'Fit for surgery': The relationship between cardiorespiratory fitness and postoperative outcomes

Multi-Modal Prehabilitation in Thoracic Surgery: From Basic Concepts to Practical Modalities

Over the last two decades, the invasiveness of thoracic surgery has decreased along with technological advances and better diagnostic tools, whereas the patient's comorbidities and frailty patterns have increased, as well as the number of early cancer stages that could benefit from curative resection. Poor aerobic fitness, nutritional defects, sarcopenia and "toxic" behaviors such as sedentary behavior, smoking and alcohol consumption are modifiable risk factors for major postoperative complications. The process of enhancing patients' physiological reserve in anticipation for surgery is referred to as prehabilitation. Components of prehabilitation programs include optimization of medical treatment, prescription of structured exercise program, correction of nutritional deficits and patient's education to adopt healthier behaviors. All patients may benefit from prehabilitation, which is part of the enhanced recovery after surgery (ERAS) programs. Faster functional recovery is expected in low-risk patients, whereas better clinical outcome and shorter hospital stay have been demonstrated in higher risk and physically unfit patients.

Deep learned representations of the resting 12-lead electrocardiogram to predict at peak exercise

AIMS

To leverage deep learning on the resting 12-lead electrocardiogram (ECG) to estimate peak oxygen consumption (V˙O2peak) without cardiopulmonary exercise testing (CPET).

METHODS AND RESULTS

V ˙ O 2 peak estimation models were developed in 1891 individuals undergoing CPET at Massachusetts General Hospital (age 45 ± 19 years, 38% female) and validated in a separate test set (MGH Test, n = 448) and external sample (BWH Test, n = 1076). Three penalized linear models were compared: (i) age, sex, and body mass index ('Basic'), (ii) Basic plus standard ECG measurements ('Basic + ECG Parameters'), and (iii) basic plus 320 deep learning-derived ECG variables instead of ECG measurements ('Deep ECG-V˙O2'). Associations between estimated V˙O2peak and incident disease were assessed using proportional hazards models within 84 718 primary care patients without CPET. Inference ECGs preceded CPET by 7 days (median, interquartile range 27-0 days). Among models, Deep ECG-V˙O2 was most accurate in MGH Test [r = 0.845, 95% confidence interval (CI) 0.817-0.870; mean absolute error (MAE) 5.84, 95% CI 5.39-6.29] and BWH Test (r = 0.552, 95% CI 0.509-0.592, MAE 6.49, 95% CI 6.21-6.67). Deep ECG-V˙O2 also outperformed the Wasserman, Jones, and FRIEND reference equations (P < 0.01 for comparisons of correlation). Performance was higher in BWH Test when individuals with heart failure (HF) were excluded (r = 0.628, 95% CI 0.567-0.682; MAE 5.97, 95% CI 5.57-6.37). Deep ECG-V˙O2 estimated V˙O2peak <14 mL/kg/min was associated with increased risks of incident atrial fibrillation [hazard ratio 1.36 (95% CI 1.21-1.54)], myocardial infarction [1.21 (1.02-1.45)], HF [1.67 (1.49-1.88)], and death [1.84 (1.68-2.03)].

CONCLUSION

Deep learning-enabled analysis of the resting 12-lead ECG can estimate exercise capacity (V˙O2peak) at scale to enable efficient cardiovascular risk stratification.

Wearable Sensors as a Preoperative Assessment Tool: A Review

Surgery is a common first-line treatment for many types of disease, including cancer. Mortality rates after general elective surgery have seen significant decreases whilst postoperative complications remain a frequent occurrence. Preoperative assessment tools are used to support patient risk stratification but do not always provide a precise and accessible assessment. Wearable sensors (WS) provide an accessible alternative that offers continuous monitoring in a non-clinical setting. They have shown consistent uptake across the perioperative period but there has been no review of WS as a preoperative assessment tool. This paper reviews the developments in WS research that have application to the preoperative period. Accelerometers were consistently employed as sensors in research and were frequently combined with photoplethysmography or electrocardiography sensors. Pre-processing methods were discussed and missing data was a common theme; this was dealt with in several ways, commonly by employing an extraction threshold or using imputation techniques. Research rarely processed raw data; commercial devices that employ internal proprietary algorithms with pre-calculated heart rate and step count were most commonly employed limiting further feature extraction. A range of machine learning models were used to predict outcomes including support vector machines, random forests and regression models. No individual model clearly outperformed others. Deep learning proved successful for predicting exercise testing outcomes but only within large sample-size studies. This review outlines the challenges of WS and provides recommendations for future research to develop WS as a viable preoperative assessment tool.

Data Processing Strategies to Determine Maximum Oxygen Uptake: A Systematic Scoping Review and Experimental Comparison with Guidelines for Reporting

BACKGROUND

Gas exchange data from maximum oxygen uptake ([Formula: see text]) testing typically require post-processing. Different processing strategies may lead to varying [Formula: see text] values affecting their interpretation. However, the exact processing strategies used in the literature have yet to be systematically investigated. Previous research investigated differences across methods at the group level only.

METHODS

Out of a random sample, we investigated 242 recently published articles that measured [Formula: see text] during ramp tests. Reported data processing methods and their rationale were extracted. We compared the most common processing strategies on a data set of 72 standardized exercise tests in trained athletes.

RESULTS

Half of the included studies did not report their data processing strategy and almost all articles failed to provide a rationale for the particular strategy chosen. Most studies use binned time averages to determine [Formula: see text], with a minority using moving time or moving breath averages. The processing strategies found in the literature can lead to mean differences in [Formula: see text] of more than 5% (range 0-7%) with considerable variation at the individual level.

CONCLUSIONS

We advise researchers to change their processing strategy and use moving averages or digital filters instead of binned averages. Researchers should report their data processing strategy used to determine [Formula: see text]. We provide a reporting checklist of seven items that can function as a template for reporting.

Cardiac and intramuscular adaptations following short-term exercise prehabilitation in unfit patients scheduled to undergo hepatic or pancreatic surgery: study protocol of a multinuclear MRI study

INTRODUCTION

Short-term exercise prehabilitation programmes have demonstrated promising results in improving aerobic capacity of unfit patients prior to major abdominal surgery. However, little is known about the cardiac and skeletal muscle adaptations explaining the improvement in aerobic capacity following short-term exercise prehabilitation.

METHODS AND ANALYSIS

In this single-centre study with a pretest-post-test design, 12 unfit patients with a preoperative oxygen uptake (VO2) at the ventilatory anaerobic threshold ≤13 mL/kg/min and/or VO2 at peak exercise ≤18 mL/kg/min, who are scheduled to undergo hepatopancreatobiliary surgery at the University Medical Center Groningen (UMCG), the Netherlands, will be recruited. As part of standard care, unfit patients are advised to participate in a home-based exercise prehabilitation programme, comprising high-intensity interval training and functional exercises three times per week, combined with nutritional support, during a 4-week period. Pre-intervention and post-intervention, patients will complete a cardiopulmonary exercise test. Next to this, study participants will perform additional in-vivo exercise cardiac magnetic resonance (MR) imaging and phosphorus 31-MR spectroscopy of the quadriceps femoris muscle before and after the intervention to assess the effect on respectively cardiac and skeletal muscle function.

ETHICS AND DISSEMINATION

This study was approved in May 2023 by the Medical Research Ethics Committee of the UMCG (registration number NL83611.042.23, March 2023) and is registered in the ClinicalTrials.gov register. Results of this study will be submitted for presentation at (inter)national congresses and publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT05772819.

Cardiopulmonary Exercise Testing in Patients with Heart Failure: Impact of Gender in Predictive Value for Heart Transplantation Listing

BACKGROUND

Exercise testing is key in the risk stratification of patients with heart failure (HF). There are scarce data on its prognostic power in women. Our aim was to assess the predictive value of the heart transplantation (HTx) thresholds in HF in women and in men.

METHODS

Prospective evaluation of HF patients who underwent cardiopulmonary exercise testing (CPET) from 2009 to 2018 for the composite endpoint of cardiovascular mortality and urgent HTx.

RESULTS

A total of 458 patients underwent CPET, with a composite endpoint frequency of 10.5% in females vs. 16.0% in males in 36-month follow-up. Peak VO2 (pVO2), VE/VCO2 slope and percent of predicted pVO2 were independent discriminators of the composite endpoint, particularly in women. The International Society for Heart Lung Transplantation recommended values of pVO2 ≤ 12 mL/kg/min or ≤14 if the patient is intolerant to β-blockers, VE/VCO2 slope > 35, and percent of predicted pVO2 ≤ 50% showed a higher diagnostic effectiveness in women. Specific pVO2, VE/VCO2 slope and percent of predicted pVO2 cut-offs in each sex group presented a higher prognostic power than the recommended thresholds.

CONCLUSION

Individualized sex-specific thresholds may improve patient selection for HTx. More evidence is needed to address sex differences in HF risk stratification.

Myths and methodologies: Cardiopulmonary exercise testing for surgical risk stratification in patients with an abdominal aortic aneurysm; balancing risk over benefit

The extent to which patients with an abdominal aortic aneurysm (AAA) should exercise remains unclear, given theoretical concerns over the perceived risk of blood pressure-induced rupture, which is often catastrophic. This is especially pertinent during cardiopulmonary exercise testing, when patients are required to perform incremental exercise to symptom-limited exhaustion for the determination of cardiorespiratory fitness. This multimodal metric is being used increasingly as a complementary diagnostic tool to inform risk stratification and subsequent management of patients undergoing AAA surgery. In this review, we bring together a multidisciplinary group of physiologists, exercise scientists, anaesthetists, radiologists and surgeons to challenge the enduring 'myth' that AAA patients should be fearful of and avoid rigorous exercise. On the contrary, by appraising fundamental vascular mechanobiological forces associated with exercise, in conjunction with 'methodological' recommendations for risk mitigation specific to this patient population, we highlight that the benefits conferred by cardiopulmonary exercise testing and exercise training across the continuum of intensity far outweigh the short-term risks posed by potential AAA rupture.

Analysis of Individual V˙O2max Responses during a Cardiopulmonary Exercise Test and the Verification Phase in Physically Active Women

This study aimed to investigate the test-retest reliability, mean, and individual responses in the measurement of maximal oxygen consumption (V˙O2max) during a cardiopulmonary exercise test (CPET) and the verification phase during cycle ergometry in women. Nine women (22 ± 2 yrs, 166.0 ± 4.5 cm, 58.6 ± 7.7 kg) completed a CPET, passively rested for 5 min, and then completed a verification phase at 90% of peak power output to determine the highest V˙O2 from the CPET (V˙O2CPET) and verification phase (V˙O2verification) on 2 separate days. Analyses included a two-way repeated measures ANOVA, intraclass correlation coefficients (ICC2,1), standard errors of the measurement (SEM), minimal differences (MD), and coefficients of variation (CoV). There was no test (test 1 versus test 2) × method (CPET vs. verification phase) interaction (p = 0.896) and no main effect for method (p = 0.459). However, test 1 (39.2 mL·kg-1·min-1) was significantly higher than test 2 (38.3 mL·kg-1·min-1) (p = 0.043). The V˙O2CPET (ICC = 0.984; CoV = 1.98%; SEM = 0.77 mL·kg-1·min-1; MD = 2.14 mL·kg-1·min-1) and V˙O2verification (ICC = 0.964; CoV = 3.30%; SEM = 1.27 mL·kg-1·min-1; MD = 3.52 mL·kg-1·min-1) demonstrated "excellent" reliability. Two subjects demonstrated a test 1 V˙O2CPET that exceeded the test 2 V˙O2CPET, and one subject demonstrated a test 1 V˙O2verification that exceeded the test 2 V˙O2verification by more than the respective CPET and verification phase MD. One subject demonstrated a V˙O2CPET that exceeded the V˙O2verification, and one subject demonstrated a V˙O2verification that exceeded the V˙O2CPET by more than the MD. These results demonstrate the importance of examining the individual responses in the measurement of the V˙O2max and suggest that the MD may be a useful threshold to quantify real individual changes in V˙O2.

Temporary hypoxemia at high altitude in an intensive care unit physician

A 42-year-old pediatric intensive care unit physician traveled to Nepal and took a helicopter trip to Everest Base Camp. The helicopter reached an altitude of 5500 m during flight and descended at different destinations with varying altitudes. At Hotel Everest View at 3820 m, his oxygen saturation was 79%. He had mild tachypnea and deep breathing but was able to walk around, jump, and take photographs. He returned to Kathmandu (altitude, 1324 m) without using any supplemental oxygen during the entire trip. Based on calculations with the alveolar gas equation, he observed that he and his fellow passengers probably had hypoxemia during the trip. In summary, temporary hypoxemia associated with high altitude in healthy individuals without cardiorespiratory compromise may not require oxygen therapy. In contrast, intensive care unit patients who have respiratory failure may have similar oxygen saturation levels but may require oxygen therapy and mechanical ventilation. The oxygen saturation level must be interpreted in consideration of the clinical scenario before deciding about the need for oxygen therapy.