Surgical Apgar score is strongly associated with postoperative ICU admission

Esophageal surgical Apgar score (eSAS): A predictor for postoperative morbidity in patients undergoing neoadjuvant therapy and esophagectomy

BACKGROUND

The surgical Apgar score (SAS) quantifying three intraoperative indexes has been confirmed to be significantly associated with postoperative morbidity and prognosis in many surgical specialties. However, there are great limitations in its application for esophageal cancer (EC). This study aimed to assess the predictive capability of esophagectomy SAS (eSAS) in determining postoperative morbidity and overall survival (OS) in EC patients who had undergone neoadjuvant therapy.

METHODS

A retrospective evaluation was conducted on a cohort of 221 patients in which surgery- and tumor-related data were extracted and analyzed. Major morbidity was defined as complications meeting the criteria of Clavien-Dindo classification III or higher during hospitalization. Univariate and multivariate analyses were performed to identify potential risk factors for major morbidity. Kaplan-Meier analysis was utilized to calculate the OS and relapse-free survival (RFS).

RESULTS

The results exhibited that eSAS demonstrated potential predictive value for postoperative morbidity with an optimal cutoff value of 6. The eSAS and diabetes mellitus were two independent risk factors for the major morbidity; however, no correlation between the eSAS and the OS or RFS was detected.

CONCLUSION

The eSAS could be used as a predictor of major morbidity, while it was not correlated with OS and RFS.

The surgical Apgar score predicts postoperative complications and the survival in lung cancer patients

PURPOSE

The surgical Apgar score (SAS)-calculated using the intraoperative variables estimated blood loss, lowest heart rate, and lowest mean systolic pressure-is associated with mortality in cancer surgery. We investigated the utility of the SAS in patients with lung cancer undergoing surgery.

METHODS

We retrospectively analyzed the data of 691 patients who underwent surgery for primary lung cancer between 2015 and 2019 in a single institute and analyzed the impact of the SAS.

RESULTS

Of the 691 patients, 138 (20%), 57 (8.2%), and 7 (1.0%) had postoperative complications of all grades, grades ≥ III, and grade V, respectively, according to the Clavien-Dindo classification. The C-index for postoperative complications of grades ≥ III was 0.605. A lower score (0-5 points) (odds ratio 3.09 against 8-10 points, P = 0.04) and a lower percentage of vital capacity (odds ratio 0.97, P = 0.04) were independent negative risk factors for major postoperative complications. Patients with a lower score (0-5 points) had poor 5-year overall and cancer-specific survival rates (60.1% and 72.3%, respectively; P < 0.05 for both).

CONCLUSIONS

The surgical Apgar score predicted postoperative complications and the long-term survival. Surgeons may improve surgical results using the SAS.

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 &lt; 0.001) and had longer total LOS-I (2.45 vs 0.89 days, p &lt; 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.

Quality of Recovery After General Anesthesia with Remimazolam in Patients' Undergoing Urologic Surgery: A Randomized Controlled Trial Comparing Remimazolam with Propofol

Background

Remimazolam is a new medication with sedative and hypnotic effects. It has been demonstrated non-inferior to propofol in general anesthesia with regard to efficacy and safety. However, whether general anesthesia with remimazolam is better than propofol in terms of patients' recovery quality remains unknown.

Patients and Methods

Patients enrolled in this study were randomized to remimazolam or propofol group. In remimazolam group, general anesthesia was induced with remimazolam and sufentanil and maintained with remimazolam and remifentanil. In propofol group, general anesthesia was induced with propofol and sufentanil and maintained with propofol and remifentanil. Neuromuscular blocking agent cisatracurium was also injected during anesthesia. Sedation level was monitored by bispectral index (BIS). Our primary outcome was the quality of patients' postoperative recovery, using the Quality of Recovery-15 (QoR-15) scale. Secondary outcomes included SpO2, HR, MBP and frequency of application of vasoactive drugs during anesthesia, as well as incidences of adverse events in the post anesthesia care unit (PACU).

Results

The global scores of QoR-15 scale were lower in remimazolam group at postoperative day 1 and day 3 compared to propofol group, but differences between the two groups only had clinical significance at postoperative day 1. Among the five dimensions of QoR-15 scale, scores for physical comfort and emotional state were lower in remimazolam group than propofol group. MBP and HR were higher in remimazolam group than propofol group after anesthesia induction. SpO2 was similar in the two groups. The frequency of application of vasoactive drugs during anesthesia was higher in propofol group than remimazolam group. There was no statistical difference in the incidences of adverse events between the two groups.

Conclusion

General anesthesia with remimazolam can provide more stable hemodynamics but also cause temporary reduction in the quality of recovery in patients undergoing urologic surgery, compared to propofol.

Development and Validation of a Multivariable Prediction Model for Postoperative Intensive Care Unit Stay in a Broad Surgical Population

IMPORTANCE

Despite limited capacity and expensive cost, there are minimal objective data to guide postoperative allocation of intensive care unit (ICU) beds. The Surgical Risk Preoperative Assessment System (SURPAS) uses 8 preoperative variables to predict many common postoperative complications, but it has not yet been evaluated in predicting postoperative ICU admission.

OBJECTIVE

To determine if the SURPAS model could accurately predict postoperative ICU admission in a broad surgical population.

DESIGN, SETTING, AND PARTICIPANTS

This decision analytical model was a retrospective, observational analysis of prospectively collected patient data from the 2012 to 2018 American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) database, which were merged with individual patients' electronic health record data to capture postoperative ICU use. Multivariable logistic regression modeling was used to determine how the 8 preoperative variables of the SURPAS model predicted ICU use compared with a model inputting all 28 preoperatively available NSQIP variables. Data included in the analysis were collected for the ACS NSQIP at 5 hospitals (1 tertiary academic center, 4 academic affiliated hospitals) within the University of Colorado Health System between January 1, 2012, and December 31, 2018. Included patients were those undergoing surgery in 9 surgical specialties during the 2012 to 2018 period. Data were analyzed from May 29 to July 30, 2021.

EXPOSURE

Surgery in 9 surgical specialties, including general, gynecology, orthopedic, otolaryngology, plastic, thoracic, urology, vascular, and neurosurgery.

MAIN OUTCOMES AND MEASURES

Use of ICU care up to 30 days after surgery.

RESULTS

A total of 34 568 patients were included in the analytical data set: 32 032 (92.7%) in the cohort without postoperative ICU use and 2545 (7.4%) in the cohort with postoperative ICU use (no ICU use: mean [SD] age, 54.9 [16.6] years; 18 188 women [56.8%]; ICU use: mean [SD] age, 60.3 [15.3] years; 1333 men [52.4%]). For the internal chronologic validation of the 7-variable SURPAS model, data from 2012 to 2016 were used as the training data set (n = 24 250, 70.2% of the total sample size of 34 568) and data from 2017 to 2018 were used as the test data set (n = 10 318, 29.8% of the total sample size of 34 568). The C statistic improved in the test data set compared with the training data set (0.933; 95% CI, 0.924-0.941 vs 0.922; 95% CI, 0.917-0.928), whereas the Brier score was slightly worse in the test data set compared with the training data set (0.045; 95% CI, 0.042-0.048 vs 0.045; 95% CI, 0.043-0.047). The SURPAS model compared favorably with the model inputting all 28 NSQIP variables, with both having good calibration between observed and expected outcomes in the Hosmer-Lemeshow graphs and similar Brier scores (model inputting all variables, 0.044; 95% CI, 0.043-0.048; SURPAS model, 0.045; 95% CI, 0.042-0.046) and C statistics (model inputting all variables, 0.929; 95% CI, 0.925-0.934; SURPAS model, 0.925; 95% CI, 0.921-0.930).

CONCLUSIONS AND RELEVANCE

Results of this decision analytical model study revealed that the SURPAS prediction model accurately predicted postoperative ICU use across a diverse surgical population. These results suggest that the SURPAS prediction model can be used to help with preoperative planning and resource allocation of limited ICU beds.

Perioperative Risk Stratification: A Need for an Improved Assessment in Surgery and Anesthesia-A Pilot Study

Background and Objectives: Numerous scoring systems have been introduced into modern medicine. None of the scoring systems assessed both anesthetic and surgical risk of the patient, predict the morbidity, mortality, or the need for postoperative intensive care unit admission. The aim of this study was to compare the anesthetic and surgical scores currently used, for a better evaluation of perioperative risks, morbidity, and mortality. Material and Methods: This is a pilot, prospective, observational study. We enrolled 50 patients scheduled for elective surgery. Anesthetic and surgery risk was assessed using American Society of Anesthesiologists (ASA) scale, Physiological and Operative Severity Score for the enumeration of Mortality and morbidity (P-POSSUM), Acute Physiology and Chronic Health Evaluation (APACHE II), and Surgical APGAR Score (SAS) scores. The real and the estimated length of stay (LOS) were registered. Results: We obtained several statistically significant positive correlations: ASA score–P-POSSUM (p < 0.01, r = 0.465); ASA score–SAS, (p < 0.01, r = −0.446); ASA score–APACHE II, (p < 0.01 r = 0.519); predicted LOS and ASA score (p < 0.01, r = 0.676); predicted LOS and p-POSSUM (p < 0.01, r = 0.433); and predicted LOS and APACHE II (p < 0.01, r = 0.454). A significant negative correlation between predicted LOS, real LOS, ASA class, and SAS (p < 0.05) was observed. We found a statistically significant difference between the predicted and actual LOS (p < 001). Conclusions: Anesthetic, surgical, and severity scores, used together, provide clearer information about mortality, morbidity, and LOS. ASA scale, associated with surgical scores and severity scores, presents a better image of the patient’s progress in the perioperative period. In our study, APACHE II is the best predictor of mortality, followed by P-POSSUM and SAS. P-POSSUM score and ASA scale may be complementary in terms of preoperative physiological factors, providing valuable information for postoperative outcomes.