with pro-inflammatory cytokines and chemokines and the Toll-like receptor, destabilize the immune system. Moreover, superoxides and hydroperoxides generate oxidative stress and perturb mitochondrial dynamics and ATP synthesis, propagating neuronal injury cycle. Activated mitochondrial apoptotic pathway, characterized by increased caspase-3 and caspase-9 cleavage and Bax/Bcl2 ratio in the hippocampal and cortical neurons, stimulate neurocognitive impairments. Additionally, altered LC3-II/I and P62/SQSTM1, p-mTOR, p-AMPK1 and p-ULK1 levels and dysregulated autophagosome-lysosome fusion decrease neuronal and glial energy homeostasis. The therapies and procedures for attenuating sepsis-induced brain damage include early resuscitation, cerebral blood flow autoregulation, implantable electric vagus nerve stimulation, antioxidants, statins, glucocorticoids, neuroimmune axis modulators and PKCδ inhibitors. The current review enumerates the pathophysiology of sepsis-induced brain damage, its diagnosis, the role of critical inducers and mediators and, ultimately, therapeutic measures attenuating cerebrovascular degeneration.

Impact of a hospital-wide sepsis pathway on improved quality of care and clinical outcomes in surgical patients at a comprehensive cancer centre

PURPOSE

Sepsis is a significant complication following cancer surgery. Although standardised care bundles improve sepsis outcomes in other populations, the benefits in cancer patients are unclear. The objectives of this study were to describe the epidemiology of sepsis in cancer patients post-surgery, and to evaluate the impact of a clinical sepsis pathway on management and clinical outcomes.

METHODS

A standardised hospital-wide sepsis pathway was developed in 2013, and all cases of sepsis at the Peter MacCallum Cancer Centre in 2014 were retrospectively evaluated. Inclusion criteria were sepsis onset during the 100-day period following a surgical procedure for cancer diagnosis. Patients were identified using ICD-10-AM sepsis discharge codes, audit documentation and the hospital's antimicrobial approval system. Sepsis episodes were classified as managed on- or off-pathway.

RESULTS

A total of 119 sepsis episodes were identified. Of these, 71 (59.7%) were managed on the sepsis pathway. Episodes managed on-pathway resulted more frequently in administration of appropriate antibiotics compared to those off-pathway (94.4% vs. 66.7%, p < 0.001), and had shorter time to first-dose antibiotics (median 85 vs. 315 min, p < 0.001). Pathway utilisation was associated with significant reductions in need for inotropes (7% vs. 13%, p = 0.023), ventilation (3% vs. 10%, p = 0.006) and length of hospitalisation (median 15 vs. 30 days, p = 0.008). The most frequent source of infection was organ-space surgical site infection (24.4% of instances).

CONCLUSIONS

A dedicated hospital-wide sepsis pathway had significant impact on the quality of care and clinical outcomes of sepsis in cancer surgery patients. Cost-benefit analysis of sepsis pathways for cancer patients is required.

NICE guidance on sepsis is of limited value in postoperative colorectal patients: the scores that cry 'wolf!'

Background and aims Late recognition of sepsis and consequent death remains a problem. To address this, the National Institute for Health and Care Excellence has published updated guidance recommending the use of the Quick Sequential Organ Failure Assessment (Q-SOFA) score when assessing patients at risk of sepsis following the publication of the Third International Consensus Definitions for Sepsis and Septic Shock. The trauma from major surgery produces a systemic inflammatory response syndrome (SIRS) postoperatively as part of its natural history, which may falsely trigger scoring systems. We aimed to assess the accuracy of Q-SOFA and SIRS criteria as recommended scores for early detection of sepsis and septic complications in the first 48hrs after colorectal cancer surgery. Methods We reviewed all elective major colorectal operations in a single centre during a 12-month period from prospectively maintained electronic records. Results One hundred and thirty nine patients were included in this study. In all, 29 patients developed postoperative infective complications in hospital. Nineteen patients triggered on SIRS without developing infective complications, while 42 patients triggered on Q-SOFA with no infective complications. The area under the ROC curve was 0.52 for Q-SOFA and 0.67 for SIRS. Discussion Q-SOFA appears to perform little better than a coin toss at identifying postoperative sepsis after colorectal cancer resection and is inferior to the SIRS criteria. More work is required to assess whether a combination of scoring criteria, biochemical markers and automated tools could increase accurate detection of postoperative infection and trigger early intervention.