The combined risk predictive power of frailty and hypoalbuminemia in free tissue flap reconstruction: A cohort study of 34,571 patients from the NSQIP database.

INTRODUCTION: Significant morbidity and mortality are hallmarks of the functional decline seen in physically frail patients. The modified frailty index 5 (mFI-5) represents a risk predictor score that has been validated as a comorbidity-based scale in surgery. Serum albumin levels of <3.5 g/dL (hypoalbuminemia) have also been implicated with poor postoperative outcomes. However, the association between these two parameters remains to be investigated. We aimed to elucidate the interdependence of preoperative albumin levels and frailty, as evaluated by the mFI-5 score, and its reliability to prognosticate postoperative results in free flap reconstruction (FFR). METHODS: We conducted a multicenter, retrospective cohort study and accessed the ACS National Surgical Quality Improvement Program (ACS-NSQIP) from 2008 to 2021. We identified all adult patients (≥18 years of age) who underwent a FFR. We extracted perioperative data and lab values including albumin. Multivariable linear and logistic regression analyses were performed to identify independent risk predictors. Main outcomes involved mortality, length of hospital stay, reoperation, medical and surgical complications, and discharge destination within the 30-day postoperative period. RESULTS: A total of 34,571 patients were included in the study, with an average age of 53.9 years (standard deviation [SD] 12.2) and an average body mass index (BMI) of 28.8 (SD 6.1). Of these patients, 7484 were male (21.6%), whereas 22,363 (64.7%) had no frailty (mFI = 0). Additionally, 9466 patients had a frailty score of 1 (27.4%), 2505 had a score of 2 (7.2%), 226 had a score of 3 (0.7%), and 11 had a score of 4 or higher (0.0%). Albumin levels were available for 16,250 patients (47.0%), and among them, 1334 (8.2%) had hypoalbuminemia. Regression analyses showed that higher mFI scores were independent predictors of any, surgical, and medical complications, as well as increased rates of reoperations, unplanned readmissions, and prolonged hospital stays. Hypoalbuminemia independently predicted any, surgical, and medical complications, and higher mortality, reoperation, and longer hospital stay. When both frailty and albumin levels (mFI-5 and albumin) were considered together, this combined assessment was found to be a more accurate predictor of all major outcomes (any, medical and surgical complications, mortality, and reoperation). Further, our analysis identified a weak negative correlation between serum albumin levels and mFI scores (Spearman R: -.1; p < .0001). CONCLUSION: In conclusion, this cohort study highlights the association of hypoalbuminemia with adverse postoperative outcomes, including those not directly related to frailty. Simultaneously, higher mFI scores independently predicted outcomes not associated with hypoalbuminemia. Stemming from these findings, we recommend considering both serum albumin levels and frailty in patients receiving FFR. This perioperative algorithm may help provide more individualized planning including multidisciplinary care and pre and posthabilitation.

General independent censoring in event-driven trials with staggered entry.

Randomized clinical trials with time-to-event endpoints are frequently stopped after a prespecified number of events has been observed. This practice leads to dependent data and nonrandom censoring, which can in general not be solved by conditioning on the underlying baseline information. In case of staggered study entry, matters are complicated substantially. The present paper demonstrates that the study design at hand entails general independent censoring in the counting process sense, provided that the analysis is based on study time information only. To illustrate that the filtrations must not use abundant information, we simulated data of event-driven trials and evaluated them by means of Cox regression models with covariates for the calendar times. The Breslow curves of the cumulative baseline hazard showed considerable deviations, which implies that the analysis is disturbed by conditioning on the calendar time variables. A second simulation study further revealed that Efron's classical bootstrap, unlike the (martingale-based) wild bootstrap, may lead to biased results in the given setting, as the assumption of random censoring is violated. This is exemplified by an analysis of data on immunotherapy in patients with advanced, previously treated nonsmall cell lung cancer.

The individual relationship between atrial fibrillation sources from CARTOFINDER mapping and atrial cardiomyopathy: The catch me if you can trial.

BACKGROUND: Targeting individual sources identified during atrial fibrillation (AF) has been used as an ablation strategy with varying results. OBJECTIVE: Aim of this study was to evaluate the relationship between regions of interest (ROIs) from CARTOFINDER (CF) mapping and atrial cardiomyopathy from late gadolinium enhancement (LGE) cardiovascular magnetic resonance imaging (CMR). METHODS: Twenty consecutive patients underwent index catheter ablation for persistent AF (PERS AF). Pre-processed LGE CMR images were merged with the results from CF mapping to visualize harboring regions for focal and rotational activities. Atrial cardiomyopathy was classified based on the four Utah stages. RESULTS: Procedural success was achieved in all patients (n = 20, 100%). LGE CMR revealed an intermediate amount of 21.41% ± 6.32% for LA fibrosis. ROIs were identified in all patients (mean no ROIs per patient n = 416.45 ± 204.57). A tendency towards a positive correlation between the total amount of atrial cardiomyopathy and the total number of ROIs per patient (regression coefficient, ß = 10.86, p = .15) was observed. The degree of fibrosis and the presence of ROIs per segment showed no consistent spatial correlation (posterior: ß = 0.36, p-value (p) = .24; anterior: ß = -0.08, p = .54; lateral: ß = 0.31, p = 39; septal: ß = -0.12; p = .66; right PVs: ß = 0.34, p = .27; left PVs: ß = 0.07, p = .79; LAA: ß = -0.91, p = .12). 12 months AF-free survival was 70% (n = 14) after ablation. CONCLUSION: The presence of ROIs from CF mapping was not directly associated with the extent and location of fibrosis. Further studies evaluating the relationship between focal and rotational activity and atrial cardiomyopathy are mandatory.

A novel surgical risk predictor combining frailty and hypoalbuminemia - A cohort study of 9.8m patients from the ACS-NSQIP database.

INTRODUCTION: The functional decline seen in frail patients is associated with significant morbidity and mortality. The modified frailty index 5 (mFI-5) score is an accepted risk predictor score in surgery. Hypoalbuminemia has been correlated with poor postoperative outcomes.There exists, however, a gap in the literature regarding the combined assessment of frailty and hypoalbuminemia and the predictive power of this combined assessment. This retrospective cohort study aimed to investigate the association of preoperative albumin and frailty, as assessed with the mFI-5 score, and its ability to predict surgical outcomes. METHODS: We queried the ACS-NSQIP database (2008-2021) to identify all surgical patients. Perioperative data, including demographics and preoperative laboratory values, including albumin, were collected. The predictive power of the mFI-5 and hypoalbuminemia (Alb) independently, and in combination (mFI-5+Alb), was assessed using multivariable linear and logistic regression models 30-day outcomes were assessed including mortality, length of hospital stay, reoperation, medical and surgical complications, and discharge destination. RESULTS: A total of 9,782,973 patients were identified of whom 4,927,520 (50.4%) were non-frail (mFI=0), 3,266,636 had a frailty score of 1 (33.4%), 1,373,968 a score of 2 (14.0%), 188,821 a score of 3 (1.9%) and 26,006 a score greater or equal to 4 (0.3%). Albumin levels were available for 4,570,473 patients (46.7%), of whom 848,315 (18.6%) had hypoalbuminemia. The combined assessment (mFI-5+Alb) was found to be a more accurate risk predictor than each factor independently for all outcomes. A weak negative correlation between serum albumin levels and mFI scores was established (Spearman R: -0.2; <0.0001). CONCLUSIONS: Combined assessment of frailty and albumin was the strongest risk predictor. Therefore, for patients undergoing surgery, we recommend consideration of both serum albumin and frailty in order to optimally determine perioperative planning, including multi-disciplinary care mobilization and pre- and posthabilitation.

Applications of artificial intelligence/machine learning approaches in cardiovascular medicine: a systematic review with recommendations.

Aims: Artificial intelligence (AI) and machine learning (ML) promise vast advances in medicine. The current state of AI/ML applications in cardiovascular medicine is largely unknown. This systematic review aims to close this gap and provides recommendations for future applications. Methods and results: Pubmed and EMBASE were searched for applied publications using AI/ML approaches in cardiovascular medicine without limitations regarding study design or study population. The PRISMA statement was followed in this review. A total of 215 studies were identified and included in the final analysis. The majority (87%) of methods applied belong to the context of supervised learning. Within this group, tree-based methods were most commonly used, followed by network and regression analyses as well as boosting approaches. Concerning the areas of application, the most common disease context was coronary artery disease followed by heart failure and heart rhythm disorders. Often, different input types such as electronic health records and images were combined in one AI/ML application. Only a minority of publications investigated reproducibility and generalizability or provided a clinical trial registration. Conclusions: A major finding is that methodology may overlap even with similar data. Since we observed marked variation in quality, reporting of the evaluation and transparency of data and methods urgently need to be improved.