A Novel Score to Estimate the Risk of Pneumonia After Cardiac Surgery Arman Kilic, MD1, Rika Ohkuma, MD 1, J. Trent Magruder, MD1, Joshua C. Grimm, MD1, Marc Sussman, MD1, Eric B. Schneider, PhD1, Glenn J.R. Whitman, MD1 1Division of Cardiac Surgery, Johns Hopkins Hospital, Baltimore, MD None of the authors have any relevant financial relationships to disclose.

Background Pneumonia is the most common nosocomial infection after cardiac surgery Postoperative pneumonia is associated with increased risk of mortality and readmission, as well as prolonged ICU and hospital stay and increased costs of care A composite risk index for estimating pneumonia risk after cardiac surgery would have clinical utility

Study Aim To derive and validate a risk score for postoperative pneumonia after cardiac surgery

Study Design Data Source Single institution series Study Population Adult patients (18 or older) Study period: January 1, 2005 to December 31, 2012 Excluded: ECMO or heart transplant patients

Data Analysis Primary Outcome Postoperative pneumonia – STS definition – “positive sputum cultures, transtracheal fluid, bronchial washings, and/or clinical findings consistent with pneumonia” Study Population Randomly divided 3:1 into training and validation sets

Data Analysis Generation of Risk Score in the Training Set Univariable logistic regression analysis to evaluate association between multiple preoperative and intraoperative variables and postoperative pneumonia Variables associated with pneumonia in univariable analysis (p<0.20) and <10% missing data entered into a multivariable model Points were assigned to significant risk factors based on the relative magnitudes of the odds ratios .

Data Analysis Validation of Risk Score in the Validation Set Predictive accuracy of the risk score evaluated using logistic regression, area under receiver operating characteristic curve (c-index) C-indices also compared between risk score and STS prolonged ventilation model in predicting pneumonia .

Baseline Patient Characteristics Variable Training Set (n=4,666) Validation Set (n=1,556) p-value Age (years) 61.2 ± 14.9 61.4 ± 14.7 0.69 Male 3,067 (66%) 1,020 (66%) 0.90 Body Mass Index (kg/m2) 28.8 ± 7.6 29.0 ± 9.4 0.38 Chronic Lung Disease None Mild Moderate Severe 4,053 (87%) 338 (7%) 184 (4%) 90 (2%) 1,346 (87%) 131 (8%) 54 (3%) 25 (2%) 0.32 Diabetes Mellitus 1,257 (27%) 404 (26%) 0.45 Hypertension 3,411 (73%) 1,112 (71%) 0.21 Dialysis Dependence 135 (4%) 38 (4%) 0.34 Serum Creatinine (mg/dL) 1.20 ± 1.10 1.18 ± 1.12 0.56 Cerebrovascular Disease 467 (10%) 177 (11%) 0.13 Peripheral Vascular Disease 473 (10%) 160 (10%) 0.87 Prior Cardiac Intervention 1,437 (31%) 486 (31%) 0.75 Cardiogenic Shock 124 (3%) 37 (2%) 0.55 Myocardial Infarction 1,294 (28%) 413 (27%) 0.36

Baseline Operative Characteristics Variable Training Set (n=4,666) Validation Set (n=1,556) p-value Elective Case 2,886 (62%) 976 (63%) 0.54 Type of Operation Valve CABG Combined Valve and CABG Other 1,613 (35%) 1,776 (38%) 487 (10%) 790 (17%) 534 (34%) 595 (38%) 172 (11%) 255 (16%) 0.88 Cardiopulmonary Bypass Time (minutes) 122.1 ± 53.3 122.1 ± 55.7 0.98 Aortic Cross Clamp Time (minutes) 78.6 ± 34.5 77.9 ± 34.6 0.52 Intra-Aortic Balloon Pump 427 (9%) 127 (8%) 0.24 Timing of Intra-Aortic Balloon Pump Preoperative Intraoperative Postoperative 262 (61%) 140 (33%) 25 (6%) 79 (62%) 39 (31%) 9 (7%) 0.83

Results Postoperative pneumonia rate of 4.5% (n=282) In-hospital mortality rate 15.3% (pneumonia) versus 4.8% (no pneumonia) p<0.001 30-day mortality rate 8.0% (pneumonia) versus 4.6% (no pneumonia) p=0.01 .

Multivariable Model for Pneumonia Covariate Odds Ratio (95% Confidence Interval) P-value Points Assigned Age ≥ 65 Years 1.40 (1.01-1.94) 0.04 3 Chronic Lung Disease None Mild Moderate Severe Reference 1.97 (1.22-3.16) 3.07 (1.80-5.23) 3.31 (1.56-7.03) 0.005 <0.001 0.002 4 6 7 Peripheral Vascular Disease 1.69 (1.11-2.56) 0.01 Cardiopulmonary Bypass Time >100 Minutes 1.71 (1.13-2.61) Intraoperative Red Blood Cell Transfusion 1.08 (1.03-1.13) 2 Pre- or Intraoperative Intra-Aortic Balloon Pump 2.01 (1.30-3.11) TOTAL POINTS POSSIBLE - 22 *other variables included in the multivariable model but not significant predictors: hypertension, prior cardiac intervention, myocardial infarction in last 24 hours, cardiogenic shock, increasing serum creatinine, emergent operation, type of operation, increasing aortic cross clamp time, and tricuspid valve procedure

Probability of Pneumonia Based on the Training Set

Probability of Pneumonia Based on the Training Set Predicted Rate 95% CI for Predicted Rate

Probability of Pneumonia Based on the Training Set Predicted Rate 95% CI for Predicted Rate Score=0 Rate=1.2%

Probability of Pneumonia Based on the Training Set Score=22 Rate=55% Predicted Rate 95% CI for Predicted Rate Score=0 Rate=1.2%

Predicted Rates of Pneumonia in the Training Set by Score Categories

Actual Rates of Pneumonia in the Validation Set by Score Categories

Correlation Between Predicted and Actual Rates of Pneumonia Correlation between predicted rates in training set and actual rates in validation set r=0.70 p<0.001

Predictive Accuracy of the Risk Score in the Validation Set Logistic regression Odds ratio 1.32, 95% CI 1.16-1.49 p<0.001 C-index 0.74 (risk score) versus 0.71 (STS prolonged ventilation model) in predicting postoperative pneumonia .

Summary Component Points Age ≥ 65 years 3 Chronic Lung Disease None Mild Moderate Severe 4 6 7 Peripheral Vascular Disease Cardiopulmonary Bypass Time >100 Minutes Intraoperative Red Blood Cell Transfusion 2 Pre- or Intraoperative Intra-Aortic Balloon Pump TOTAL POINTS POSSIBLE 22

Limitations Clinical diagnosis of pneumonia can be subjective In-hospital pneumonia diagnoses only Potential for other risk factors not captured in our analysis Did not account for interrelationship between pneumonia and other postoperative complications

Conclusions We derived and validated a risk score for postoperative pneumonia in adult patients undergoing cardiac surgery Immediately applicable on ICU arrival Risk score may aid in identifying high risk patients, and therefore have applications in: clinical research stratification targeting patients who will benefit from tailored preoperative management

A Novel Score to Estimate the Risk of Pneumonia After Cardiac Surgery Arman Kilic, MD1, Rika Ohkuma, MD 1, Joshua C. Grimm, MD1, J. Trent Magruder, MD1, Marc Sussman, MD1, Eric B. Schneider, PhD1, Glenn J.R. Whitman, MD1 1Division of Cardiac Surgery, Johns Hopkins Hospital, Baltimore, MD