Combining the ASA Physical Classification System and Continuous Intraoperative Surgical Apgar Score Measurement in Predicting Postoperative Risk

Ability to predict surgical outcomes by surgical Apgar score: a systematic review

BACKGROUND

The Surgical Apgar score (SAS) is a straightforward and unbiased measure to assess the probability of experiencing complications after surgery. It is calculated upon completion of the surgical procedure and provides valuable predictive information. The SAS evaluates three specific factors during surgery: the estimated amount of blood loss (EBL), the lowest recorded mean arterial pressure (MAP), and the lowest heart rate (LHR) observed. Considering these factors, the SAS offers insights into the probability of encountering postoperative complications.

METHODS

Three authors independently searched the Medline, PubMed, Web of Science, Scopus, and Embase databases until June 2022. This search was conducted without any language or timeframe restrictions, and it aimed to cover relevant literature on the subject. The inclusion criteria were the correlation between SAS and any modified/adjusted SAS (m SAS, (Modified SAS). eSAS, M eSAS, and SASA), and complications before, during, and after surgeries. Nevertheless, the study excluded letters to the editor, reviews, and case reports. Additionally, the researchers employed Begg and Egger's regression model to evaluate publication bias.

RESULTS

In this systematic study, a total of 78 studies \were examined. The findings exposed that SAS was effective in anticipating short-term complications and served as factor for a long-term prognostic following multiple surgeries. While the SAS has been validated across various surgical subspecialties, based on the available evidence, the algorithm's modifications may be necessary to enhance its predictive accuracy within each specific subspecialty.

CONCLUSIONS

The SAS enables surgeons and anesthesiologists to recognize patients at a higher risk for certain complications or adverse events. By either modifying the SAS (Modified SAS) or combining it with ASA criteria, healthcare professionals can enhance their ability to identify patients who require continuous observation and follow-up as they go through the postoperative period. This approach would improve the accuracy of identifying individuals at risk and ensure appropriate measures to provide necessary care and support.

Improved Re-estimation of Perioperative Cardiac Risk Using the Surgical Apgar Score: A Retrospective Cohort Study

OBJECTIVE

To assess whether the Surgical Apgar Score (SAS) improves re-estimation of perioperative cardiac risk.

BACKGROUND

The SAS is a novel risk index that integrates three relevant and easily measurable intraoperative parameters (blood loss, heart rate, mean arterial pressure) to predict outcomes. The incremental prognostic value of the SAS when used in combination with standard preoperative risk indices is unclear.

METHODS

We conducted a retrospective cohort study of adults (18 years and older) who underwent elective noncardiac surgery at a quaternary care hospital in Canada (2009-2014). The primary outcome was postoperative acute myocardial injury. The SAS (range 0-10) was calculated based on intraoperative estimated blood loss, lowest mean arterial pressure, and lowest heart rate documented in electronic medical records. Incremental prognostic value of the SAS when combined with the Revised Cardiac Risk Index was assessed based on discrimination (c-statistic), reclassification (integrated discrimination improvement, net reclassification index), and clinical utility (decision curve analysis).

RESULTS

The cohort included 16,835 patients, of whom 607 (3.6%) patients had acute postoperative myocardial injury. Addition of the SAS to the Revised Cardiac Risk Index improved risk estimation based on the integrated discrimination improvement [2.0%; 95% confidence interval (CI): 1.5%-2.4%], continuous net reclassification index (54%; 95% CI: 46%-62%), and c-index, which increased from 0.68 (95% CI: 0.65-0.70) to 0.75 (95% CI: 0.73-0.77). On decision curve analysis, addition of the SAS to the Revised Cardiac Risk Index resulted in a higher net benefit at all decision thresholds.

CONCLUSIONS

When combined with a validated preoperative risk index, the SAS improved the accuracy of cardiac risk assessment for noncardiac surgery. Further research is needed to delineate how intraoperative data can better guide postoperative decision-making.

The Surgical Apgar Score: A Systematic Review of Its Discriminatory Performance

To review the current literature evaluating the performance of the Surgical Apgar Score (SAS).

Background

The SAS is a simple metric calculated at the end of surgery that provides clinicians with information about a patient's postoperative risk of morbidity and mortality. The SAS differs from other prognostic models in that it is calculated from intraoperative rather than preoperative parameters. The SAS was originally derived and validated in a general and vascular surgery population. Since its inception, it has been evaluated in many other surgical disciplines, large heterogeneous surgical populations, and various countries.

Methods

A database and gray literature search was performed on March 3, 2020. Identified articles were reviewed for applicability and study quality with prespecified inclusion criteria, exclusion criteria, and quality requirements. Thirty-six observational studies are included for review. Data were systematically extracted and tabulated independently and in duplicate by two investigators with differences resolved by consensus.

Results

All 36 included studies reported metrics of discrimination. When using the SAS to correctly identify postoperative morbidity, the area under the receiver operating characteristic curve or concordance-statistic ranged from 0.59 in a general orthopedic surgery population to 0.872 in an orthopedic spine surgery population. When using the SAS to identify mortality, the area under the receiver operating characteristic curve or concordance-statistic ranged from 0.63 in a combined surgical population to 0.92 in a general and vascular surgery population.

Conclusions

The SAS provides a moderate and consistent degree of discrimination for postoperative morbidity and mortality across multiple surgical disciplines.

Which Frailty Evaluation Method Can Better Improve the Predictive Ability of the SASA for Postoperative Complications of Patients Undergoing Elective Abdominal Surgery?

Purpose

To determine which frailty method can better improve the predictive ability of the Surgical Apgar Score combined with American Society of Anesthesiologists physical status classification (SASA).

Patients and Methods

A prospective cohort study was conducted. A total of 194 elderly patients undergoing elective abdominal surgery were included. Preoperative frailty using FRAIL questionnaire, frailty index (FI), Clinical Frailty Scale (CFS) and SASA scores was assessed. Primary outcome was in-hospital Clavien-Dindo ≥grade II complications. Multiple logistic regression was used to examine the association between frailty and complications. Receiver operating characteristic curves were used to explore the predictive ability of frailty.

Results

According to the FRAIL, FI and CFS criteria, the prevalence of frailty in the study population was 43.8%, 32.5%, and 36.6%, respectively. After adjusting for all covariates, frailty was significantly associated with postoperative complications in hospital by FRAIL [odds ratio: 5.11, 95% CI: 1.41–18.44, P = 0.013], by FI [OR: 4.25, 95% CI: 1.21–14.90, P = 0.024] and by CFS [OR: 5.10, 95% CI: 1.52–17.17, P = 0.008]. The area under the curve (AUC) for SASA was 0.768 (95% CI: 0.702–0.826). Addition of frailty assessment (FRAIL, FI and CFS) increased the AUC to 0.787 (95% CI: 0.722–0.842), 0.798 (95% CI: 0.734–0.852), and 0.815 (95% CI: 0.753–0.867), respectively. Compared to SASA, only addition of CFS had a significant difference (P = 0.0478).

Conclusion

Frailty is an effective predictor of postoperative complications in elderly Chinese patients undergoing elective abdominal surgery. Frailty assessment of CFS can better improve the predictive ability of SASA.

Surgical Apgar score is strongly associated with postoperative ICU admission

Immediate postoperative intensive care unit (ICU) admission can increase the survival rate in patients undergoing high-risk surgeries. Nevertheless, less than 15% of such patients are immediately admitted to the ICU due to no reliable criteria for admission. The surgical Apgar score (SAS) (0–10) can be used to predict postoperative complications, mortality rates, and ICU admission after high-risk intra-abdominal surgery. Our study was performed to determine the relationship between the SAS and postoperative ICU transfer after all surgeries. All patients undergoing operative anesthesia were retrospectively enrolled. Among 13,139 patients, 68.4% and < 9% of whom had a SASs of 7–10 and 0–4. Patients transferred to the ICU immediately after surgery was 7.8%. Age, sex, American Society of Anesthesiologists (ASA) class, emergency surgery, and the SAS were associated with ICU admission. The odds ratios for ICU admission in patients with SASs of 0–2, 3–4, and 5–6 were 5.2, 2.26, and 1.73, respectively (P < 0.001). In general, a higher ASA classification and a lower SAS were associated with higher rates of postoperative ICU admission after all surgeries. Although the SAS is calculated intraoperatively, it is a powerful tool for clinical decision-making regarding the immediate postoperative ICU transfer.

Surgical risk assessment for gynecological oncologic patients

Objective

Preoperative surgical risk assessment is important in terms of postoperative morbidity and mortality. Therefore, it is necessary to evaluate the efficacy and safety of these surgeries via an ideal risk assessment model, and reduce risks via applying some findings (for instance, perioperative beta-blockers). There are some risk assessment systems, but these have generally not been verified for patients with gynecologic cancer. The aim of this study was to assess the risk of surgery for gynecological oncologic patients and suggest an easy risk assessment model and risk reduction by applying our findings.

Materials and Methods

We retrospectively analyzed 258 gynecologic patients with cancer. Age, diagnosis, staging, performance scale, metoprolol use, heart, renal diabetes, Chronic Obstructive Pulmonary disease, diabetes, operation type and length, carcinoma antigen 125, ascites, albumin, surgical procedure, hospitalization length, and complications were recorded.

Results

Of the 258 patients, 173 patients (67.1%) had no complications, 43 patients (16.7%) had one and 42 patients (16.3%) had two or more complications. The most common complication was the acid-base imbalance (14%), followed by urinary tract infection (9.7%). Parameters associated with complications were performance status, ascites, operating length, metoprolol use, and upper abdominal surgery. In our proposed scoring model with a total score range 0-23, cut-off value points for both the presence and rate of complications was found as >5.

Conclusion

In gynecological patients with cancer, the addition of metoprolol use and upper abdominal surgery within preoperative risk assessment evaluation parameters are significantly effective in predicting the rate and severity of complications. Moreover, we have suggested a simple, practical, and convenient scoring model for this evaluation.

Who is a high-risk surgical patient?

PURPOSE OF REVIEW

Timely identification of high-risk surgical candidates facilitate surgical decision-making and allows appropriate tailoring of perioperative management strategies. This review aims to summarize the recent advances in perioperative risk stratification.

RECENT FINDINGS

Use of indices which include various combinations of preoperative and postoperative variables remain the most commonly used risk-stratification strategy. Incorporation of biomarkers (troponin and natriuretic peptides), comprehensive objective assessment of functional capacity, and frailty into the current framework enhance perioperative risk estimation. Intraoperative hemodynamic parameters can provide further signals towards identifying patients at risk of adverse postoperative outcomes. Implementation of machine-learning algorithms is showing promising results in real-time forecasting of perioperative outcomes.

SUMMARY

Perioperative risk estimation is multidimensional including validated indices, biomarkers, functional capacity estimation, and intraoperative hemodynamics. Identification and implementation of targeted strategies which mitigate predicted risk remains a greater challenge.

Postoperative complications following colonic resection for cancer are associated with impaired long-term survival

AIM

Surgery for colorectal cancer is associated with a high incidence of postoperative complications. The aim of this study was to analyse whether postoperative complications following radical resection for colorectal cancer are associated with increased recurrence rate and impaired survival.

METHOD

Patients operated for colon cancer between 2007 and 2009 with curative intent were identified through the Swedish Colorectal Cancer Registry. The cohort was divided into three subgroups: patients who developed severe postoperative complications, patients who developed non-severe complications and patients who did not develop any complication (controls).

RESULTS

Of 6779 patients included in the study, 640 (9%) developed severe complications, 994 (15%) non-severe complications and 5145 (76%) had no complications. The 5-year overall survival rate was 60.3% in the severe complication group, 64.2% in the non-severe complication group and 72.8% in the control group (P < 0.01). The 3-year disease-free survival rate was 66.8%, 70.9% and 77.8% respectively (P < 0.01). The recurrence rate did not differ between the three groups. In multivariate analysis, both severe and non-severe complications were found to be risk factors for decreased overall survival at 5 years [hazard ratio (HR) 1.38, 95% CI 1.47-1.92, and HR 1.18, 95% CI 1.27-1.60 respectively; P < 0.05) as well as for decreased 3-year disease-free survival (HR 1.37, 95% CI 1.14-1.65, and HR 1.26, 95% CI 1.08-1.48 respectively; P < 0.05).

CONCLUSION

Complications after colonic resection for cancer are associated with impaired 5-year overall survival and 3-year disease-free survival and exhibit more severe postoperative complications, mainly via mechanisms other than cancer recurrence.

Frailty and postoperative complications in older Chinese adults undergoing major thoracic and abdominal surgery

Purpose: To determine the association between frailty and postoperative complications in elderly Chinese patients and to determine whether addition of frailty assessment improves the predictive ability of the American Society of Anesthesiologists (ASA) score, Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM), and Estimation of Physiologic Ability and Surgical Stress (E-PASS) score.

Patients and methods: A prospective cohort study was conducted in a tertiary hospital. Elderly patients undergoing major thoracic or abdominal surgery were included. Frailty phenotype and ASA, POSSUM, and E-PASS scores were assessed. Demographic, preoperative, and surgical variables were extracted from medical records. Primary outcome measure was in-hospital Clavien-Dindo ≥ grade II complications. Multiple logistic regression was used to examine the association between frailty and complications. Receiver operating characteristic curves were used to explore the predictive ability of frailty.

Results: Prevalence of frailty was 26.12%. Significant differences were observed between the frail and non-frail groups with respect to age, Activities of Daily Living, Charlson Comorbidity Index, respiratory function, presence of malignancy, serum albumin, prealbumin, and hemoglobin levels (P<0.05). ASA, POSSUM, and E-PASS scores were higher in the frail group. After adjusting for all covariates, frailty was significantly associated with postoperative complications in hospital [odds ratio: 16.59, 95% CI: 4.56–60.40, P<0.001]. The area under the curve (AUC) for frailty was 0.762 (95% CI: 0.703–0.814). The AUC for ASA, POSSUM, and E-PASS for prediction of complications was 0.751 (95% CI: 0.692–0.804), 0.762 (95% CI: 0.704–0.814), and 0.824 (95% CI: 0.771–0.870), respectively. Addition of frailty assessment increased the AUC to 0.858 (95% CI: 0.808–0.899), 0.842 (95% CI: 0.790–0.885), and 0.854 (95% CI: 0.803–0.896), respectively.

Conclusion: Frailty is an effective predictor of postoperative complications in elderly Chinese patients undergoing major thoracic and abdominal surgery. Frailty assessment can improve the predictive ability of current surgical risk assessment tools. Frailty phenotype should be considered perioperatively. Frailty assessment could also expand the scope for nurses to evaluate patients for safety management.

Prediction of perioperative complications after robotic-assisted radical hysterectomy for cervical cancer using the modified surgical Apgar score

BACKGROUND

Although there has been marked development in surgical techniques, there is no easy and fast method of predicting complications in minimally invasive surgeries. We evaluated whether the modified surgical Apgar score (MSAS) could predict perioperative complications in patients undergoing robotic-assisted radical hysterectomy.

METHODS

All patients with cervical cancer undergoing robotic-assisted radical hysterectomy at our institution between January 2011 and May 2017 were included. Their clinical characteristics were retrieved from their medical records. The surgical Apgar score (SAS) was calculated from the estimated blood loss, lowest mean arterial pressure, and lowest heart rate during surgery. We modified the SAS considering the lesser blood loss typical of robotic surgeries. Perioperative complications were defined using a previous study and the Clavien-Dindo classification and subdivided into intraoperative and postoperative complications. We analyzed the association of perioperative complications with low MSAS.

RESULTS

A total of 138 patients were divided into 2 groups: with (n = 53) and without (n = 85) complications. According to the Clavien-Dindo classification, 49 perioperative complications were classified under Grade I (73.1%); 13, under Grade II (19.4%); and 5, under Grade III (7.5%); 0, under both Grade IV and Grade V. Perioperative complications were significantly associated with surgical time (p = 0.026). The MSAS had a correlation with perioperative complications (p = 0.047). The low MSAS (MSAS, ≤6; n = 52) group had significantly more complications [40 (76.9%), p = 0.01]. Intraoperative complications were more correlated with a low MSAS than were postoperative complications [1 (1.2%) vs. 21 (40.4%); p < 0.001, 13 (15.1%) vs. 25 (48.1%); p = 0.29, respectively]. We also analyzed the risk-stratified MSAS in 3 subgroups: low (MSAS, 7-10), moderate (MSAS 5-6), and high risks (MSAS, 0-4). The prevalence of intraoperative complications significantly increased as the MSAS decreased p = 0.01).

CONCLUSIONS

This study was consistent the concept that the intuitive and simple MSAS might be more useful in predicting intraoperative complications than in predicting postoperative complications in minimally invasive surgeries, such as robotic-assisted radical hysterectomy for cervical cancer.

[CR-POSSUM and Surgical Apgar Score as predictive factors for patients' allocation after colorectal surgery]

BACKGROUND AND OBJECTIVES

Surgical patients frequently require admission in high-dependency units or intensive care units. Resources are scarce and there are no universally accepted admission criteria, so patients' allocation must be optimized. The purpose of this study was to investigate the relationship between postoperative destination of patients submitted to colorectal surgery and the scores ColoRectal Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (CR-POSSUM) and Surgical Apgar Score (SAS) and, secondarily find cut-offs to aid this allocation.

METHODS

A cross-sectional prospective observational study, including all adult patients undergoing colorectal surgery during a 2 years period. Data collected from the electronic clinical process and anesthesia records.

RESULTS

A total of 358 patients were included. Median score for SAS was 8 and CR-POSSUM had a median mortality probability of 4.5%. Immediate admission on high-dependency units/intensive care units occurred in 51 patients and late admission in 18. Scores from ward and high-dependency units/intensive care units patients were statistically different (SAS: 8 vs. 7, p<0.001; CR-POSSUM: 4.4% vs. 15.9%, p<0.001). Both scores were found to be predictors of immediate postoperative destination (p<0.001). Concerning immediate high-dependency units/intensive care units admission, CR-POSSUM showed a strong association (AUC 0.78, p=0.034) with a ≥9.16 cut-off point (sensitivity: 62.5%; specificity: 75.2%), outperforming SAS (AUC 0.67, p=0.048), with a ≤7 cut-off point (sensitivity: 67.3%; specificity: 56.1%).

CONCLUSIONS

Both CR-POSSUM and SAS were associated with the clinical decision to admit a patient to the high-dependency units/intensive care units immediately after surgery. CR-POSSUM alone showed a better discriminative capacity.

Utility of the Modified Surgical Apgar Score in a Head and Neck Cancer Population

Objective The Surgical Apgar Score (SAS) is a validated postoperative complication prediction model. The purpose of this study was to investigate the utility of the SAS in a diverse head and neck cancer population and to compare it with a recently developed modified SAS (mSAS) that accounts for intraoperative transfusion. Study Design Case series with chart review. Setting Academic tertiary care medical center. Subjects and Methods This study comprised 713 patients undergoing surgery for head and neck cancer from April 2012 to March 2015. SAS values were calculated according to intraoperative data obtained from anesthesia records. The mSAS was computed by assigning an estimated blood loss score of zero for patients receiving intraoperative transfusions. Primary outcome was 30-day postoperative morbidity. Results Mean SAS and mSAS were 6.3 ± 1.5 and 6.2 ± 1.7, respectively. SAS and mSAS were significantly associated with 30-day postoperative morbidity, length of stay, operative time, American Society of Anesthesiologists status, race, and body mass index ( P < .05); however, no significant association was detected for age, sex, and smoking status. Multivariable analysis identified SAS and mSAS as independent predictors of postoperative morbidity, with the mSAS ( P = .03) being a more robust predictor than the SAS ( P = .15). Strong inverse relationships were demonstrated for the SAS and mSAS with length of stay and operative time ( P < .0001). Conclusion The SAS serves as a useful metric for risk stratification of patients with head and neck cancer. With the inclusion of intraoperative transfusion, the mSAS demonstrates superior utility in predicting those at risk for postoperative complications.

The Reliability of Surgical Apgar Score in Predicting Immediate and Late Postoperative Morbidity and Mortality: A Narrative Review

Surgical Apgar Score is a simple, 10-point scoring system in which a low score reliably identifies those patients at risk for adverse perioperative outcomes. Surgical techniques and anesthesia management should be directed in such a way that the Surgical Apgar Score remains higher to avoid postoperative morbidity and mortality.