Considerations in Releasing Equations for the American College of Surgeons NSQIP Surgical Risk Calculator

Liu, Yaoming; Cohen, Mark E.; Ko, Clifford Y.; Bilimoria, Karl Y.; Hall, Bruce L.

doi:10.1016/j.jamcollsurg.2016.06.009

Cited by 12 publications

(5 citation statements)

References 1 publication

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“…Updated model performance was published in 2016, with discrimination for mortality consistently high (c‐statistic 0.94) and excellent calibration 45 . The surgical risk calculator uses a proprietary algorithm and there are no plans for the predictive equations to be publicly released to facilitate external validation 46,47 . Discrimination of the surgical risk calculator has been shown to be superior to the Surgical Apgar Score for both mortality and morbidity, however complete risk prediction could only be generated for 57.5% of patients in the mortality model and 60.3% of patients in the morbidity model due to missing data, most commonly laboratory data 48 …”

Section: Resultsmentioning

confidence: 99%

Systematic review of perioperative mortality risk prediction models for adults undergoing inpatient non‐cardiac surgery

Reilly

Gabbe

Brown

et al. 2020

ANZ Journal of Surgery

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Background Risk prediction tools can be used in the perioperative setting to identify high‐risk patients who may benefit from increased surveillance and monitoring in the postoperative period, to aid shared decision‐making, and to benchmark risk‐adjusted hospital performance. We evaluated perioperative risk prediction tools relevant to an Australian context. Methods A systematic review of perioperative mortality risk prediction tools used for adults undergoing inpatient noncardiac surgery, published between 2011 and 2019 (following an earlier systematic review). We searched Medline via OVID using medical subject headings consistent with the three main areas of risk, surgery and mortality/morbidity. A similar search was conducted in Embase. Tools predicting morbidity but not mortality were excluded, as were those predicting a composite outcome that did not report predictive performance for mortality separately. Tools were also excluded if they were specifically designed for use in cardiac or other highly specialized surgery, emergency surgery, paediatrics or elderly patients. Results Literature search identified 2568 studies for screening, of which 19 studies identified 21 risk prediction tools for inclusion. Conclusion Four tools are candidates for adapting in the Australian context, including the Surgical Mortality Probability Model (SMPM), Preoperative Score to Predict Postoperative Mortality (POSPOM), Surgical Outcome Risk Tool (SORT) and NZRISK. SORT has similar predictive performance to POSPOM, using only six variables instead of 17, contains all variables of the SMPM, and the original model developed in the UK has already been successfully adapted in New Zealand as NZRISK. Collecting the SORT and NZRISK variables in a national surgical outcomes study in Australia would present an opportunity to simultaneously investigate three of our four shortlisted models and to develop a locally valid perioperative mortality risk prediction model with high predictive performance.

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Section: Resultsmentioning

confidence: 99%

Systematic review of perioperative mortality risk prediction models for adults undergoing inpatient non‐cardiac surgery

Reilly

Gabbe

Brown

et al. 2020

ANZ Journal of Surgery

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“…The addition of a Surgeon Adjustment Score feature granted surgeons the ability to incorporate their subjective risk for a more personalized score when applicable. There has been ongoing calibration and editing of the calculator with updated CPT codes; however, the internal equations have not been publicized for wide use or automatic integration into the electronic medical record 23,24 . At this time, the tool is for manual use only.…”

Section: Discussionmentioning

confidence: 99%

“…There has been ongoing calibration and editing of the calculator with updated CPT codes; however, the internal equations have not been publicized for wide use or automatic integration into the electronic medical record. 23,24 At this time, the tool is for manual use only. Automatic integration into the and senior attendings.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the American College of Surgeons National Surgical Quality Improvement Program Risk Calculator to predict outcomes after hysterectomies

Hamade

Alshiek

Javadian

et al. 2022

Intl J Gynecology & Obste

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Objective: To evaluate the American College of Surgeons (ACS) surgical risk calculator's reliability in predicting outcomes in hysterectomies.Methods: This is a prospective cohort study at a large community-based hospital.Twenty-one preoperative and postoperative criteria were abstracted from the electronic medical record and entered into the online ACS calculator to determine a risk score. Logistical regression was used to determine the association between risk score and actual outcome. The prediction capability was analyzed with c-statistic, Hosmer-Lemeshow, and Brier score.Results: A total of 634 hysterectomies were performed during the study period from January to April 2019. Patients were predominantly 55 years old, white (53%) and overweight (body mass index 30). Predicted perioperative adverse events were significantly higher than actual adverse events across all domains. In all, 54/634 (8.5%) patients experienced postoperative urinary tract infection. C-statistics for return to operating room, renal failure, and readmission were 0.607 (95% C Statistic index [CI] 0.370-0.845), 0.882 (95% CI 0.802-0.962), 0.637 (95% CI 0.524-0.750), respectively.

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“…The ACS-Calculator’s models remain proprietary and inaccessible for external validation or research. [32,33]…”

Section: Discussionmentioning

confidence: 99%

“…These studies’ limited samples, however, make it difficult to determine whether the ACS-Calculator predictions were poorly-calibrated, or the included patients simply differed from the overall NSQIP risk profile. [27,33]…”

Section: Discussionmentioning

confidence: 99%

Prospective Validation of the Iowa Rectal Surgery Risk Calculator

Sherman

Hrabe

Huang

et al. 2018

Journal of Gastrointestinal Surgery

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Considerations in Releasing Equations for the American College of Surgeons NSQIP Surgical Risk Calculator

Cited by 12 publications

References 1 publication

Systematic review of perioperative mortality risk prediction models for adults undergoing inpatient non‐cardiac surgery

Systematic review of perioperative mortality risk prediction models for adults undergoing inpatient non‐cardiac surgery

Evaluation of the American College of Surgeons National Surgical Quality Improvement Program Risk Calculator to predict outcomes after hysterectomies

Prospective Validation of the Iowa Rectal Surgery Risk Calculator

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