Disability-free survival after major cardiac surgery: a population-based retrospective cohort study

Closing the care gap: combining enhanced recovery with minimally invasive valve surgery

PURPOSE OF REVIEW

Patients with advanced age and frailty require interventions for structural heart disease at an increasing rate. These patients typically experience higher rates of postoperative morbidity, mortality and prolonged hospital length of stay, loss of independence as well as associated increased costs to the healthcare system. Therefore, it is becoming critically important to raise awareness and develop strategies to improve clinical outcomes in the contemporary, high-risk patient population undergoing cardiacprocedures.

RECENT FINDINGS

Percutaneous options for structural heart disease have dramatically improved the therapeutic options for some older, frail, high-risk patients; however, others may still require cardiac surgery. Minimally invasive techniques can reduce some of the physiologic burden experienced by patients undergoing surgery and improve recovery. Enhanced Recovery After Cardiac Surgery (ERAS Cardiac) is a comprehensive, interdisciplinary, evidence-based approach to perioperative care. It has been shown to improve recovery and patient satisfaction while reducing complications and length of stay.

SUMMARY

Combining minimally invasive cardiac surgery with enhanced recovery protocols may result in improved patient outcomes for a patient population at high risk of morbidity and mortality following cardiac surgery.

Derivation and validation of pragmatic clinical models to predict hospital length of stay after cardiac surgery in Ontario, Canada: a population-based cohort study

BACKGROUND

Cardiac surgery is resource intensive and often requires multidisciplinary involvement to facilitate discharge. To facilitate evidence-based resource planning, we derived and validated clinical models to predict postoperative hospital length of stay (LOS).

METHODS

We used linked, population-level databases with information on all Ontario residents and included patients aged 18 years or older who underwent coronary artery bypass grafting, valvular or thoracic aorta surgeries between October 2008 and September 2019. The primary outcome was hospital LOS. The models were derived by using patients who had surgery before Sept. 30, 2016, and validated after that date. To address the rightward skew in LOS data and to identify top-tier resource users, we used logistic regression to derive a model to predict the likelihood of LOS being more than the 98th percentile (> 30 d), and γ regression in the remainder to predict continuous LOS in days. We used backward stepwise variable selection for both models.

RESULTS

Among 105 193 patients, 2422 (2.3%) had an LOS of more than 30 days. Factors predicting prolonged LOS included age, female sex, procedure type and urgency, comorbidities including frailty, high-risk acute coronary syndrome, heart failure, reduced left ventricular ejection fraction and psychiatric and pulmonary circulatory disease. The C statistic was 0.92 for the prolonged LOS model and the mean absolute error was 2.4 days for the continuous LOS model.

INTERPRETATION

We derived and validated clinical models to identify top-tier resource users and predict continuous LOS with excellent accuracy. Our models could be used to benchmark clinical performance based on expected LOS, rationally allocate resources and support patient-centred operative decision-making.

Heart Disease and Ageing: The Roles of Senescence, Mitochondria, and Telomerase in Cardiovascular Disease

During ageing molecular damage leads to the accumulation of several hallmarks of ageing including mitochondrial dysfunction, cellular senescence, genetic instability and chronic inflammation, which contribute to the development and progression of ageing-associated diseases including cardiovascular disease. Consequently, understanding how these hallmarks of biological ageing interact with the cardiovascular system and each other is fundamental to the pursuit of improving cardiovascular health globally. This review provides an overview of our current understanding of how candidate hallmarks contribute to cardiovascular diseases such as atherosclerosis, coronary artery disease and subsequent myocardial infarction, and age-related heart failure. Further, we consider the evidence that, even in the absence of chronological age, acute cellular stress leading to accelerated biological ageing expedites cardiovascular dysfunction and impacts on cardiovascular health. Finally, we consider the opportunities that modulating hallmarks of ageing offer for the development of novel cardiovascular therapeutics.

Derivation and External Validation of a Clinical Model to Predict Heart Failure Onset in Patients With Incident Diabetes

OBJECTIVE

Heart failure (HF) often develops in patients with diabetes and is recognized for its role in increased cardiovascular morbidity and mortality in this population. Most existing models predict risk in patients with prevalent rather than incident diabetes and fail to account for sex differences in HF risk factors. We derived sex-specific models in Ontario, Canada to predict HF at diabetes onset and externally validated these models in the U.K.

RESEARCH DESIGN AND METHODS

Retrospective cohort study using international population-based data. Our derivation cohort comprised all Ontario residents aged ≥18 years who were diagnosed with diabetes between 2009 and 2018. Our validation cohort comprised U.K. patients aged ≥35 years who were diagnosed with diabetes between 2007 and 2017. Primary outcome was incident HF. Sex-stratified multivariable Fine and Gray subdistribution hazard models were constructed, with death as a competing event.

RESULTS

A total of 348,027 Ontarians (45% women) and 54,483 U.K. residents (45% women) were included. At 1, 5, and 9 years, respectively, in the external validation cohort, the C-statistics were 0.81 (95% CI 0.79-0.84), 0.79 (0.77-0.80), and 0.78 (0.76-0.79) for the female-specific model; and 0.78 (0.75-0.80), 0.77 (0.76-0.79), and 0.77 (0.75-0.79) for the male-specific model. The models were well-calibrated. Age, rurality, hypertension duration, hemoglobin, HbA1c, and cardiovascular diseases were common predictors in both sexes. Additionally, mood disorder and alcoholism (heavy drinker) were female-specific predictors, while income and liver disease were male-specific predictors.

CONCLUSIONS

Our findings highlight the importance of developing sex-specific models and represent an important step toward personalized lifestyle and pharmacologic prevention of future HF development.

Comparison of Multidimensional Frailty Instruments for Estimation of Long-term Patient-Centered Outcomes After Cardiac Surgery

Importance

Little is known about the performance of available frailty instruments in estimating patient-relevant outcomes after cardiac surgery.

Objective

To examine how well the Johns Hopkins Adjusted Clinical Groups (ACG) frailty indicator, the Hospital Frailty Risk Score (HFRS), and the Preoperative Frailty Index (PFI) estimate long-term patient-centered outcomes after cardiac surgery.

Design, Setting, and Participants

This retrospective cohort study was conducted in Ontario, Canada, among residents 18 years and older who underwent coronary artery bypass grafting or aortic, mitral or tricuspid valve, or thoracic aorta surgery between October 2008 and March 2017. Long-term care residents, those with discordant surgical encounters, and those receiving dialysis or dependent on a ventilator within 90 days were excluded. Statistical analysis was conducted from July 2021 to January 2022.

Main Outcomes and Measures

The primary outcome was patient-defined adverse cardiovascular and noncardiovascular events (PACE), defined as the composite of severe stroke, heart failure, long-term care admission, new-onset dialysis, and ventilator dependence. Secondary outcomes included mortality and individual PACE events. The association between frailty and PACE was examined using cause-specific hazard models with death as a competing risk, and the association between frailty and death was examined using Cox models. Areas under the receiver operating characteristic curve (AUROC) were determined over 10 years of follow-up for each frailty instrument.

Results

Of 88 456 patients (22 924 [25.9%] female; mean [SD] age, 66.3 [11.1] years), 14 935 (16.9%) were frail according to ACG criteria, 63 095 (71.3%) according to HFRS, and 76 754 (86.8%) according to PFI. Patients with frailty were more likely to be older, female, and rural residents; to have lower income and multimorbidity; and to undergo urgent surgery. Patients meeting ACG criteria (hazard ratio [HR], 1.66; 95% CI, 1.60-1.71) and those with higher HFRS scores (HR per 1.0-point increment, 1.10; 95% CI, 1.09-1.10) and PFI scores (HR per 0.1-point increment, 1.75; 95% CI, 1.73-1.78) had higher rates of PACE. Similar magnitudes of association were observed for each frailty instrument with death and individual PACE components. The HFRS had the highest AUROC for estimating PACE during the first 2 years and death during the first 4 years, after which the PFI had the highest AUROC.

Conclusions and Relevance

These findings could help to tailor the use of frailty instruments by outcome and follow-up duration, thus optimizing preoperative risk stratification, patient-centered decision-making, candidate selection for prehabilitation, and personalized monitoring and health resource planning in patients undergoing cardiac surgery.

Preoperative Phase Angle as a Risk Indicator in Cardiac Surgery-A Prospective Observational Study

Background: The phase angle (PhA) can be used for prognostic assessments in critically ill patients. This study describes the perioperative course of PhA and associated risk indicators in a cohort of elective cardiac surgical patients. Methods: The PhA was measured in 168 patients once daily until postoperative day (POD) seven. Patients were split into two groups depending on their median preoperative PhA and analyzed for several clinical outcomes; logistic regression models were used. Results: The PhA decreased from preoperative (6.1° ± 1.9°) to a nadir on POD 2 (3.5° ± 2.5°, mean difference −2.6° (95% CI, −3.0°; −2.1°; p < 0.0001)). Patients with lower preoperative PhA were older (71.0 ± 9.1 vs. 60.9 ± 12.0 years; p < 0.0001) and frailer (3.1 ± 1.3 vs. 2.3 ± 1.1; p < 0.0001), needed more fluids (8388 ± 3168 vs. 7417 ± 2459 mL, p = 0.0287), and stayed longer in the ICU (3.7 ± 4.5 vs. 2.6 ± 3.8 days, p = 0.0182). Preoperative PhA was independently influenced by frailty (OR 0.77; 95% CI 0.61; 0.98; p = 0.0344) and cardiac function (OR 1.85; 95%CI 1.07; 3.19; p = 0.028), whereas the postoperative PhA decline was independently influenced by higher fluid balances (OR 0.86; 95% CI 0.75; 0.99; p = 0.0371) and longer cardiopulmonary bypass times (OR 0.99; 95% CI 0.98; 0.99; p = 0.0344). Conclusion: Perioperative PhA measurement is an easy-to-use bedside method that may critically influence risk evaluation for the outcome of cardiac surgery patients.

Association between timing of speech and language therapy initiation and outcomes among post-extubation dysphagia patients: a multicenter retrospective cohort study

Background

Post-extubation dysphagia (PED) is recognized as a common complication in the intensive care unit (ICU). Speech and language therapy (SLT) can potentially help improve PED; however, the impact of the timing of SLT initiation on persistent PED has not been well investigated. This study aimed to examine the timing of SLT initiation and its effect on patient outcomes after extubation in the ICU.

Methods

We conducted this multicenter, retrospective, cohort study, collecting data from eight ICUs in Japan. Patients aged ≥ 20 years with orotracheal intubation and mechanical ventilation for longer than 48 h, and those who received SLT due to PED, defined as patients with modified water swallowing test scores of 3 or lower, were included. The primary outcome was dysphagia at hospital discharge, defined as functional oral intake scale score < 5 or death after extubation. Secondary outcomes included dysphagia or death at the seventh, 14th, or 28th day after extubation, aspiration pneumonia, and in-hospital mortality. Associations between the timing of SLT initiation and outcomes were determined using multivariable logistic regression.

Results

A total of 272 patients were included. Of them, 82 (30.1%) patients exhibited dysphagia or death at hospital discharge, and their time spans from extubation to SLT initiation were 1.0 days. The primary outcome revealed that every day of delay in SLT initiation post-extubation was associated with dysphagia or death at hospital discharge (adjusted odds ratio (AOR), 1.09; 95% CI, 1.02–1.18). Similarly, secondary outcomes showed associations between this per day delay in SLT initiation and dysphagia or death at the seventh day (AOR, 1.28; 95% CI, 1.05–1.55), 14th day (AOR, 1.34; 95% CI, 1.13–1.58), or 28th day (AOR, 1.21; 95% CI, 1.07–1.36) after extubation and occurrence of aspiration pneumonia (AOR, 1.09; 95% CI, 1.02–1.17), while per day delay in post-extubation SLT initiation did not affect in-hospital mortality (AOR, 1.04; 95% CI, 0.97–1.12).

Conclusions

Delayed initiation of SLT in PED patients was associated with persistent dysphagia or death. Early initiation of SLT may prevent this complication post-extubation. A randomized controlled study is needed to validate these results.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-03974-6.

Association Between Handover of Anesthesiology Care and 1-Year Mortality Among Adults Undergoing Cardiac Surgery

Importance

Handovers of anesthesia care from one anesthesiologist to another is an important intraoperative event. Despite its association with adverse events after noncardiac surgery, its impact in the context of cardiac surgery remains unclear.

Objective

To compare the outcomes of patients who were exposed to anesthesia handover vs those who were unexposed to anesthesia handover during cardiac surgery.

Design, Setting, and Participants

This retrospective cohort study in Ontario, Canada, included Ontario residents who were 18 years or older and had undergone coronary artery bypass grafting or aortic, mitral, tricuspid valve, or thoracic aorta surgical procedures between 2008 and 2019. Exclusion criteria were non-Ontario residency status and other concomitant procedures. Statistical analysis was conducted from April 2021 to June 2021, and data collection occurred between November 2020 to January 2021.

Exposures

Complete handover of anesthesia care, where the case is completed by the replacement anesthesiologist.

Main Outcomes and Measures

The coprimary outcomes were mortality within 30 days and 1 year after surgery. Secondary outcomes were patient-defined adverse cardiac and noncardiac events (PACE), intensive care unit (ICU), and hospital lengths of stay (LOS). Inverse probability of treatment weighting based on the propensity score was used to estimate adjusted effect measures. Mortality was assessed using a Cox proportional hazard model, PACE using a cause-specific hazard model with death as a competing risk, and LOS using Poisson regression.

Results

Of the 102 156 patients in the cohort, 25 207 (24.7%) were women; the mean (SD) age was 66.4 (10.8) years; and 72 843 of surgical procedures (71.3%) were performed in teaching hospitals. Handover occurred in 1926 patients (1.9%) and was associated with higher risks of 30-day mortality (hazard ratio [HR], 1.89; 95% CI, 1.41-2.54) and 1-year mortality (HR, 1.66; 95% CI, 1.31-2.12), as well as longer ICU (risk ratio [RR], 1.43; 95% CI, 1.22-1.68) and hospital (RR, 1.17; 95% CI, 1.06-1.28) LOS. There was no statistically significant association between handover and PACE (30 days: HR 1.09; 95% CI, 0.79-1.49; 1 year: HR 0.89; 95% CI, 0.70-1.13).

Conclusions and Relevance

Handover of anesthesia care during cardiac surgical procedures was associated with higher 30-day and 1-year mortality rates and increased health care resource use. Further research is needed to evaluate and systematically improve the handover process qualitatively.

Derivation and validation of a clinical risk score to predict death among patients awaiting cardiac surgery in Ontario, Canada: a population-based study

BACKGROUND

Surgical delay may result in unintended harm to patients needing cardiac surgery, who are at risk for death if their condition is left untreated. Our objective was to derive and internally validate a clinical risk score to predict death among patients awaiting major cardiac surgery.

METHODS

We used the CorHealth Ontario Registry and linked ICES health administrative databases with information on all Ontario residents to identify patients aged 18 years or more who were referred for isolated coronary artery bypass grafting (CABG), valvular procedures, combined CABG-valvular procedures or thoracic aorta procedures between Oct. 1, 2008, and Sept. 30, 2019. We used a hybrid modelling approach with the random forest method for initial variable selection, followed by backward stepwise logistic regression modelling for clinical interpretability and parsimony. We internally validated the logistic regression model, termed the CardiOttawa Waitlist Mortality Score, using 200 bootstraps.

RESULTS

Of the 112 266 patients referred for cardiac surgery, 269 (0.2%) died while awaiting surgery (118/72 366 [0.2%] isolated CABG, 81/24 461 [0.3%] valvular procedures, 63/12 046 [0.5%] combined CABG-valvular procedures and 7/3393 [0.2%] thoracic aorta procedures). Age, sex, surgery type, left main stenosis, Canadian Cardiovascular Society classification, left ventricular ejection fraction, heart failure, atrial fibrillation, dialysis, psychosis and operative priority were predictors of waitlist mortality. The model discriminated (C-statistic 0.76 [optimism-corrected 0.73]). It calibrated well in the overall cohort (Hosmer-Lemeshow p = 0.2) and across surgery types.

INTERPRETATION

The CardiOttawa Waitlist Mortality Score is a simple clinical risk model that predicts the likelihood of death while awaiting cardiac surgery. It has the potential to provide data-driven decision support for managing access to cardiac care and preserve system capacity during the COVID-19 pandemic, the recovery period and beyond.