Abstract
Advances in burn care continues to improve survival rates and patient outcomes. There are several burn prognostic tools used to predict mortality and outcomes; however, none include patient comorbidities. We used the American Society of Anesthesiologists physical status score as a surrogate measure for comorbidities, and evaluated its role in predicting mortality and outcomes in adult burn patients undergoing surgery. A retrospective analysis was performed on data collected from a single burn center in the United States, which was comprised of 183 patients. We evaluated the American Society of Anesthesiologists physical status score as an independent predictor of mortality and outcomes, including intensive care unit (ICU) length of stay (LOS), hospital LOS, mechanical ventilator (MV) days, and complications. We compared the American Society of Anesthesiologists physical status score to other prognostic models which included the revised Baux score, Belgian Outcome in Burn Injury, and the Abbreviated Burn Severity Index. Our results demonstrated that the revised Baux and American Society of Anesthesiologists physical status scores could be used to determine the mortality risk in adult burn patients. The revised Baux was the best predictor of mortality, ICU LOS, and MV days, while the Abbreviated Burn Severity Index was the best predictor of total LOS.
Per the American Burn Association (ABA) National Burn Repository (NBR) 2017 annual report, which collected data from 101 hospitals in 37 states, there were 212,820 burn-related hospital admissions.1 More than 67% of patients had a total body surface area (TBSA) % burn less than 10%, which had an associated mortality rate of 0.6%.1 Mortality rate increased with increased percentage of TBSA. The two most common causes of burns were flame and scalds, and the overall mortality rate was 3.1% with 5.6% for flame and scald injuries. Major predictors of case fatality in burns include burn size, age, and the presence of inhalation injury. Furthermore, the complication rate was increased in patients requiring mechanical ventilation, and increased with the duration of ventilation.1 Although the overall mortality rate for burn-associated injuries is low, those who require intensive care unit (ICU) admission are at increased risk of death, which prompted the development of several mortality prognostic models.2
The three main prognostic models which have been externally validated include the revised Baux (rBaux) score, the Belgian Outcome in Burn Injury (BOBI), and the Abbreviated Burn Severity Index (ABSI).3–5 Major predictors of burn mortality include age, %TBSA, and the presence of inhalation injury; 1 the rBaux score and BOBI incorporate these variables into their score algorithms. The ABSI also uses these variables, but also includes sex and the presence of full thickness burn.2 Shortcomings of these models are that they do not factor in patient medical comorbidities, and mortality appears to be underestimated in patients requiring ICU care.2
The American Society of Anesthesiologists physical status (ASA PS) score (Table 1) is a simple and easy to use tool that quickly classifies patients’ overall health status and comorbidities, using a numeric scale (I–VI).7–11 The ASA PS has been demonstrated to predict morbidity and mortality in surgical patients,8,9 resulting in its incorporation into risk-adjustment models for nontrauma surgical outcomes.8 Additionally, preinjury ASA PS scores have been integrated into trauma patient prediction models.10–12 As adding measures of comorbidities to other surgical outcome prediction models improved outcome predictive ability, incorporating ASA PS as a surrogate measure of medical comorbidities into current burn prediction models may improve their predictive ability.
Table 1.
ASA PS (American Society of Anesthesiologist Physical Status) classifications and examples6
| ASA PS Classification | Definition | Examples |
|---|---|---|
| ASA I | A normal healthy patient | Healthy, nonsmoking, no or minimal alcohol use |
| ASA II | A patient with mild systemic disease | Mild diseases only without substantive functional limitations. Examples include (but not limited to): current smoker, social alcohol drinker, pregnancy, obesity (30 < BMI < 40), well-controlled DM/HTN, mild lung disease |
| ASA III | A patient with severe systemic disease | Substantive functional limitations; one or more moderate to severe diseases. Examples include (but not limited to): poorly controlled DM of HTN, COPD, morbid obesity (BMI ≥ 40), acute hepatitis, alcohol dependence or abuse, implanted pacemaker, moderate reduction of ejection fraction, ESRD undergoing regularly scheduled dialysis, premature infant PCA <60 wk, history (>3 mo) of MI, CVA, TIA, or CAD/stents |
| ASA IV | A patient with severe systemic disease that is a constant threat to life | Examples include (but not limited to): recent (<3 mo) MI, CVA, TIA, or CAD/stents; ongoing cardiac ischemia or severe valve dysfunction; severe reduction of ejection fraction; sepsis; DIC; ARD; or ESRD not undergoing regularly scheduled dialysis |
| ASA V | A moribund patient who is not expected to survive without the operation | Examples include (but not limited to): ruptured abdominal/ thoracic aneurysm, massive trauma, intracranial bleed with mass effect, ischemic bowel in the face of significant cardiac pathology or multiple organ/system dysfunction |
| ASA VI | A declared brain-dead patient whose organs are being removed for donor purposes |
ARD, acid reflux disease; ASA, American Society of Anesthesiologists; BMI, body mass index; CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease; CVA, cerebral vascular accident; DIC, disseminated intravascular coagulation; DM, diabetes mellitus; ESRD, end-stage renal disease; HTN, hypertension; MI, myocardial infarction; PCA, postconceptual age; PS, physical status; TIA, transient ischemic attack.
To the best our knowledge, this is the first study to examine the mortality and outcome predictive ability of the ASA PS score in burn patients. Additionally, we evaluated the role of quick Systemic Organ Failure Assessment (qSOFA) in predicting outcomes in our burn population, as it has been associated with predicting in-hospital mortality in ICU and severe burn injury patients.2,12 Our aim was to evaluate the role of ASA PS as an independent predictor of in-hospital mortality in adult burn patients undergoing surgery. We evaluated the role of ASA PS, qSOFA, rBaux, BOBI, and ASBI in predicting in-hospital mortality and ICU and total hospital length of stay (LOS), mechanical ventilator (MV) days, and complications. We hypothesize that ASA is an independent predictor of in-hospital mortality, ICU LOS, total LOS, MV days, and complications. Our secondary objective was to determine whether a combination of ASA PS and rBaux, BOBI, and or ASBI would result in superior mortality predictive ability compared to any of these models alone.
METHODS
Ethics
Our protocol was approved by our instructional review board. This study adhered to the guidelines in the statement of Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).
Patient Population and Data Collection
All adults admitted to our ABA verified burn center from January 1, 2016 to April 1, 2019 with TBSA ≥10% who underwent surgery were included for analysis. Demographics (age, sex, TBSA, race, ASA PS), vital signs (Glasgow coma scale [GCS], blood pressure, respiratory rate), and outcome variables (hospital and ICU LOS, MV days, and complications) were evaluated. The primary outcome was in-hospital mortality. Secondary outcomes included: hospital and ICU LOS, MV days, and complications.
Burn Prognostic Scores
The rBaux, BOBI, ABSI, and qSOFA scores were calculated. The ASA PS score was obtained from the anesthesiology intraoperative record from the first surgery the patient underwent during their hospitalization. We excluded patients assigned an ASA PS of VI, as this is the assignment for a patient who is brain-dead undergoing organ procurement surgery.
Statistical Analysis
Categorical variables were reported as frequencies and percentages; continuous variables were reported as median (interquartile range [IQR]). Differences in patient characteristics and risk factors by mortality were tested by Fisher’s exact test or Wilcoxon rank-sum test, as appropriate.
Due to the overdispersion and a minimum hospital LOS of 10 days, a truncated negative binomial regression model was used to estimate the association between LOS with each burn score. A negative binomial regression model was used to estimate the association between ICU LOS and days on MV. Results were reported as incidence rate ratios (IRRs) and their 95% confidence intervals. ASA PS scores I/II and IV/V and BOBI scores greater than or equal to 4 were combined due to sparse data. The rBaux scores were categorized into quartiles. ABSI scores were collapsed into clinical meaningful categories: low-moderate (1–5), moderately severe-serious (6–9), and severe-maximum (≥10).
Firth’s penalized logistic regression analysis was performed to test the association and predictive ability of each burn score on in-hospital mortality. The discriminative power of each burn score was assessed with area under curve (AUC) of the receiver operating curves (ROC) independently. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using a cutoff value of 0.5. Every possible combination of two or three scores including rBaux were compared nonparametrically to a model with rBaux alone with respect to the areas under their ROC curves in order to determine the significance of the incremental and combined contributions of each score to rBaux alone.
All statistical tests were two-sided with an alpha level set at 0.05 for statistical significance. All statistical analyses were performed using SAS 9.4.
RESULTS
A total of 183 patients met inclusion criteria, and were included in the analytical sample (Table 2). The median (IQR) age was 44 (30–57) years, and 30% of the patients were female. Seventeen of the 183 (9.3%) patients died in the hospital. The median %TBSA burned was 20 for both survivors and nonsurvivors. All patients who died in the hospital with available data experienced at least one complication up to a maximum of 5, which included nine cardiac arrests, one surgical site infection, two urinary tract infections, eight pneumonias, five acute respiratory distress syndromes, one percutaneous endoscopic gastrostomy tube placement, five tracheostomies, nine continuous renal replacement therapies, and ten septic shock incidents. All burn scoring systems were statistically significantly associated with mortality. Of the 17 patients who died, 2 (11.8%) had an ASA PS score of II, 5 (29.4%) had a score of III, and 8 (47.1%) had a score of IV. For the 166 survivors, 65 (39.6%) had an ASA PS score of II, 58 (35.4%) a score of III, and 27 (16.5%) a score of IV (P < .005). Compared to patients who survived, deceased patients had a higher median (IQR) of rBaux score (98 [86–100] vs 66.5 [53–84]; P < .001), ABSI score (8 [7–9] vs 6 [5–7]; P = .001), and BOBI score (3 [2–4] vs 1 [0–2]; P < .001). The median (IQR) qSOFA scores for both survivors and nonsurvivors was 1 although the majority of scores were between 0 and 1 for survivors and 1 and 2 for nonsurvivors (P = .005).
Table 2.
Patient cohort characteristics, risk factors, and mortality predictive capacity of multiple burn prognostic scores
| Mortality | ||||
|---|---|---|---|---|
| Characteristic | Total Sample (n = 183) | Yes (n = 17) | No (n = 166) | P* |
| Age, yr | 44 (30–57) | 58 (51–79) | 40.5 (29–54) | <.001 |
| Female sex | 55 (30.1%) | 7 (41.2%) | 48 (28.9%) | .40 |
| Race | ||||
| White | 39 (21.3%) | 6 (35.3%) | 33 (19.9%) | .52 |
| Hispanic | 77 (42.1%) | 6 (35.3%) | 71 (42.8%) | |
| African American | 28 (15.3%) | 1 (5.9%) | 27 (16.3%) | |
| Asian | 14 (7.7%) | 2 (11.8%) | 12 (7.2%) | |
| Native American | 1 (0.6%) | 0 | 1 (0.6%) | |
| Other/unknown | 24 (13.1%) | 2 (11.8%) | 22 (13.3%) | |
| % TBSA burned | 20 (13.5–30) | 20 (17–41) | 20 (13–30) | .20 |
| Inhalation injury | 25 (13.7%) | 4 (23.5%) | 21 (12.7%) | .26 |
| Presence of full thickness burn | 118 (64.5%) | 14 (82.4%) | 104 (62.7%) | .12 |
| ASA PS score from first surgery† | ||||
| I | 14 (7.7%) | 1 (5.9%) | 13 (7.9%) | .005 |
| II | 67 (37.0%) | 2 (11.8%) | 65 (39.6%) | |
| III | 63 (34.8%) | 5 (29.4%) | 58 (35.4%) | |
| IV | 35 (19.3%) | 8 (47.1%) | 27 (16.5%) | |
| V | 1 (0.6%) | 1 (5.9%) | 0 | |
| VI | 1 (0.6%) | 0 | 1 (0.6%) | |
| ASA PS score from first surgery† | ||||
| I/II | 81 (44.8%) | 3 (17.7%) | 78 (47.6%) | .003 |
| III | 63 (34.8%) | 5 (29.4%) | 58 (35.4%) | |
| IV/V/VI | 37 (20.4%) | 9 (52.9%) | 28 (17.1%) | |
| Revised Baux score | 71 (54–87) | 98 (86–100) | 66.5 (53–84) | <.001 |
| Revised Baux score category | ||||
| 30–53 | 44 (24.0%) | 0 | 44 (26.5%) | <.001 |
| 54–70 | 47 (25.7%) | 0 | 47 (28.3%) | |
| 71–86 | 46 (25.1%) | 5 (29.4%) | 41 (24.7%) | |
| 87–148 | 46 (25.1%) | 12 (70.6%) | 34 (20.5%) | |
| ABSI score | 6 (5–8) | 8 (7–9) | 6 (5–7) | .001 |
| ABSI score category | ||||
| Low-moderate (1–5) | 62 (33.9%) | 1 (5.9%) | 61 (36.8%) | .003 |
| Moderately severe-serious (6–9) | 106 (57.9%) | 12 (70.6%) | 94 (56.6%) | |
| 15 (8.2%) | 4 (23.5%) | 11 (6.6%) | ||
| BOBI score | 1 (0–3) | 3 (2–4) | 1 (0–2) | <.001 |
| qSOFA score† | ||||
| 0 | 69 (38.1%) | 2 (11.8%) | 67 (40.9%) | .02 |
| 1 | 75 (41.4%) | 8 (47.1%) | 67 (40.9%) | |
| 2 | 26 (14.4%) | 4 (23.5%) | 22 (13.4%) | |
| 3 | 11 (6.1%) | 3 (17.7%) | 8 (4.9%) | |
| Glasgow coma scale‡ | 15 (14–15) | 11 (7.5–14.5) | 15 (15-15) | <.001 |
| Respiratory rate | 20 (18–26) | 24 (18–32) | 20 (18–26) | .23 |
| Systolic blood pressure | 144 (115–167) | 148 (84–177) | 144 (116–166) | .98 |
| Complication§ | 79 (43.4%) | 16 (100%) | 63 (38.0%) | <.001 |
ABSI, Abbreviated Burn Severity Index; ASA, American Society of Anesthesiologists; BOBI, Belgian Outcome in Burn Injury; IQR, interquartile range; PS, physical status; qSOFA, quick Systemic Organ Failure Assessment. Results are reported as N (%) or median (IQR).
aBy Fisher’s exact test or Wilcoxon rank-sum test, as appropriate.
†Two missing.
‡Four missing.
§One missing.
Higher scores in ASA PS, rBaux, ABSI, and BOBI were significantly associated with longer hospital LOS by truncated negative binomial regression. Based on the model pseudo-R2, ABSI best explained the variability in hospital LOS (Table 3). Compared with patients with a score of 1 to 5, patients with ABSI scores of 6 to 9 were expected to have a rate 2.22 (95% CI: 1.66–2.98) times greater, and patients with a score of at least 10 were expected to have a rate 4.95 (95% CI: 3.00–8.17) times greater for hospital LOS (both P < .001). The mean predicted LOS increased from 12.8 days (95% CI: 8.7–16.9), to 28.4 (95% CI: 22.2–34.6), to 63.2 (95% CI: 36.1–90.2) for patients with scores of 1 to 5, 6 to 9, and 10+, respectively.
Table 3.
Model pseudo-R2 was used to determine the predictive capacity of each prognostic model for variables such as hospital LOS, ICU LOS, and MV days
| Scoring System | Hospital LOS | ICU LOS | MV Days |
|---|---|---|---|
| ASA PS | 0.0304 | 0.0423 | 0.0398 |
| rBaux | 0.0311 | 0.0612 | 0.0662 |
| ABSI | 0.0384 | 0.0410 | 0.0335 |
| BOBI | 0.0255 | 0.0720 | 0.0576 |
| qSOFA | 0.0086 | 0.0087 | 0.0106 |
ABSI, Abbreviated Burn Severity Index; ASA, American Society of Anesthesiologists; BOBI, Belgian Outcome in Burn Injury; ICU, intensive care unit; LOS, length of stay; MV, mechanical ventilator; PS, physical status; qSOFA, quick Systemic Organ Failure Assessment; rBaux, revised Baux.
Based on the model pseudo-R2, BOBI best explained the variability in ICU LOS. Compared to patients with a BOBI score of 0, patients with a BOBI score of 1 were expected to have a rate 10.82 (95% CI: 6.32–18.63) times greater for ICU LOS (P < 0.001), while patients with a score of 4 or greater were expected to have a rate over 26 times that of those with a score of 0 (IRR, 95% CI: 26.36, 13.95–49.80; P < .001). The mean predicted ICU LOS increased from 1.2 up to 31.5 days for the lowest and highest BOBI score categories, respectively.
The number of days on MV was best explained by the rBaux score, based on the model pseudo-R2. Compared to rBaux scores of 30 to 53, patients with score of 54 to 70, 71 to 86, and 87 to 148 were expected to have a rate 5.90 (95% CI: 2.51–13.87), 20.29 (95% CI: 8.70–47.33), and 49.74 (95% CI: 21.39–115.67) times greater for days on MV, respectively (all P < .001). The mean predicted days on MV increased from less than 1 day (95% CI: 0.2–0.9), 3.1 (95% CI: 1.4–4.7) days, 10.6 (95% CI: 5.1–16.2) days, up to 26.0 (95% CI: 12.5–39.5) days for each rBaux score quartile.
The strength of the association and predictive ability of ASA PS, revised Baux, ABSI, BOBI, and qSOFA were each independently tested by Firth’s logistic regression. The odds of mortality were 2.28 (95% CI: 1.33–4.14) times greater for every 1-unit increase in ASA PS (P = .003) (Table 4). The odds of mortality increased significantly by 5% (95% CI: 3%–8%), 46% (95% CI: 16%–87%), 71% (95% CI: 35%–123%), and 110% (95% CI: 25%–258%) for every 1-unit increase in rBaux, ABSI, BOBI, and qSOFA score, respectively.
Table 4.
Comparison of burn prognostic scores in predicting mortality
| Score | OR (95% CI) | P | Sensitivity (%) | Specificity (%) | PPV (%) | NPV (%) | AUC (95% CI) |
|---|---|---|---|---|---|---|---|
| ASA PS | 2.28 (1.33–4.14) | .003 | 0 | 99.4 | 0 | 90.6 | 0.71 (0.58–0.85) |
| rBaux | 1.05 (1.03–1.08) | <.001 | 11.8 | 99.4 | 66.7 | 91.7 | 0.84 (0.76–0.91) |
| ABSI | 1.46 (1.16–1.87) | .001 | 0 | 100 | 0 | 90.7 | 0.74 (0.61–0.87) |
| BOBI | 1.71 (1.35–2.23) | <.001 | 11.8 | 98.8 | 50.0 | 91.6 | 0.84 (0.77–0.91) |
| qSOFA* | 2.10 (1.25–3.58) | .005 | 0 | 100 | 0 | 90.6 | 0.69 (0.57–0.81) |
ABSI, Abbreviated Burn Severity Index; ASA, American Society of Anesthesiologists; AUC, area under curve; BOBI, Belgian Outcome in Burn Injury; NPV, negative predictive value; PPV, positive predictive value; PS, physical status; qSOFA, quick Systemic Organ Failure Assessment; rBaux, revised Baux.
Odds ratios (ORs) represent the increase in the odds of mortality vs survival for every 1 unit increase in score.
*No patients in study cohort reported a score of 4.
An ROC curve for each logistic regression model was plotted, and the AUC was calculated to provide a measure of the discriminative ability of each burn score (Figure 1). Based on the AUC, the best predictors of inpatient mortality were the rBaux score and BOBI score (both 0.84). Notably, the rBaux and BOBI scores are also highly significantly correlated (Pearson r = 0.84; P < .001). No combination of two or three scores were significantly superior in predicting mortality compared with rBaux alone.
Figure 1.
Comparing the discriminatory ability in predicting mortality with rBaux independently or with a combination of rBaux and another prognostic score.
DISCUSSION
To the best our knowledge, this is the first pilot study to examine the outcome predictive ability of ASA PS as a measure of comorbidities in adult burn patients at a single ABA verified burn center. Our results demonstrate that all prognostic scores were independently associated with predicting in-hospital mortality in burn patients undergoing surgical management. Every score except the qSOFA score was significantly able to predict hospital LOS.
The best predictors of inpatient mortality were the rBaux and BOBI scores, which are traditionally used in burn care, and do not take medical comorbidities into account. While the Baux score is commonly used, there is a lack of high quality data that demonstrates one burn prognostic score is superior over the other.2,13–20 Our analysis demonstrated that the two scores were closely significantly correlated with each other, which could be explained by the fact that both scores use patient age, %TBSA, and inhalation injury to predict mortality. The ASA PS, which is a prognostic model that is mainly based on comorbidities, was also predictive of inpatient mortality, MV days, and LOS.
When multiple scores were combined, the addition of ASA PS, ABSI, BOBI, or qSOFA each independently to a model with rBaux alone was not significantly better at discriminating mortality than rBaux alone. Our findings indicate that while prognostic models that incorporate comorbidities are capable of reliably predicting mortality, they do not appear to be superior to traditional burn prognostic models. We believe this is because %TBSA and inhalation injury have a more profound effect on mortality than some common comorbidities assessed with the ASA PS, such as diabetes, hypertension, and chronic obstructive pulmonary disease. However, congestive heart failure and chronic kidney disease are comorbidities that should raise concern, as these patients would have a very low tolerance to large-volume resuscitations required with higher %TBSA injuries.
While comorbidities are considered in trauma and general surgery outcome prognostic models, they are not factored into the prognostic models routinely used in the burn population.14 To the best our knowledge, only the study conducted by Heng et al2 assessed the role of comorbidities in predicting mortality in burn patients. They retrospectively analyzed 90 mechanically ventilated adult patients admitted to the ICU over a 10-year period, who had %TBSA ≥15%. They used the Charlson comorbidity index (CCI) as a surrogate measure of medical comorbidities.21 Furthermore, they computed the rBaux score, BOBI, ABSI, SOFA score, and CCI, and analyzed if these scores were related to in-hospital mortality. They concluded that the rBaux score and CCI were independently associated with mortality in ICU burn patients, suggesting that comorbidities may need to be factored into mortality prognostication models.2 Similarly, our study demonstrated that the ASA PS score could be used to predict mortality in burn patients. However, our study did not demonstrate that ASA PS combined with other prognostic models (rBaux, BOBI, and ABSI) was superior than the rBaux in predicting outcomes in our burn population.
The rBaux score should continue to be used to quickly prognosticate burn outcomes, especially in the acute setting. Having a score with a higher positive predictive value would be a beneficial tool for providers to use when making goals of care decisions after burn injury. Since our study reported that ASA PS is independently associated with mortality in burn patients, there seems to be an association between preexisting medical conditions and burn outcomes that have yet to be elucidated. As our study was a single-center retrospective study with a small patient population, performing a larger multicenter prospective study may reveal that ASA PS, or other comorbidity measuring tools, may improve the outcome predictive ability of currently accepted prediction models in the burn patient population.
CONCLUSIONS
The rBaux and ASA PS scores can be used to determine risk of mortality in burn patients. The rBaux is the best predictor of mortality, ICU LOS, and MV days. The ABSI is the best predictor of hospital LOS. Future studies should be performed to determine the outcome predictive ability of ASA PS and its incorporation in other burn predictive models.
LIMITATIONS
Our study is subject to several limitations, including those associated with a retrospective study, such as selection bias and coding errors. Data outcome variables such as complications may have been underestimated or overlooked. We are limited by having a small patient sample size and being a single-center study. As our study population only had 17 in-hospital deaths, a larger sample size could elucidate associations between medical comorbidities and burn outcomes that was not detected in our study. We chose patients undergoing surgery, and our results cannot be generalized to the burn population who have not undergone surgical procedures. Additionally, the ASA PS was subjectively assigned by different anesthesiologists, and there may be variability in the ASA PS assignment by providers. Furthermore, we do not know if the anesthesiologists assigning ASA PS were using preinjury or postinjury scores. Our study is subject to confounding bias as other potential variables affecting outcomes were not included in our analysis. We only evaluated in-hospital mortality and not 30-day or early (within 72 hours of admission) mortality; it is possible if we looked at these outcomes our results would be different. Finally, we did not look at additional burn outcome predictive models other than the ones included in our analysis.
Funding Statistical analysis for this work was supported by grants UL1TR001855 and UL1TR000130 from the National Center for Advancing Translational Science (NCATS) of the U.S. National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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