Using PAH-SYMPACT to assess quality of life in patients with pulmonary hypertension associated with chronic lung disease.

Chronic lung disease (CLD) is the second leading cause of pulmonary hypertension (PH) and is associated with significant morbidity and mortality. Although PH associated with CLD (PH-CLD) leads to impaired health-related quality of life (HRQOL), there are no validated tools to assess HRQOL in PH-CLD. The Pulmonary Arterial Hypertension-Symptoms and Impact Questionnaire (PAH-SYMPACT) is an HRQOL instrument aimed at assessing the symptoms and impact of PH on overall function and well-being. We performed a single-center prospective cohort study using PAH-SYMPACT scores to compare symptoms, exercise capacity and HRQOL in patients with PAH and PH-CLD. One hundred and twenty-five patients (99 patients with idiopathic/heritable PAH and 26 with PH-CLD) completed the PAH-SYMPACT questionnaire which consists of 22 questions that assess HRQOL across four domains: cardiopulmonary (CP) symptoms, cardiovascular (CV) symptoms, physical impact (PI), and cognitive/emotional (CE) impact. Higher scores indicate worse HRQOL. We compared patients with PAH and PH-CLD using a Wilcoxon rank sum or chi-squared test as appropriate. Multivariate linear regression analysis was used to assess the relationship between PH classification and SYMPACT scores. Compared to PAH, patients with PH-CLD were older, more likely to use oxygen and had worse functional class and exercise capacity. While there was no significant difference between the two groups in CP, CV, or CE domain scores, patients with PH-CLD had significantly worse PI scores by univariate (1.79 vs. 1.13, p < 0.001) and multivariate analysis (1.61 vs. 1.17, p = 0.02) and overall worse SYMPACT scores (1.19 vs. 0.91, p = 0.03). In conclusion, patients with PH-CLD have worse HRQOL as assessed by the PAH-SYMPACT questionnaire versus patients with PAH. Although PAH-SYMPACT has not been validated in PH-CLD, the results of this study can guide clinicians in understanding the symptoms and impact of PH-CLD relative to PAH.

Patients Aged 90 Years and Above With Acute Coronary Syndrome in the Cardiac Intensive Care Unit: Management and Outcomes.

Limited data exist regarding outcomes after coronary angiography (CAG) and percutaneous coronary intervention (PCI) in patients aged ≥90 years admitted to the cardiac intensive care unit (CICU) with acute coronary syndrome (ACS). We studied sequential CICU patients ≥90 years admitted with ACS from 2007 to 2018. Three therapeutic approaches were defined: (1) No CAG; (2) CAG without PCI (CAG/No PCI); and (3) CAG with PCI (CAG/PCI). In-hospital mortality was evaluated using multivariable logistic regression. All-cause 1-year mortality was evaluated using Kaplan-Meier and multivariable Cox proportional hazards analysis. The study included 239 patients with a median age of 92 (range 90 to 100) years (57% females; 45% ST-elevation myocardial infarction; 8% cardiac arrest; 16% shock). The No CAG group had higher Day 1 Sequential Organ Failure Assessment scores, more co-morbidities, worse kidney function, and fewer ST-elevation myocardial infarctions. In-hospital mortality was 20.8% overall and did not differ between the No CAG (n = 103; 21.4%), CAG/No PCI (n = 47; 21.3%), and CAG/PCI (n = 90; 20.0%) groups, before or after adjustment. Overall 1-year mortality was 52.5% and did not differ between groups before or after adjustment. Median survival was 6.9 months overall and 41.2% of hospital survivors died within 1 year of CICU admission. CICU patients aged ≥90 years with ACS have a substantial burden of illness with high in-hospital and 1-year mortality that was not lower in those who underwent CAG or PCI. These results suggest that careful patient selection for invasive coronary procedures is essential in this vulnerable population.

Exercise Test Predicts Both Noncardiovascular and Cardiovascular Death in a Primary Prevention Population.

OBJECTIVE: To identify specific causes of death and determine the prevalence of noncardiovascular (non-CV) deaths in an exercise test referral population while testing whether exercise test parameters predict non-CV as well as CV deaths. PATIENTS AND METHODS: Non-imaging exercise tests on patients 30 to 79 years of age from September 1993 to December 2010 were reviewed. Patients with baseline CV diseases and non-Minnesota residents were excluded. Mortality through January 2016 was obtained through Mayo Clinic Records and the Minnesota Death Index. Exercise test abnormalities included low functional aerobic capacity (ie, less than 80%), heart rate recovery (ie, less than 13 beats/min), low chronotropic index (ie, less than 0.8), and abnormal exercise electrocardiogram (ECG) of greater than or equal to 1.0 mm ST depression or elevation. We also combined these four abnormalities into a composite exercise test score (EX_SCORE). Statistical analyses consisted of Cox regression adjusted for age, sex, diabetes, hypertension, obesity, current and past smoking, and heart rate-lowering drug. RESULTS: The study identified 13,382 patients (females: n=4736, 35.4%, 50.5±10.5 years of age). During 12.7±5.0 years of follow-up, there were 849 deaths (6.3%); of these 162 (19.1%) were from CV; 687 (80.9%) were non-CV. Hazard ratios for non-CV death were significant for low functional aerobic capacity (HR, 1.42; 95% CI, 1.19 to 1.69; P<.0001), abnormal heart rate recovery (HR, 1.36; 95% CI, 1.15 to 1.61; P<.0033), and low chronotropic index (HR, 1.49; 95% CI, 1.26 to 1.77; P<.0001), whereas abnormal exercise ECG was not significant. All exercise test abnormalities including EX_SCORE were more strongly associated with CV death versus non-CV death except abnormal exercise ECG. CONCLUSION: Non-CV deaths predominated in this primary prevention cohort. Exercise test abnormalities not only predicted CV death but also non-CV death.

The feasibility and value of assessing patient-reported outcomes in pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) is a progressive pulmonary vascular disease that negatively impacts health-related quality of life (HRQOL). The PAH-symptoms and impact (PAH-SYMPACT) questionnaire is a validated disease-specific patient-reported outcome (PRO) instrument that assesses a patient's symptoms and the impact of PAH and its treatment on well-being. We performed a single-center prospective cohort study of patients with PAH to determine the feasibility of assessing PROs in clinical practice and to determine the association between PAH-SYMPACT domains and clinical characteristics and outcomes. One hundred and ten patients completed the 1-day version of the PAH-SYMPACT questionnaire which consists of 22 Likert-scale questions that assess HRQOL across four domains: cardiopulmonary (CP) symptoms, cardiovascular (CV) symptoms, physical impact (PI), and cognitive and emotional (CE) impact. Higher scores indicate worse HRQOL. Patients were predominantly female (n = 86, 78%) with a mean age of 57.8 ± 16.2 years. While several patient characteristics were associated with CP and PI domains, few were associated with CV and CE domains. PI and CE impact scores were associated with recent hospitalizations and mortality and CE impact score was independently associated with an increased risk of death after adjustment for disease severity (hazard ratio: 3.29, 95% confidence interval: 1.56-6.91, p = 0.002). In conclusion, the assessment of PROs in clinical practice using the PAH-SYMPACT questionnaire is both feasible and valuable. PAH-SYMPACT scores have independent prognostic value and are not adequately reflected by traditional measures of disease severity. These findings underscore the importance of assessing HRQOL in clinical practice.

Braden Skin Score Subdomains Predict Mortality Among Cardiac Intensive Care Patients.

BACKGROUND: The Braden Skin Score (BSS) is a bedside nursing assessment that may be a measure of frailty and predicts mortality among patients in the cardiac intensive care unit (CICU). We examined the association between each of the 6 individual BSS subscores with hospital mortality in patients in the CICU. We hypothesized that BSS subscores reflecting patient frailty would have a stronger association with outcomes. METHODS: Retrospective cohort study of unique adult patients admitted to the Mayo Clinic CICU from 2007 to 2018 with BSS documented on admission. Primary outcome was all-cause hospital mortality. Odds ratios (ORs) were determined using multivariable logistic regression. RESULTS: The 11,954 included patients had a mean age of 67.4 ± 15.2 years (37.8% women). Each individual BSS subscore was lower among patients who died in the hospital (all P < .001). The total BSS was inversely associated with in-hospital mortality across admission diagnoses and among patients with coma or mechanical ventilation; each individual subscore was inversely associated with in-hospital mortality. On multivariable regression, all subscores were inversely associated with hospital mortality after full adjustment. Shear had the strongest association (adjusted OR 0.59), followed by nutrition (adjusted OR 0.67), skin moisture (adjusted OR 0.76), mobility (adjusted OR 0.76), sensory perception (adjusted OR 0.82), and activity level (adjusted OR 0.85). CONCLUSION: BSS can serve as a rapid noninvasive screening tool for identifying poor outcomes in patients in the CICU. BSS subdomains that are more strongly associated with mortality appear to reflect physical frailty. Insofar as the BSS and its subscores measure frailty, a low BSS may identify frail patients.

The Mayo Cardiac Intensive Care Unit Admission Risk Score is Associated with Medical Resource Utilization During Hospitalization.

OBJECTIVE: To determine whether the Mayo Cardiac Intensive Care Unit (CICU) Admission Risk Score (M-CARS) is associated with CICU resource utilization. PATIENTS AND METHODS: Adult patients admitted to our CICU from 2007 to 2018 were retrospectively reviewed, and M-CARS was calculated from admission data. Groups were compared using Wilcoxon test for continuous variables and χ2 test for categorical variables. RESULTS: We included 12,428 patients with a mean age of 67±15 years (37% female patients). The mean M-CARS was 2.1±2.1, including 5890 (47.4%) patients with M-CARS less than 2 and 644 (5.2%) patients with M-CARS greater than 6. Critical care restricted therapies were frequently used, including mechanical ventilation in 28.0%, vasoactive medications in 25.5%, and dialysis in 4.8%. A higher M-CARS was associated with greater use of critical-care therapies and longer CICU and hospital length of stay. The low-risk cohort with M-CARS less than 2 was less likely to require critical-care-restricted therapies, including invasive or noninvasive mechanical ventilation (8.0% vs 46.1%), vasoactive medications (10.1% vs 38.8%), or dialysis (1.0% vs 8.2%), compared with patients with M-CARS greater than or equal to 2 (all P<.001). CONCLUSION: Patients with M-CARS less than 2 infrequently require critical-care resources and have extremely low mortality, suggesting that the M-CARS could be used to facilitate the triage of critically ill cardiac patients.

Predicting 1-Year Mortality on Admission Using the Mayo Cardiac Intensive Care Unit Admission Risk Score.

OBJECTIVE: To determine whether the Mayo Cardiac Intensive Care Unit (CICU) Admission Risk Score (M-CARS) accurately predicts 1-year mortality. METHODS: We retrospectively reviewed adult CICU patients admitted from January 1, 2007, through April 30, 2018, and calculated M-CARS using admission data. We examined the association between admission M-CARS, as continuous and categorical variables, and 1-year mortality. RESULTS: This study included 12,428 unique patients with a mean age of 67.6±15.2 years (4686 [37.7%] female). A total of 2839 patients (22.8%) died within 1 year of admission, including 1149 (9.2%) hospital deaths and 1690 (15.0%) of the 11,279 hospital survivors. The 1-year survival decreased incrementally as a function of increasing M-CARS (P<.001), and all components of M-CARS were significant predictors of 1-year mortality (P<.001). The 1-year survival among hospital survivors decreased incrementally as a function of increasing M-CARS for scores below 3 (all P<.001); however, there was no further decrease in 1-year survival for hospital survivors with M-CARS of 3 or more (P=.99). The M-CARS components associated with 1-year mortality among hospital survivors included blood urea nitrogen, red blood cell distribution width, Braden skin score, and respiratory failure (all P<.001). CONCLUSION: M-CARS predicted 1-year mortality among CICU admissions, with a plateau effect at high M-CARS of 3 or more for hospital survivors. Significant added predictors of 1-year mortality among hospital survivors included markers of frailty and chronic illness.

Shock in the cardiac intensive care unit: Changes in epidemiology and prognosis over time.

There are few studies documenting the changing epidemiology and outcomes of shock in cardiac intensive care unit (CICU) patients. We sought to describe the changes in shock epidemiology and outcomes over time in a CICU population. METHODS: We included 1859 unique patients admitted to the Mayo Clinic Rochester CICU from 2007 through 2018 with an admission diagnosis of shock. Temporal trends, including mortality, were assessed across 3-year periods. RESULTS: Shock comprised 15.1% of CICU admissions during the study period, increasing from 8.8% of CICU admissions in 2007 to 21.6% in 2018 (P < .01 for trend). Mean age was 68 ±â€¯14 years (38% females). Shock was cardiogenic in 65%, septic in 10% and mixed cardiogenic-septic in 15%. Concomitant diagnoses in patients with cardiogenic shock (CS) included acute coronary syndrome (ACS) in 17%, heart failure (HF) in 35% and both in 40%. There was no significant change in the prevalence of individual shock subtypes over time (P > .1). Among patients with CS, the prevalence of ACS decreased and the prevalence of HF increased over time (P < .01). Hospital mortality was highest among patients with mixed shock (39%; P = .05). Among patients with CS, hospital mortality was lower among those with HF compared to those without HF (31% vs. 40%, P < .01). Hospital mortality decreased over time among patients with shock (P < .01) and CS (P = .02). CONCLUSIONS: The prevalence of shock in the CICU has increased over time, with a substantial prevalence of mixed CS. The etiology of CS has changed over the last decade with HF overtaking ACS as the most common cause of CS in the CICU.

Prevalence of Noncardiac Multimorbidity in Patients Admitted to Two Cardiac Intensive Care Units and Their Association with Mortality.

BACKGROUND: Current cardiac intensive care unit (CICU) practice has seen an increase in patient complexity, including an increase in noncardiac organ failure, critical care therapies, and comorbidities. We sought to describe the changing epidemiology of noncardiac multimorbidity in the CICU population. METHODS: We analyzed consecutive unique patient admissions to 2 geographically distant tertiary care CICUs (n = 16,390). We assessed for the prevalence of 0, 1, 2, and ≥3 noncardiac comorbidities (diabetes, chronic lung, liver, and kidney disease, cancer, and stroke/transient ischemic attack) and their associations with hospital and postdischarge 1-year mortality using multivariable logistic regression. RESULTS: The prevalence of 0, 1, 2, and ≥3 noncardiac comorbidities was 37.7%, 31.4%, 19.9%, and 11.0%, respectively. Increasing noncardiac comorbidities were associated with a stepwise increase in mortality, length of stay, noncardiac indications for ICU admission, and increased utilization of critical care therapies. After multivariable adjustment, compared with those without noncardiac comorbidities, there was an increased hospital mortality for patients with 1 (odds ratio [OR] 1.30; 95% confidence interval [CI], 1.10-1.54, P = .002), 2 (OR 1.47; 95% CI, 1.22-1.77, P < .001), and ≥3 (OR 1.79; 95% CI, 1.44-2.22, P < .001) noncardiac comorbidities. Similar trends for each additional noncardiac comorbidity were seen for postdischarge 1-year mortality (P < .001, all). CONCLUSIONS: In 2 large contemporary CICU populations, we found that noncardiac multimorbidity was highly prevalent and a strong predictor of short- and long-term adverse clinical outcomes. Further study is needed to define the best care pathways for CICU patients with acute cardiac illness complicated by noncardiac multimorbidity.

Admission Braden Skin Score Independently Predicts Mortality in Cardiac Intensive Care Patients.

OBJECTIVE: To determine whether a low Braden skin score (BSS), reflecting increased risk for skin pressure injury, would predict lower survival in cardiac intensive care unit (CICU) patients after adjustment for illness severity and comorbidities. PATIENTS AND METHODS: This retrospective cohort study included consecutive unique adult patients admitted to a single tertiary care referral hospital CICU from January 1, 2007, through December 31, 2015, who had a BSS documented on CICU admission. The primary outcome was all-cause hospital mortality, using elastic net penalized logistic regression to determine predictors of hospital mortality. The secondary outcome was all-cause post-discharge mortality, using Cox proportional hazards models to determine predictors of post-discharge mortality. RESULTS: The study included 9552 patients with a mean age of 67.4±15.2 years (3589 [37.6%] were females) and a hospital mortality rate of 8.3%. Admission BSS was inversely associated with hospital mortality (unadjusted odds ratio, 0.70; 95% CI, 0.68-0.72; P<.001; area under the receiver operator curve, 0.80; 95% CI, 0.78-0.82), with increased short-term mortality as a function of decreasing admission BSS. After adjustment for illness severity and comorbidities using multivariable analysis, admission BSS remained inversely associated with hospital mortality (adjusted odds ratio, 0.88; 95% CI, 0.85-0.92; P<.001). Among hospital survivors, admission BSS was inversely associated with post-discharge mortality after adjustment for illness severity and comorbidities (adjusted hazard ratio, 0.89; 95% CI, 0.88-0. 90; P<.001). CONCLUSION: The admission BSS, a simple inexpensive bedside nursing assessment potentially reflecting frailty and overall illness acuity, was independently associated with hospital and post-discharge mortality when added to established multiparametric illness severity scores among contemporary CICU patients.

Derivation and Validation of a Novel Cardiac Intensive Care Unit Admission Risk Score for Mortality.

Background There are no risk scores designed specifically for mortality risk prediction in unselected cardiac intensive care unit (CICU) patients. We sought to develop a novel CICU-specific risk score for prediction of hospital mortality using variables available at the time of CICU admission. Methods and Results A database of CICU patients admitted from January 1, 2007 to April 30, 2018 was divided into derivation and validation cohorts. The top 7 predictors of hospital mortality were identified using stepwise backward regression, then used to develop the Mayo CICU Admission Risk Score (M-CARS), with integer scores ranging from 0 to 10. Discrimination was assessed using area under the receiver-operator curve analysis. Calibration was assessed using the Hosmer-Lemeshow statistic. The derivation cohort included 10 004 patients and the validation cohort included 2634 patients (mean age 67.6 years, 37.7% females). Hospital mortality was 9.2%. Predictor variables included in the M-CARS were cardiac arrest, shock, respiratory failure, Braden skin score, blood urea nitrogen, anion gap and red blood cell distribution width at the time of CICU admission. The M-CARS showed a graded relationship with hospital mortality (odds ratio 1.84 for each 1-point increase in M-CARS, 95% CI 1.78-1.89). In the validation cohort, the M-CARS had an area under the receiver-operator curve of 0.86 for hospital mortality, with good calibration (P=0.21). The 47.1% of patients with M-CARS <2 had hospital mortality of 0.8%, and the 5.2% of patients with M-CARS >6 had hospital mortality of 51.6%. Conclusions Using 7 variables available at the time of CICU admission, the M-CARS can predict hospital mortality in unselected CICU patients with excellent discrimination.

Changes in comorbidities, diagnoses, therapies and outcomes in a contemporary cardiac intensive care unit population.

Prior studies have demonstrated that the cardiac intensive care unit (CICU) patient population has evolved over time. We sought to describe the temporal changes in comorbidities, illness severity, diagnoses, procedures and adjusted mortality within our CICU practice in recent years. METHODS: We retrospectively reviewed unique CICU admissions at the Mayo Clinic from January 2007 to April 2018. Comorbidities, severity of illness scores, discharge diagnosis codes and CICU procedures and therapies were recorded, and temporal trends were assessed using linear regression and Cochran-Armitage trend tests. Trends in adjusted hospital mortality over time were assessed using multivariable logistic regression. RESULTS: We included 12,418 patients with a mean age of 67.6 years (including 37.7% females). Temporal trends in the prevalence of several comorbidities and discharge diagnoses were observed, reflecting an increase in the prevalence of non-coronary cardiovascular diseases, critical care diagnoses, and organ failure (all P ≪ .05). The use of several CICU therapies and procedures increased over time, including mechanical ventilation, invasive lines and vasoactive drugs (all P ≪ .05). A temporal decrease in adjusted hospital mortality was observed among the subgroup of patients with (adjusted OR per year 0.97, 95% CI 0.94-0.99, P = .023) and without (adjusted OR per year 0.91, 95% CI 0.85-0.96, P = .002) a critical care discharge diagnosis. CONCLUSIONS: We observed an increasing prevalence of critical care and organ failure diagnoses as well as increased utilization of critical care therapies in this CICU cohort, associated with a decrease in risk-adjusted hospital mortality over time.

Severity of illness assessment with application of the APACHE IV predicted mortality and outcome trends analysis in an academic cardiac intensive care unit.

PURPOSE: To assess trends in life support interventions and performance of the automated Acute Physiology and Chronic Health Evaluation (APACHE) IV model at mortality prediction compared with Oxford Acute Severity of Illness Score (OASIS) in a contemporary cardiac intensive care unit (CICU). METHODS AND MATERIALS: Retrospective analysis of adults (age ≥ 18 years) admitted to CICU from January 1, 2007, through December 31, 2015. Temporal trends were assessed with linear regression. Discrimination of each risk score for hospital mortality was assessed with use of area under the receiver operating characteristic curve (AUROC) values. Calibration was assessed with Hosmer-Lemeshow goodness-of-fit test. RESULTS: The study analyzed 10,004 patients. CICU and hospital mortality rates were 5.7% and 9.1%. APACHE IV predicted death had an AUROC of 0.82 (0.81-0.84) for hospital death, compared with 0.79 for OASIS (P < .05). Calibration was better for OASIS than APACHE IV. Increases were observed in CICU and hospital lengths of stay (both P < .001), APACHE IV predicted mortality (P = .007), Charlson Comorbidity Index (P < .001), noninvasive ventilation use (P < .001), and noninvasive ventilation days (P = .02). CONCLUSIONS: Contemporary CICU patients are increasingly ill, observed in upward trends in comorbid conditions and life support interventions. APACHE IV predicted death and OASIS showed good discrimination in predicting death in this population. APACHE IV and OASIS may be useful for benchmarking and quality improvement initiatives in the CICU, the former having better discrimination.

Comparison of Mortality Risk Prediction Among Patients ≥70 Versus <70 Years of Age in a Cardiac Intensive Care Unit.

Older adults account for an increasing number of cardiac intensive care unit (CICU) admissions. This study sought to determine the predictive value of illness severity scores for mortality in CICU patients ≥70 years of age. Adult patients admitted to the CICU from 2007 to 2015 at one tertiary care hospital were reviewed. Severity of illness scores were calculated on the first CICU day. Area under the receiver-operator characteristic curve (AUROC) values were used to assess discrimination for hospital mortality in patients ≥70 versus <70 years of age. We included 10,004 patients with a mean age of 67.4 ± 15.2 years (37.4% female); 4,771 patients (47.7%) were ≥70 years of age. Patients ≥70 years of age had greater illness severity and more extensive co-morbidities compared with patients <70 years of age. Patients ≥70 years of age had higher hospital mortality (11.6% vs 6.8%, odds ratio 1.80, 95% confidence interval 1.57 to 2.07, p <0.001), with a progressive increase in mortality as a function of decade. Severity of illness scores had lower AUROC values for hospital mortality in patients ≥70 years of age compared with patients <70 years of age (all p <0.05 by DeLong test). The Braden skin score on CICU admission predicted hospital mortality with an AUROC value only slightly lower than these scores. Increasing age decade was associated with decreased postdischarge survival by Kaplan-Meier analysis (p <0.001 by log-rank). In conclusion, contemporary CICU patients ≥70 years of age have greater illness severity, more co-morbidities and higher mortality than patients <70 years of age, yet severity of illness scores are less accurate for predicting mortality in CICU patients ≥70 years of age, emphasizing the need for more effective risk-stratification methods in this population.

Effect of Cardiorespiratory Fitness on Co-Morbidities and Mortality in Never, Past, and Current Smokers.

Smoking is a strong risk factor for cardiovascular (CV) disease and mortality, but quitting may cause weight gain and increase the risk of co-morbidities. Our aim was to investigate the effect of smoking and exercise on weight-associated co-morbidities and mortality. We included Minnesota residents without baseline CV disease who underwent exercise testing from 1993 to 2010. Mortality was determined from Mayo Clinic records and Minnesota Death Index. Total, CV and cancer mortality by smoking status and cardiorespiratory fitness (CRF): (1) <80%, (2) 80% to 99%, (3) ≥100%. Differences were tested using logistic and Cox regression adjusting for age and gender. A total of 21,981 patients (7,090 past, 2,464 current smokers) were included. Past smokers had more obesity, hypertension, diabetes, and low CRF compared with never smokers. Current smokers did not show increased risk factor prevalence compared with never smokers but had higher rates of low CRF. There were 1,749 deaths; mean follow-up was 12 ± 5 years. Mortality was only slightly increased in past versus never smokers (Hazard Ratio: 1.2; 95% confidence interval 1.12 to 1.38) but was much higher in current smokers (Hazard Ratio 2.4; 95% confidence interval 2.05 to 2.80). Mortality in never, past, and current smokers was inversely related to CRF level. In conclusion, past smokers showed higher rates of co-morbidities and low CRF, but mortality was only mildly increased versus never smokers, whereas current smokers carried a high mortality risk. Our data suggest that quitting smoking is beneficial despite the increased co-morbidities. Exercise may potentially mitigate the risk of co-morbidities and death in those who quit smoking.