Reliability of the American Society of Anesthesiologists Physical Status Scale in Clinical Practice

Sankar, Ashwin; Johnson, S. R.; Beattie, W. Scott; Wijeysundera, Duminda N.

doi:10.1097/01.sa.0000466634.00085.fe

Cited by 123 publications

(180 citation statements)

References 4 publications

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“…While previous studies focused on select comorbidities [14], or used Charlson comorbidity index [15], we included all active comorbidities (physical and mental), which we believe is one of the strengths of the study. There is currently no gold-standard instrument for evaluating comorbidities; and even the most widely used scoring systems (American Society of Anesthesiologists score and Charlson comorbidity index) are not all-inclusive or have moderate inter-rater reliability [19,20]. For example, while the Charlson comorbidity index, initially designed as a predictor for mortality [21], is an excellent prognostic tool in life-threatening conditions [22], it may not be sensitive enough for low-mortality elective procedures [23] and it does not account for conditions that may impact the postoperative course, such as depression and anxiety.…”

Section: Discussionmentioning

confidence: 99%

Preoperative Predictors of Extended Hospital Length of Stay Following Total Knee Arthroplasty

Halawi

Vovos

Green

et al. 2015

The Journal of Arthroplasty

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a b s t r a c t a r t i c l e i n f oThe purpose of this study was to identify the preoperative predictors of hospital length of stay after primary total knee arthroplasty in a patient population reflecting current trends toward shorter hospitalization and using readily obtainable factors that do not require scoring systems. A single-center, multi-surgeon retrospective chart review of two hundred and sixty consecutive patients who underwent primary total knee arthroplasty was performed. The mean length of stay was 3.0 days. Among the different variables studied, increasing comorbidities, lack of adequate assistance at home, and bilateral surgery were the only multivariable significant predictors of longer length of stay. The study was adequately powered for statistical analyses and the concordance index of the multivariable logistic regression model was 0.815.

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Section: Discussionmentioning

confidence: 99%

Preoperative Predictors of Extended Hospital Length of Stay Following Total Knee Arthroplasty

Halawi

Vovos

Green

et al. 2015

The Journal of Arthroplasty

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“…These models are able to predict a range of postoperative events, such as death, cardiac complications, pneumonia, and acute kidney injury, with good accuracy [8]. While clearly the best tool, nevertheless, the ACS NSQIP risk calculator has two notable limitations: first, the prediction models were derived from a very large multicenter observational dataset that is yet to undergo external validation, especially in settings outside the United States; and, second, it incorporates the American Society of Anesthesiologists Physical Status (ASA-PS) classification system, which has limited interrater reliability [9].…”

Section: Discussionmentioning

confidence: 99%

The criteria of “inoperability”

Romagnoli

Paparella

Boninsegni

2017

Monaldi Arch Chest Dis

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In the literature, the term "inoperable" mainly refers to two specific clinical aspects: cancer staging and technical difficulty/impossibility in performing. In light of this clarification, the statement "the patient cannot be anesthetized" has no medical foundation. On the contrary, the physicians have to carefully stratify the perioperative risk and optimize the patients' preoperative clinical status. In order to perform a precise risk stratification, the European Society of Cardiology and the European Society of Anaesthesiology have joined and published the guidelines for the perioperative cardiovascular management of patients scheduled to undergo non-cardiac surgery. The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) represents the most complete and accurate prediction tool so far. It includes 21 preoperative factors relating to demographics, comorbidities and procedures able to predict outcomes based on preoperative risk factors such as death, cardiac complications, pneumonia, and acute kidney injury. The present article will address aspects related to common aspects concerning modifiable and non-modifiable that should be addressed in every patient to whom elective surgery has been scheduled.

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“…[14][15][16][17][18][19] Conversely, more recent research has shown the scale to have at least moderate inter-rater reliability in usual clinical practice, with more than 98% of paired ASA-PS ratings of individual patients being within one class of each other. 20 Additionally, despite these potential limitations, the ASA-PS scale has shown at least moderate accuracy in predicting postoperative mortality across a wide range of studies. 21 Estimating perioperative risk using risk scores An alternative to a subjective evaluation of overall risk is the formal integration of several different sources of risk information into a single score, such that patients are allocated points based on the presence of prognostically important risk criteria (e.g., increased age, concomitant coronary artery disease, preoperative anemia).…”

Section: Résumémentioning

confidence: 99%

“…The graph was plotted using the R Statistical Language Version 3.2.1 (Vienna, Austria) reliability. [14][15][16][17][18][19][20] Thus, whenever possible, a risk score and its individual components should have good inter-rater reliability.…”

Section: Other Characteristics Needed In a Good Risk Scorementioning

confidence: 99%

Predicting outcomes: Is there utility in risk scores?

Wijeysundera

2015

Can J Anesth/J Can Anesth

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Purpose This review discusses the utility of risk scores, specifically, the role of preoperative risk scores in guiding the management of surgical patients, approaches to evaluate the quality of risk scores, and limitations to consider when applying risk scores in clinical practice. Principal findings This review shows how accurate predictions of perioperative risk can help inform patients and clinicians with respect to decision-making around surgery; identify patients who warrant further specialized investigations, new interventions intended to decrease risk, modifications in planned operative procedures, or intensification of postoperative monitoring; and facilitate fairer comparisons of outcomes between providers and hospitals. A preoperative risk score formally integrates several pieces of clinical information (e.g., age, comorbid disease, laboratory tests) to arrive at an overall estimate of an individual patient's expected risk for specific postoperative adverse events. A good risk score should be simple to incorporate in clinical practice, reliable when applied by different raters, and accurate at predicting postoperative risk. Several analytical methods (e.g., receiver operating characteristic curves, likelihood ratios, risk reclassification tables, observed vs predicted plots) are required to characterize the relevant domains that encompass the prognostic accuracy of a risk score. External validation is critical in determining whether the predictive accuracy of a risk score is preserved when applied to new settings, populations, or outcome events. Conclusions Preoperative risk scores help inform perioperative clinical decision-making. Future research must determine how estimates of preoperative risk can be updated with information from the intraoperative period, how risk information should be communicated to patients, and which interventions can improve outcomes among patients within newly identified risk strata. RésuméObjectif Ce compte rendu s'intéresse à l'utilité des cotes de risque, et plus spécifiquement au rô le des cotes de risque préopératoires dans l'orientation de la prise en charge des patients chirurgicaux, aux approches permettant d'évaluer la qualité des cotes de risque, ainsi qu'aux limites à garder à l'esprit lorsqu'on applique de telles cotes de risque à la pratique clinique. Constatations principales Ce compte rendu démontre comment des prédictions précises du risque périopératoire peuvent aider à guider les patients et les cliniciens dans leurs prises de décision concernant la chirurgie, à identifier les patients qui bénéficieraient d'examens plus spécialisés, de nouvelles interventions visant à réduire leur risque, de modifications dans les interventions opératoires planifiées, ou d'une intensification du monitorage

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Reliability of the American Society of Anesthesiologists Physical Status Scale in Clinical Practice

Cited by 123 publications

References 4 publications

Preoperative Predictors of Extended Hospital Length of Stay Following Total Knee Arthroplasty

Preoperative Predictors of Extended Hospital Length of Stay Following Total Knee Arthroplasty

The criteria of “inoperability”

Predicting outcomes: Is there utility in risk scores?

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