Routine Intensive Care Unit Admission Following Liver Resection: What Is the Value Proposition?

Effect of sarcopenia on postoperative ICU admission and length of stay after hepatic resection for Klatskin tumor

Background

Hepatic resection of Klatskin tumors usually requires postoperative intensive care unit (ICU) admission because of its high morbidity and mortality. Identifying surgical patients who will benefit most from ICU admission is important because of scarce resources but remains difficult. Sarcopenia is characterised by the loss of skeletal muscle mass and is associated with poor surgical outcomes.

Methods

We retrospectively analysed th.e relationship between preoperative sarcopenia and postoperative ICU admission and length of ICU stay (LOS-I) in patients who underwent hepatic resection for Klatskin tumors. Using preoperative computed tomography scans, the cross-sectional area of the psoas muscle at the level of the third lumbar vertebra was measured and normalised to the patient’s height. Using these values, the optimal cut-off for diagnosing sarcopenia was determined using receiver operating characteristic curve analysis for each sex.

Results

Of 330 patients, 150 (45.5%) were diagnosed with sarcopenia. Patients with preoperative sarcopenia presented significantly more frequently to the ICU (77.3% vs. 47.9%, p < 0.001) and had longer total LOS-I (2.45 vs 0.89 days, p < 0.001). Moreover, patients with sarcopenia showed a significantly higher postoperative length of hospital stay, severe complication rate, and in-hospital mortality.

Conclusions

Sarcopenia correlated with poor postoperative outcomes, especially with the increased requirement of postoperative ICU admission and prolonged LOS-I after hepatic resection in patients with Klatskin tumors.

Neuraxial anesthesia in hepato-pancreatic-bilio surgery: a first western pilot study of 46 patients

The most common anesthetic approach in hepato-pancreatic-biliary (HPB) surgery is general anesthesia (GA), but it may result in increased morbidity and mortality and peri-operative risks especially in frail patients. The aim of this study was to assess the safety and effectiveness of neuraxial anesthesia (NA) in HPB in a pilot clinical series. This analysis was conducted on 46 consecutive patients undergoing HPB surgery in an Italian Tertial referral center. Data were prospectively collected and retrospectively analyzed. continuous spinal anesthesia (CSA), combined spino-epidural anesthesia (CSEA) and peridural anesthesia (PA) were used in major and minor hepatectomies and bilio-pancreatic surgery instead of GA. NA was evaluated by analyzing the surgical and anesthesiological short-term outcomes. 46 patients were considered eligible for the study between February 2018 and May 2020. The average age was 69.07 (±  9.95) years. 22 were males and 24 were females. According to the ASA score, 19 (41.30%) patients had ASA II, 22 (47.83%) had ASA III and 5 (10.87%) had ASA IV. 22 (47.83%) patients underwent CSA, 20 (43.48%) CSEA and 4 (8.69%) PA. We performed 8 major and 19 minor hepatectomies, 7 bilio-digestive derivations, 5 Whipple procedures, 4 iatrogenic biliary duct injuries, 2 splenopancreatectomies and 1 hepatic cyst fenestration. Clavien-Dindo ≥ 3 was observed in 3 patients. The conversion rate to endotracheal intubation occurring in 3 of 46 (6.52%) patients. After surgery, no local or pulmonary complications and delirium were reported in our series. The present study demonstrates that NA is a safe and feasible option in selected patients, if performed in referral centers by well-trained anaesthesiologists and surgeons.

Assessment of Factors Associated with Morbidity and Textbook Outcomes of Laparoscopic Liver Resection in Obese Patients: A French Nationwide Study

BACKGROUND

Liver surgeons need to know the expected outcomes of laparoscopic liver resection (LLR) in obese patients.

OBJECTIVE

The purpose of the present study is to assess morbidity, mortality and textbook outcomes (TO) after LLR in obese patients.

METHODS

This is a French multicenter study of patients undergoing LLR between 1996 and 2018. Obesity was defined by a BMI at or above 30 kg/m 2 . Short-term outcomes and TO were compared between obese (ob) and nonobese (non-ob) patients. Factors associated with severe morbidity and TO were investigated.

RESULTS

Of 3,154 patients included, 616 (19.5%) were obese. Ob-group patients had significantly higher American Society of Anesthesiologists (ASA) score and higher incidence of metabolic syndrome and chronic liver disease and were less likely to undergo major hepatectomy. Mortality rates were similar between ob and non-ob groups (0.8 vs 1.1%; p = 0.66). Overall morbidity and hospital stay were significantly increased in the ob group compared with the non-ob group (39.4 vs 34.7%, p = 0.03; and 9.5 vs 8.6 days, p = 0.02), whereas severe 90-day morbidity (at or above Clavien-Dindo grade III) was similar between groups (8% in both groups; p = 0.90). TO rate was significantly lower for the ob group than the non-ob group (58.3 vs 63.7%; p = 0.01). In multivariate analysis, obesity did not emerge as a risk factor for severe 90-day morbidity but was associated with a lower TO rate after LLR (odds ratio = 0.8, 95% CI 0.7-1.0; p = 0.03).

CONCLUSIONS

LLR in obese patients is safe and effective with acceptable mortality and morbidity. Obesity had no impact on severe morbidity but was a factor for failing to achieve TO after LLR.

Nomogram to Predict Intensive Care Following Gastrectomy for Gastric Cancer: A Useful Clinical Tool to Guide the Decision-Making of Intensive Care Unit Admission

BACKGROUND

We aimed to generate and validate a nomogram to predict patients most likely to require intensive care unit (ICU) admission following gastric cancer surgery to improve postoperative outcomes and optimize the allocation of medical resources.

METHODS

We retrospectively analyzed 3,468 patients who underwent gastrectomy for gastric cancer from January 2009 to June 2018. Here, 70.0% of the patients were randomly assigned to the training cohort, and 30.0% were assigned to the validation cohort. Least absolute shrinkage and selection operator (LASSO) method was performed to screen out risk factors for ICU-specific care using the training cohort. Then, based on the results of LASSO regression analysis, multivariable logistic regression analysis was performed to establish the prediction nomogram. The calibration and discrimination of the nomogram were evaluated in the training cohort and validated in the validation cohort. Finally, the clinical usefulness was determined by decision curve analysis (DCA).

RESULTS

Age, the American Society of Anesthesiologists (ASA) score, chronic pulmonary disease, heart disease, hypertension, combined organ resection, and preoperative and/or intraoperative blood transfusions were selected for the model. The concordance index (C-index) of the model was 0.843 in the training cohort and 0.831 in the validation cohort. The calibration curves of the ICU-specific care risk nomogram suggested great agreement in both training and validation cohorts. The DCA showed that the nomogram was clinically useful.

CONCLUSIONS

Age, ASA score, chronic pulmonary disease, heart disease, hypertension, combined organ resection, and preoperative and/or intraoperative blood transfusions were identified as risk factors for ICU-specific care after gastric surgery. A clinically friendly model was generated to identify those most likely to require intensive care.

Perioperative Outcomes for Centers Routinely Admitting Postoperative Endovascular Aortic Aneurysm Repair to the ICU

BACKGROUND

Intensive care unit (ICU) admission after endovascular aortic aneurysm repair (EVAR) varies across medical centers. We evaluated the association of postoperative ICU use with perioperative and long-term outcomes after EVAR.

STUDY DESIGN

The Vascular Quality Initiative (2003-2019) was queried for index elective EVARs. Included centers were categorized by percentage of patients with EVARs postoperatively admitted to the ICU; routine ICU (rICU) centers as ≥80% ICU admissions and nonroutine ICU (nrICU) centers as ≤20% ICU admissions. Patients admitted preoperatively or with same day discharge were excluded. Perioperative outcomes and survival were compared between rICU and nrICU centers.

RESULTS

Of 45,310 EVARs in the database, 35,617 were performed at rICU or nrICU centers - 5,443 (15.3%) at 71 rICU centers and 30,174 (84.7%) at 200 nrICU centers. Overall, mean age was 73.4 years and 81.6% were male. Postoperative myocardial infarction, pulmonary complications, stroke, leg ischemia, and in-hospital mortality were similar between rICU and nrICU centers (all p > 0.05). Postoperative length of stay (LOS) was prolonged at rICU centers (mean) (2.2 ± 3.6 vs 2 ± 4.2 days, p < 0.001). One-year survival was similar between rICU and nrICU centers, respectively, (94.9% vs 95.4%, p = 0.085). When compared with nrICU centers, rICU centers had similar 1-year mortality risk (hazard ratio [HR] 1.15, 95% CI 0.99-1.34, p = 0.076), but were associated with longer postoperative LOS (means ratio 1.1, 95% CI 1.08-1.13, p < 0.001).

CONCLUSIONS

Routine ICU use after EVAR was associated with prolonged postoperative LOS, without improved perioperative/long-term morbidity or mortality. Updated care pathways to include postoperative admission to lower acuity care units may reduce costs without compromising care.

Development and Performance of a Clinical Decision Support Tool to Inform Resource Utilization for Elective Operations

IMPORTANCE

Hospitals ceased most elective procedures during the height of coronavirus disease 2019 (COVID-19) infections. As hospitals begin to recommence elective procedures, it is necessary to have a means to assess how resource intensive a given case may be.

OBJECTIVE

To evaluate the development and performance of a clinical decision support tool to inform resource utilization for elective procedures.

DESIGN, SETTING, AND PARTICIPANTS

In this prognostic study, predictive modeling was used on retrospective electronic health records data from a large academic health system comprising 1 tertiary care hospital and 2 community hospitals of patients undergoing scheduled elective procedures from January 1, 2017, to March 1, 2020. Electronic health records data on case type, patient demographic characteristics, service utilization history, comorbidities, and medications were and abstracted and analyzed. Data were analyzed from April to June 2020.

MAIN OUTCOMES AND MEASURES

Predicitons of hospital length of stay, intensive care unit length of stay, need for mechanical ventilation, and need to be discharged to a skilled nursing facility. These predictions were generated using the random forests algorithm. Predicted probabilities were turned into risk classifications designed to give assessments of resource utilization risk.

RESULTS

Data from the electronic health records of 42 199 patients from 3 hospitals were abstracted for analysis. The median length of stay was 2.3 days (range, 1.3-4.2 days), 6416 patients (15.2%) were admitted to the intensive care unit, 1624 (3.8%) received mechanical ventilation, and 2843 (6.7%) were discharged to a skilled nursing facility. Predictive performance was strong with an area under the receiver operator characteristic ranging from 0.76 to 0.93. Sensitivity of the high-risk and medium-risk groupings was set at 95%. The negative predictive value of the low-risk grouping was 99%. We integrated the models into a daily refreshing Tableau dashboard to guide decision-making.

CONCLUSIONS AND RELEVANCE

The clinical decision support tool is currently being used by surgical leadership to inform case scheduling. This work shows the importance of a learning health care environment in surgical care, using quantitative modeling to guide decision-making.

Influence of hospital teaching status on the chance to achieve a textbook outcome after hepatopancreatic surgery for cancer among Medicare beneficiaries

BACKGROUND

Assessing composite measures of quality such as textbook outcome may be superior to focusing on individual parameters when evaluating hospital performance. The aim of the current study was to assess the impact of teaching hospital status on the occurrence of a textbook outcome after hepatopancreatic surgery.

METHODS

The Medicare Inpatient Standard Analytic Files were used to identify patients undergoing hepatopancreatic surgery from 2013 to 2015 for a malignant indication. Stratified and multivariable regression analyses were performed to determine the relationship between teaching hospital status, hospital surgical volume and textbook outcome.

RESULTS

Among 8,035 Medicare patients (hepatectomy; 41.8%, pancreatectomy; 58.2%), 6,196 (77.1%) patients underwent surgery at a major teaching hospital, whereas 1,839 (22.9%) patients underwent surgery at a minor teaching hospital. Patients undergoing surgery for pancreatic cancer at a major teaching hospital had a greater likelihood of achieving a textbook outcome compared with patients treated at a minor teaching hospital (minor teaching hospital: 456, 40% versus major teaching hospital: 1,606, 45.4%; P = .002). The likelihood of textbook outcome was also greater among patients undergoing hepatopancreatic surgery at high-volume centers (pancreas, low volume: 875, 40.5% versus high volume: 1,187, 47.1% P < .001; liver, low volume: 608, 41.8% versus high volume: 886, 46.6%; P = .005). When examining only major teaching hospitals, patients undergoing a pancreatectomy at a high-volume center had 29% greater odds of achieving a textbook outcome (odds ratio 1.29, 95% confidence interval 1.12-1.49). In contrast, among patients undergoing pancreatic resection at high-volume centers, the odds of achieving a textbook outcome was comparable among major versus minor teaching hospital (odds ratio 1.17, 95% confidence interval 0.89-1.53).

CONCLUSION

The odds of achieving a textbook outcome after pancreatic and hepatic surgery was greater at major versus minor teaching hospitals; however, this effect was largely mediated by hepatopancreatic procedural volume. Patients and payers should focus on regionalization of pancreatic and liver resection to high-volume centers in an effort to optimize the chances of achieving a textbook outcome.