Assessment of the Surgical Apgar Score in a Swedish setting

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.

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.

Development and validation of a nomogram to predict complications in patients undergoing simultaneous bilateral total knee arthroplasty: A retrospective study from two centers

Purpose

Complications were significantly increased 30 days after Simultaneous bilateral total knee arthroplasty (SBTKA). In this study, an individualized nomogram was established and validated to predict the complications within 30 days after SBTKA.

Methods

The general data of 861 patients (training set) who received SBTKA in The Affiliated Hospital of Qingdao University between January 1, 2012 and March 31, 2017 were retrospectively analyzed. All patients were divided into complication group (n = 96) and non-complication group (n = 765) according to the incidence of complications within 30 years after SBTKA. Independent risk factors for postoperative SBTKA complications were identified and screened by binary logistic regression analyses, and then a nomogram prediction model was constructed using R software. The area under curve (AUC), calibration curve, and decision curve analysis (DCA) were selected to evaluate the line-chart. Meanwhile, 396 patients receiving SBTKA in the Third Hospital of Hebei Medical University who met the inclusion and exclusion criteria (test set) were selected to verify the nomogram.

Results

Five independent predictors were identified by binary logistic regression analyses and a nomogram was established. The AUC of this nomogram curve is 0.851 (95% CI: 0.819-0.883) and 0.818 (95% CI: 0.735-0.900) in the training and testing sets, respectively. In the training set and test set, calibration curves show that nomogram prediction results are in good agreement with actual observation results, and DCA shows that nomogram prediction results have good clinical application value.

Conclusion

Older age, lower preoperative hemoglobin level, higher preoperative blood urea nitrogen (BUN) level, longer operation time, ASA grade ≥ III are independent predictors of SBTKA complications within 30 days after surgery. A nomogram containing these five predictors can accurately predict the risk of complications within 30 days after SBTKA.

A nomogram to predict prolonged postoperative ileus after intestinal resection for Crohn's disease

PURPOSE

We aim to identify the risk factors of PPOI in patients with CD and create a nomogram for prediction of PPOI for CD.

METHODS

Data on 462 patients who underwent partial intestinal resection for CD in Jin-ling Hospital between January 2019 and June 2021 were retrospectively collected. Univariate and multivariate analyses were performed to determine the risk factors for PPOI and we used the risk factors to create a nomogram. Then we used the Bootstrap-Concordance index and calibration diagrams to evaluate the performance of the Nomogram. Decision curve analysis was performed to evaluate clinical practicability of the model.

RESULTS

The incidence of PPOI was 27.7% (n of N). Course of CD ≥ 10 years, operation time ≥ 154 min, the lowest mean arterial pressure ≤ 76.2 mmHg, in-out balance per body weight ≥ 22.90 ml/kg, post-op day 1 infusion ≥ 2847 ml, post-op lowest K⁺  ≤ 3.75 mmol/L, and post-op day 1 procalcitonin ≥ 2.445 ng/ml were identified as the independent risk factors of PPOI in patients with CD. The nomogram we created by these risk factors presented with good discriminative ability (concordance index 0.723) and was moderately calibrated (bootstrapped concordance index 0.704). The results of decision curve analysis showed that the nomogram was clinically effective within probability thresholds in the 8 to 66% range.

CONCLUSION

The nomogram we developed is helpful to evaluate the risk of developing PPOI after partial intestinal resection for CD. Clinicians can take more necessary measures to prevent PPOI in CD's patients or at least minimize the incidence.

Prediction of 90-Day Local Complications in Patients After Total Knee Arthroplasty: A Nomogram With External Validation

Background:

Local complications after total knee arthroplasty (TKA) significantly affect the patient’s prognosis. Nomograms can be a useful tool for predicting such complications.

Purpose:

To compare the preoperative and intraoperative factors of patients who underwent TKA with and without complications and to construct and validate a nomogram based on selective predictors of local complications within 90 days postoperatively.

Study Design:

Case-control study; Level of evidence, 3.

Methods:

The nomogram was developed in a primary cohort that consisted of 410 patients who underwent primary TKA at the authors’ institution between January 2015 and September 2018. Predictor variables included 4 major local complications that can occur within 90 days: reoperation (including implant revision or removal for any reason and manipulation under anesthesia), infection, bleeding requiring ≥4 unit transfusion of red blood cells within 72 hours of surgery, and peripheral nerve injury. The authors used least absolute shrinkage and selection operator (LASSO) regression analysis for data dimension reduction and feature selection. Multivariable logistic regression analysis was used to develop the nomogram. Performance of the nomogram was assessed using C-index, calibration plot, area under the receiver operating characteristic curve (AUC), and decision curve analysis (DCA). The model was subjected to bootstrap validation and external validation using a prospective cohort of 249 patients.

Results:

Four significantly prognostic factors were incorporated into the nomogram: age-adjusted Charlson Comorbidity Index, American Society of Anesthesiologists score, tourniquet time, and estimated intraoperative blood loss. The model displayed good discrimination, with a C-index of 0.819 and an AUC of 0.819. The calibration curves showed optimal agreement between nomogram prediction and actual observation. A high C-index value of 0.801 could still be reached in bootstrap validation. Application of the nomogram in the validation cohort showed good discrimination (C-index, 0.731) and good calibration. DCA demonstrated that the nomogram was clinically useful.

Conclusion:

The authors developed and validated a novel nomogram that can provide individual prediction of local complications within 90 days for patients after TKA. This practical tool may be conveniently used to estimate individual risk and help clinicians take measures to minimize or prevent the incidence of complications.

de Izquierdo S, García-Gallont R. Utilidad del puntaje Apgar quirúrgico como factor pronóstico de complicaciones postoperatorias

Introducción: El puntaje Apgar Quirúrgico (SAS) es un sistema de evaluación simple y confiable que identifica a los pacientes que presentan riesgos de eventos perioperatorios.  Objetivo: Determinar la utilidad del puntaje SAS como factor pronóstico de complicaciones mayores en los 30 días postoperatorios. Metodología: Este es un estudio de serie de casos, retrospectivo transversal, desarrollado con información de expedientes clínicos de 263 pacientes sometidos a cirugía mayor en el Hospital Herrera Llerandi de la Ciudad de Guatemala, durante los meses de enero a abril, 2018. Resultados: utilizando la prueba de Chi cuadrado se comprobó que existe relación entre el puntaje SAS y la presencia de complicaciones postoperatorias. Conclusión: El puntaje SAS es útil como factor pronóstico de complicaciones postoperatorias.

A simple nomogram for predicting early complications in patients after primary knee arthroplasty

BACKGROUND

This study sought to construct a nomogram for patients based on preoperative and intraoperative variables to individually predict the likelihood of complications within 30 days after primary knee arthroplasty.

METHODS

Data were obtained from the medical record of patients who underwent primary knee arthroplasty at our institution from 2015 to 2018. Preoperative and intraoperative factors were collected critically. Predictor variables include 15 common complications occurring within 30 days. The predictive model was developed using multivariable logistic regression and least absolute shrinkage and selection operator regression. Clinical usefulness and calibration of the predicting model were assessed using C-index, calibration plot, receiver operating curve, and decision curve analysis. Internal validation was assessed using the bootstrapping validation.

RESULTS

The prediction nomogram identified six variables associated with complications, including hemoglobin, tourniquet time, operative time, estimated intraoperative blood loss, American Society of Anesthesiologists Classification (ASA class) and type of anesthesia. The model displayed good discrimination with a C-index of 0.822 (95% confidence interval: 0.760-0.884), an area under the curve of 0.822 and good calibration. High C-index value of 0.810 could still be reached in the interval validation. Decision curve analysis showed that the nomogram was clinically useful when intervention was decided at the complications possibility threshold in the three percent to 100% range.

CONCLUSION

We constructed and validated a nomogram for predicting the probability of postoperative complications within 30 days after primary knee arthroplasty. Our nomogram may prove to be a useful tool for guiding physicians in terms of their decisions.

Outcomes of patients on dual antiplatelet therapy post-coronary stenting following emergency noncardiac surgery

BACKGROUND

The outcomes of patients on dual antiplatelet therapy (DAPT) post-coronary stenting following emergency noncardiac surgery remain unclear.

METHODS

This retrospective cohort study included patients on DAPT post-coronary stenting who underwent emergency noncardiac surgery within 24 hours of diagnosis from April 2007 to March 2018 where DAPT was discontinued within <5 days for aspirin and 7 days for P2Y₁₂ inhibitors. Our primary outcome was 180-day mortality in these patients. We investigated factors associated with bleeding within 180 days after surgery as our secondary outcome and exploratorily examined factors affecting 180-day mortality.

RESULTS

Of 62,528 patients who underwent any surgery under general anaesthesia during the 11-year study period, 133 patients (0.22% of all and 1.41% of emergency surgical patients) were analysed. Among the eligible patients, 180-day mortality was 9.8% (13/133). Eighteen patients (13.5%) developed bleeding within 180 days after surgery, which was the most common post-operative complication. Restarting antiplatelet agents <2 days post-operatively (OR, 4.51; 95% CI, 1.56-13.0; P = 0.005) and stent implantation at bifurcation lesions before surgery (OR, 3.28; 95% CI, 1.07-10.1; P = 0.04) were associated with post-operative bleeding. Patients on haemodialysis had the worse prognosis (hazard ratio, 5.73; 95% CI, 1.87-17.5; P = 0.002) in terms of 180-day mortality.

CONCLUSION

The 180-day mortality following emergency noncardiac surgery was approximately 10% in patients on DAPT post-coronary stenting. Restarting antiplatelet agents earlier than 2 days post-operatively and coronary stenting at bifurcation lesions were associated with bleeding within 180 days after surgery.

Does the Surgical Apgar Score predict serious complications after elective major cancer surgery?

BACKGROUND

Major cancer surgery is associated with significant risks of perioperative morbidity and mortality, resulting in delayed adjuvant therapy, higher recurrence rates, and worse overall survival. Previous retrospective studies have used the Surgical Apgar Score (SAS) for perioperative risk assessment. This study prospectively evaluated the predictive value of SAS to predict serious complication (SC) after elective major cancer surgery.

METHODS

Demographic, comorbidity, procedure, and intraoperative data were collected prospectively for 405 patients undergoing elective major cancer surgery between 2014-17. The SAS was calculated immediately postoperative and outcome data were collected prospectively. Rates of SC according to SAS risk category were compared using Cochran-Armitage trend test. Receiver operating characteristic curves and area under the receiver operating characteristic curves were generated and 95% confidence intervals were calculated.

RESULTS

Eighty percent, 17.3%, and 2.7% of patients were low (SAS 7-10), intermediate (SAS 5-6), and high risk (SAS 0-4), respectively, for SC based on their SAS. Forty-six (11.4%) had an SC within 30 days; 3.7% returned to the operating room, 3.7% experienced a urinary tract infection, 3.2% experienced a respiratory complication, 2.7% experienced a wound complication, and 1.2% experienced a cardiac complication. Overall, 9.3%, 18.6%, and 27.3% of patients with SAS 7-10, 5-6, and 0-4 experienced an SC, respectively (P = 0.005). The overall discriminatory ability of the SAS was modest (area under the receiver operating characteristic curves 0.661; 95% confidence intervals, 0.582-0.740).

CONCLUSIONS

Although there was an overall association between SAS and higher risk of subsequent postoperative SC in our cohort, the ability of the SAS to accurately predict risk of postoperative SC at the patient level was limited.

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.

Impact of systemic inflammatory response syndrome and surgical Apgar score on post-operative acute kidney injury

BACKGROUND

Surgical Apgar Score (SAS) is relatively weakly associated with post-operative outcomes in emergency surgery, compared with elective surgery. A combination of systemic inflammatory response syndrome (SIRS) and SAS may be useful for prediction of poor outcomes after emergency surgery.

METHODS

A retrospective study was conducted in patients who underwent emergency abdominal or cerebral surgery from January 2005 to December 2010. AKI was diagnosed using Acute Kidney Injury Network criteria for 2 days after surgery. Pre-operative SIRS was defined as SIRS score ≥ 2. Patients were divided into those with SAS ≥ 5 and < 5. Independent risk factors for post-operative AKI were identified. Ability to predict post-operative AKI was determined using receiver operating characteristic (ROC) curve analysis.

RESULTS

Of 742 patients, 175 (24%) had post-operative AKI. Pre-operative SIRS (OR 1.9, 95% CI: 1.2-2.9, P < 0.01) and SAS < 5 (OR 2.6, 95% CI: 1.7-4.1, P < 0.01) were independent risk factors for post-operative AKI. Patients without SIRS and SAS < 5 had an increased risk of post-operative AKI (odds ratio (OR) 3.6, 95% confidence interval (CI) 1.9-6.7, P < 0.01) and those with SIRS and SAS < 5 had increased risks of post-operative AKI (OR 5.9, 95% CI: 3.7-9.3, P < 0.01) and hospital mortality (OR 3.5, 95% CI: 1.9-6.3, P < 0.01). In ROC analysis, the c-statistic using both SIRS and SAS < 5 was 0.81 (95% CI: 0.77-0.84, P < 0.01) and higher than without use of these factors (P < 0.01).

CONCLUSION

Pre-operative SIRS and SAS are independently associated with post-operative AKI. Simultaneous use of pre-operative SIRS and SAS may improve prediction of poor post-operative outcomes.

Surgical apgar score predicts early complication in transfemoral amputees: Retrospective study of 170 major amputations

AIM

To assess whether the surgical apgar score (SAS) is a prognostic tool capable of identifying patients at risk of major complications following lower extremity amputations surgery.

METHODS

This was a single-center, retrospective observational cohort study conducted between January 2013 and April 2015. All patients who had either a primary transtibial amputation (TTA) or transfemoral amputation (TFA) conducted at our institution during the study period were assessed for inclusion. All TTA patients underwent a standardized one-stage operative procedure (ad modum Persson amputation) performed approximately 10 cm below the knee joint. All TTA procedures were performed with sagittal flaps. TFA procedures were performed in one stage with amputation approximately 10 cm above the knee joint, performed with anterior/posterior flaps. Trained residents or senior consultants performed the surgical procedures. The SAS is based on intraoperative heart rate, blood pressure and blood loss. Intraoperative parameters of interest were collected by revising electronic health records. The first author of this study calculated the SAS. Data regarding major complications were not revealed to the author until after the calculation of SAS. The SAS results were arranged into four groups (SAS 0-4, SAS 5-6, SAS 7-8 and SAS 9-10). The cohort was then divided into two groups representing low-risk (SAS ≥ 7) and high-risk patients (SAS < 7) using a previously established threshold. The outcome of interest was the occurrence of major complications and death within 30-d of surgery.

RESULTS

A logistic regression model with SAS 9-10 as a reference showed a significant linear association between lower SAS and more postoperative complications [all patients: OR = 2.00 (1.33-3.03), P = 0.001]. This effect was pronounced for TFA [OR = 2.61 (1.52-4.47), P < 0.001]. A significant increase was observed for the high-risk group compared to the low-risk group for all patients [OR = 2.80 (1.40-5.61), P = 0.004] and for the TFA sub-group [OR = 3.82 (1.5-9.42), P = 0.004]. The AUC from the models were estimated as follows: All patients = [0.648 (0.562-0.733), P = 0.001], for TFA patients = [0.710 (0.606-0.813), P < 0.001] and for TTA patients = [0.472 (0.383-0.672), P = 0.528]. This indicates moderate discriminatory power of the SAS in predicting postoperative complications among TFA patients.

CONCLUSION

SAS provides information regarding the potential development of complications following TFA. The SAS is especially useful when patients are divided into high- and low-risk groups.

An assessment of the Surgical Apgar Score in spine surgery

BACKGROUND CONTEXT

The Surgical Apgar Score (SAS), a simple metric based on intraoperative heart rate, blood pressure, and blood loss, was developed in general and vascular surgery to predict 30-day major postoperative complications and mortality. No validation of SAS has been performed in spine surgery.

PURPOSE

To perform a prospective assessment of SAS in spine surgery.

STUDY DESIGN

Prospective study.

PATIENT SAMPLE

Two hundred sixty-eight consecutive patients undergoing major and intermediate spinal surgeries in an 18-month period.

OUTCOME MEASURES

Occurrence of major complications or death within 30 days of surgery.

METHODS

Intraoperative parameters were registered, and SAS was calculated immediately after surgery. Outcome data were collected during a 30-day follow-up. The relationship between SAS and the outcomes was analyzed calculating relative risks (RRs) and likelihood ratios (LRs) for different scoring groups. A univariate logistic regression analysis was also performed. The discriminatory accuracy of SAS was evaluated calculating a C-statistic.

RESULTS

Eighteen patients had ≥1 complications (6.72%). Patients with SAS 9-10 exhibited a 1.64% complication rate (RR=1; LR=0.23), which monotonically augmented as the score decreased: (SAS 7-8=2.75%; RR=1.68; LR=0.39), (SAS 5-6=13.33%; RR=8.13; LR=2.14), (SAS≤4=17.39%; RR=10.61; LR=2.92). The regression analysis odds ratio was 0.66 (95% confidence interval, 0.54-0.82), p<.01. The C-statistic was 0.77 (95% confidence interval, 0.66-0.88).

CONCLUSIONS

Surgical Apgar Score allows risk stratification and has a good discriminatory power in patients undergoing spine surgery.

A nomogram to predict major complications after hip and knee arthroplasty

We aimed to develop a nomogram for risk stratification of major postoperative complications in hip and knee arthroplasty based on preoperative and intraoperative variables, and assessed whether this tool would have better predictive performance compared to the Surgical Apgar Score (SAS). Logistic regression analysis was performed to develop a nomogram. Discrimination and calibration were assessed. Net reclassification improvement (NRI) was used to compare to the SAS. All variables were found to be statistically significant predictors of post-operative complications except race and lowest heart rate. The concordance index was 0.76 with good calibration. Compared to the SAS, the NRI was 71.5% overall. We developed a clinical prediction tool, the Morbidity and Mortality Acute Predictor for arthroplasty (arthro-MAP) that might be useful for postoperative risk stratification.

Use of the surgical Apgar score to guide postoperative care

INTRODUCTION

The surgical Apgar score (SAS) can predict 30-day major complications or death after surgery. Studies have validated the score in different patient populations and suggest it should be used to objectively guide postoperative care. We aimed to see whether using the SAS in a decisive approach in a future randomised controlled trial (RCT) would be likely to demonstrate an effect on postoperative care and clinical outcome.

METHODS

A total of 143 adults undergoing general/vascular surgery in 9 National Health Service hospitals were recruited to a pilot single blinded RCT and the data for 139 of these were analysed. Participants were randomised to a control group with standard postoperative care or to an intervention group with care influenced (but not mandated) by the SAS (decisive approach). The notional primary outcome was 30-day major complications or death.

RESULTS

Incidence of major complications was similar in both groups (control: 20/69 [29%], intervention: 23/70 [33%], p=0.622). Immediate admissions to the critical care unit was higher in the intervention group, especially in the SAS 0-4 subgroup (4/6 vs 2/7) although this was not statistically significant (p=0.310). Validity was also confirmed in area under the curve (AUC) analysis (AUC: 0.77).

CONCLUSIONS

This pilot study found that a future RCT to investigate the effect of using the SAS in a decisive approach may demonstrate a difference in postoperative care. However, significant changes to the design are needed if differences in clinical outcome are to be achieved reliably. These would include a wider array of postoperative interventions implemented using a quality improvement approach in a stepped wedge cluster design with blinded collection of outcome data.

The surgical Apgar score is strongly associated with intensive care unit admission after high-risk intraabdominal surgery

BACKGROUND

Understanding intensive care unit (ICU) triage decisions for high-risk surgical patients may ultimately facilitate resource allocation and improve outcomes. The surgical Apgar score (SAS) is a simple score that uses intraoperative information on hemodynamics and blood loss to predict postoperative morbidity and mortality, with lower scores associated with worse outcomes. We hypothesized that the SAS would be associated with the decision to admit a patient to the ICU postoperatively.

METHODS

We performed a retrospective cohort study of adults undergoing major intraabdominal surgery from 2003 to 2010 at an academic medical center. We calculated the SAS (0-10) for each patient based on intraoperative heart rate, mean arterial blood pressure, and estimated blood loss. Using logistic regression, we assessed the association of the SAS with the decision to admit a patient directly to the ICU after surgery.

RESULTS

The cohort consisted of 8501 patients, with 72.7% having an SAS of 7 to 10 and <5% an SAS of 0 to 4. A total of 8.7% of patients were transferred immediately to the ICU postoperatively. After multivariate adjustment, there was a strong association between the SAS and the decision to admit a patient to the ICU (adjusted odds ratio 14.41 [95% confidence interval {CI}, 6.88-30.19, P < 0.001] for SAS 0-2, 4.42 [95% CI, 3.19-6.13, P < 0.001] for SAS 3-4, and 2.60 [95% CI, 2.08-3.24, P < 0.001] for SAS 5-6 compared with SAS 7-8).

CONCLUSIONS

The SAS is strongly associated with clinical decisions regarding immediate ICU admission after high-risk intraabdominal surgery. These results provide an initial step toward understanding whether intraoperative hemodynamics and blood loss influence ICU triage for postsurgical patients.

Can the Surgical Apgar Score predict morbidity and mortality in general orthopaedic surgery?

PURPOSE

The Surgical Apgar Score (SAS) is a simple tally based on intra-operative heart rate, blood pressure and blood loss; it predicts 30-day major postoperative complications and mortality in different surgical fields, but no validation has been performed in general orthopaedic surgery.

METHODS

A prospective assessment of the SAS in 723 consecutive patients undergoing major and intermediate orthopaedic procedures was performed in an 18-month period. The SAS was calculated immediately after surgery, and the occurrence of major complications or death was registered within a 30-day follow-up.

RESULTS

Thirty-seven patients had ≥1 complication (5.12 %). The complication rate did not augment as the score decreased (SAS 9-10 = 6.56 %; SAS 7-8 = 2.62 %; SAS 5-6 = 7.21 %; SAS ≤4 = 10.2 %), the relative risk did not augment as the score decreased and the likelihood ratio did not increase with decreasing SAS values, except in the subgroup of patients undergoing spine surgery. The C-statistic was 0.59 (95 % confidence interval 0.48-0.69), a weak discriminatory value. Using a threshold of 7 to define high-risk and low-risk patients, the SAS allowed risk stratification only for spine surgery.

CONCLUSIONS

The SAS does not predict 30-day major complications and death in patients undergoing general orthopaedic surgery, but it is useful in the subgroup of patients undergoing spine surgery.