Mortality Prediction in a Vertebral Compression Fracture Population: the ASA Physical Status Score versus the Charlson Comorbidity Index

Discussion

The American Society of Anesthesiologists (ASA) classification is a readily available and widely accepted method for stratification of surgical patients according to their peri-operative risk.¹⁹ ASA scores have been seen in multiple studies to have low inter-observer reliability, but are frequently incorporated in studies to cite reduced variability and predict mortality. ASA scores are typically assigned at the bedside immediately before surgery. These scores have been found to be predictive of mortality for a variety of other conditions.^{7, 19} The ASA is a subjective assessment without a rigid formula used to assign a score; therefore, it is inclusive of all available medical history and easily assigned.

In contrast, the Charlson Comorbidity Index instrument rigidly assigns a score based on the presence of specific comorbidities which possess various weights. To this end, Charlson scores are much less subjective, yet all conditions are not addressed by a Charlson score. CCI scores are a useful way to examine medical records as they may be calculated using recorded ICD-9 codes.

The goal of our analysis was to determine the agreement between these two comorbidity classification systems and to determine if one system predicted morbidity more reliably in surgical versus non-operative subpopulations. Our data may suggest that the ASA is a better instrument for stratifying operative patients while the CCI score is better for non-operative patients. However, this may be an effect of the population size of each group. It is more likely that this study merely illustrates that patients with poor scores in both systems are at a higher mortality risk while those identified at low risk in either system survived longer. Both systems have somewhat more difficulty stratifying patients of intermediate risks. This is where both systems are lacking. In comparisons made for other disease processes, such as cancer, authors have chosen to combine comorbidity classification subgroups when listing morbidity percentiles. Therefore, patients were regarded as either having a high or low degree of morbidity. It is not surprising that in both of our patient populations, when the lowest scoring and highest scoring patients were compared, both systems were highly significant for both surgical and non-operative patients. The relationship between these variables was examined categorically through a Chi Squared test which would imply that the Charlson scores for ASA groups differed statistically between each group. This relationship was also examined through a linear regression model. As the ASA score is not a continuous variable this would not be an ideal model to examine a potential relationship. Specifically, if treating the Charlson score as a continuous variable there are few patients with a score of greater than a four. This is why our assessment was completed in a categorical manner. Table 4 demonstrates that the percentage of patients with a categorically low ASA also had a categorically low Charlson Score.

Certainly a limitation of this study is that a single physician assigned either the ASA or Charlson score in a retrospective manner. Although an assignment of the Charlson score has little bias, multiple studies have determined that the ASA score has low inter-observer reliability. The design through the use of a single anesthesiologist purposefully eliminated this variability for patient ASA assignments. However, the anesthesiologist who assigned these scores may simply assign scores which correlate more readily with mortality. A study with a larger group of anesthesiologists assigning both ASA and Charlson scores would eliminate this inherent bias. Additionally, all patients were assumed to be undergoing surgery when they were assigned ASA and Charlson scores. Since the anesthesiologist was not made aware of what treatment was given, this should not affect or cause bias to the scoring. On the other hand the surgeon would potentially select healthier patients on which to perform surgery. This may have had an effect on the differences seen in the survival curves for each of the study populations; however, our analysis revealed slightly worse Charlson Scores for the patients who had received surgery.

This study has definitively illustrated that there is a great deal of agreement between the Charlson Comorbidity Index score and the ASA score. This reflects that anesthesiologists subjectively consider the same elements of the patient's medical history when assigning ASA scores as the Charlson system objectively uses. This data may prove valuable for future studies as either of these pieces of data may be available in database reviews such as those of large insurance databases. As these resources become more available, tools such as comorbidity stratifying systems will be necessary for data analysis. They will potentially allow physicians and epidemiologists to make improved data comparisons. As our ability to mitigate tremendous public health concerns such as cancer and heart disease improves, we find an ever increasing osteoporotic population. Perhaps, our next frontier of healthcare will be identifying these more chronic and often thought benign diseases such as osteoporosis and attempting to improve upon patient quality of life and potential geriatric patient survival.