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.

On the role of benchmarking data sets and simulations in method comparison studies.

Method comparisons are essential to provide recommendations and guidance for applied researchers, who often have to choose from a plethora of available approaches. While many comparisons exist in the literature, these are often not neutral but favor a novel method. Apart from the choice of design and a proper reporting of the findings, there are different approaches concerning the underlying data for such method comparison studies. Most manuscripts on statistical methodology rely on simulation studies and provide a single real-world data set as an example to motivate and illustrate the methodology investigated. In the context of supervised learning, in contrast, methods are often evaluated using so-called benchmarking data sets, that is, real-world data that serve as gold standard in the community. Simulation studies, on the other hand, are much less common in this context. The aim of this paper is to investigate differences and similarities between these approaches, to discuss their advantages and disadvantages, and ultimately to develop new approaches to the evaluation of methods picking the best of both worlds. To this aim, we borrow ideas from different contexts such as mixed methods research and Clinical Scenario Evaluation.

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.

Comparing linear discriminant analysis and supervised learning algorithms for binary classification-A method comparison study.

In psychology, linear discriminant analysis (LDA) is the method of choice for two-group classification tasks based on questionnaire data. In this study, we present a comparison of LDA with several supervised learning algorithms. In particular, we examine to what extent the predictive performance of LDA relies on the multivariate normality assumption. As nonparametric alternatives, the linear support vector machine (SVM), classification and regression tree (CART), random forest (RF), probabilistic neural network (PNN), and the ensemble k conditional nearest neighbor (EkCNN) algorithms are applied. Predictive performance is determined using measures of overall performance, discrimination, and calibration, and is compared in two reference data sets as well as in a simulation study. The reference data are Likert-type data, and comprise 5 and 10 predictor variables, respectively. Simulations are based on the reference data and are done for a balanced and an unbalanced scenario in each case. In order to compare the algorithms' performance, data are simulated from multivariate distributions with differing degrees of nonnormality. Results differ depending on the specific performance measure. The main finding is that LDA is always outperformed by RF in the bimodal data with respect to overall performance. Discriminative ability of the RF algorithm is often higher compared to LDA, but its model calibration is usually worse. Still LDA mostly ranges second in cases it is outperformed by another algorithm, or the differences are only marginal. In consequence, we still recommend LDA for this type of application.

NK cell-intrinsic FcεRIγ limits CD8+ T-cell expansion and thereby turns an acute into a chronic viral infection.

During viral infection, tight regulation of CD8+ T-cell functions determines the outcome of the disease. Recently, others and we determined that the natural killer (NK) cells kill hyperproliferative CD8+ T cells in the context of viral infection, but molecules that are involved in shaping the regulatory capability of NK cells remain virtually unknown. Here we used mice lacking the Fc-receptor common gamma chain (FcRγ, FcεRIγ, Fcer1g-/- mice) to determine the role of Fc-receptor and NK-receptor signaling in the process of CD8+ T-cell regulation. We found that the lack of FcRγ on NK cells limits their ability to restrain virus-specific CD8+ T cells and that the lack of FcRγ in Fcer1g-/- mice leads to enhanced CD8+ T-cell responses and rapid control of the chronic docile strain of the lymphocytic choriomeningitis virus (LCMV). Mechanistically, FcRγ stabilized the expression of NKp46 but not that of other killer cell-activating receptors on NK cells. Although FcRγ did not influence the development or activation of NK cell during LCMV infection, it specifically limited their ability to modulate CD8+ T-cell functions. In conclusion, we determined that FcRγ plays an important role in regulating CD8+ T-cell functions during chronic LCMV infection.

Electrode-Free Concentration and Recovery of DNA at Physiologically Relevant Ionic Concentrations.

Advances in microanalytical and microfluidic technologies have enabled rapid and amplification-free detection of DNA with a high signal-to-noise ratio. The low sample volume, however, poses a limit in the DNA detection sensitivity, which can be challenging for analyzing rare DNA in physiological samples. One way to improve the sensitivity is to concentrate the DNA in the sample prior to the analysis. The most common DNA concentration techniques are based on electrokinetics, which require an external electric field and generally become ineffective in high ionic concentration conditions. In this work, we present a facile method termed high-salt molecular rheotaxis (HiSMRT) to concentrate and recover DNA from samples with physiologically relevant ionic concentrations without any external electric field. HiSMRT requires only pressure-driven flow and ion concentration gradient to induce a stable local electric field and achieve DNA concentration, making it impervious to high ionic concentrations. We demonstrate that HiSMRT performs robustly at ionic concentrations equivalent to 2%-20% of the ionic concentration in blood serum. HiSMRT can concentrate DNA by up to 960-fold and recover an average of 96.4% of the DNA fragments from 2.0 to 23 kbp uniformly. The concentration process using HiSMRT takes as little as 7.5 min. Moreover, we show that this technique can be easily integrated to perform DNA concentration, size separation, and single-molecule detection all in one platform. We anticipate that this technique will be applicable to a wide range of biological samples and will help to improve the sensitivity of nucleic acid detection for low-abundance DNA biomarkers.

Versatile Analysis of DNA-Biomolecule Interactions in Solution by Hydrodynamic Separation and Single Molecule Detection.

DNA can interact with a wide array of molecules with a range of binding affinities, stoichiometry, and size-scales. We present a sensitive, quantitative, and versatile platform for sensing and evaluating these diverse DNA-biomolecule interactions and DNA conformational changes in free solution. Single molecule free solution hydrodynamic separation utilizes differences in hydrodynamic mobility to separate bound DNA-biomolecule complexes from unbound DNA and determine the associated size change that results from binding. Single molecule detection enables highly quantitative analysis of the fraction of DNA in the bound and unbound state to characterize binding behavior including affinity, stoichiometry, and cooperativity. A stacked injection scheme increases throughput to enable practical analysis of DNA-biomolecule interactions using only picoliters of sample per measurement. To demonstrate analysis of DNA-protein interactions on a local scale, we investigate binding of the E. coli single stranded binding protein to two DNA oligos both individually and in direct competition. We show that stoichiometry and cooperativity is a function of DNA length and verify these differences in binding characteristics through direct competition. To demonstrate analysis of DNA-small molecule interactions and global conformational changes, we also assess DNA condensation with the polyamine spermidine. We use hydrodynamic mobility to evaluate the size of spermidine-condensed DNA and single molecule burst analysis to evaluate DNA packing within the condensed globules relative to free-coiled DNA. This platform thus presents a versatile tool capable of quantitative and sensitive evaluation of diverse biomolecular interactions, complex properties, and binding characteristics.

Risk factors for surgical intervention of early medical abortion.

BACKGROUND: By being noninvasive, medical termination of pregnancy has increased worldwide access to abortion and improved safety of unsafe abortion. However, secondary surgical intervention is the most frequent complication to medical abortion. OBJECTIVE: We aimed to identify and quantify risk factors for surgical intervention in women undergoing medically induced termination of pregnancy before 9 completed weeks of gestation. STUDY DESIGN: We conducted a nationwide cohort study, including all pregnancies terminated before 63 gestational days in women aged 15-49 years during the period 2005-2015. Induction regimen was 200 mg mifepristone followed 24-48 hours later by 0.8 mg vaginal misoprostol. All included pregnancies were followed up for 8 weeks from mifepristone administration. Data were retrieved from national health registers. Multiple logistic regression provided adjusted odds ratios of surgical intervention with 95% confidence intervals. The discriminative ability of the risk factors in identifying surgical intervention was assessed by cross-validated area under the receiver operating characteristic curve. RESULTS: Of 86,437 early medical abortions, 5320 (6.2%) underwent a surgical intervention within 8 weeks after induction. The proportion of surgical interventions increased from 3.5% in the 5th to 6th gestational week to 10.3% in week 9, odds ratio, 3.2 (95% confidence interval, 2.9-3.6). Compared with women aged 15-19 years, the risk of surgical intervention increased with increasing maternal age until the age of 30-34 years, odds ratio, 1.7 (95% confidence interval, 1.5-1.9), where after the risk decreased to an odds ratio for age group 40-49 of 1.2 (95% confidence interval, 1.0-1.4). Compared with nulliparous women, a history of only vaginal deliveries with spontaneous delivery of placenta implied an odds ratio of 1.1 (95% confidence interval, 1.0-1.2), women with a history of at least 1 cesarean delivery, an odds ratio of 1.5 (95% confidence interval, 1.3-1.6), and women having experienced a manual removal of placenta after a vaginal birth, an odds ratio of 2.0 (95% confidence interval, 1.7-2.4). Previous medically induced abortion decreased the risk of surgical intervention, odds ratio 0.84 (95% confidence interval, 0.78-0.91), whereas previous early (before 56 days of gestation) surgically induced abortion implied a 53% (95% confidence interval, 1.4-1.7) increased risk of surgical intervention. Previous surgical abortion after 55 days of gestation increased the risk by 17% (95% confidence interval, 1.1-1.3). The area under the receiver operating characteristic curve of the model including all quantified risk factors was 63% (95% confidence interval, 62-64%). CONCLUSION: Gestational age, maternal age, previous deliveries, and history of medically and surgically induced abortions all had a significant influence on the risk of surgical intervention of early medical abortion. However, inclusion of all quantified risk factors still left most interventions unpredictable.

Sphingolipids in early viral replication and innate immune activation.

In this review, we summarize the mechanisms by which sphingolipids modulate virus multiplication and the host innate immune response, using a number of host-virus systems as illustrative models. Sphingolipids exert diverse functions, both at the level of the viral life cycle and in the regulation of antiviral immune responses. Sphingolipids may influence viral replication in three ways: by serving as (co)receptors during viral entry, by modulating virus replication, and by shaping the antiviral immune response. Several studies have demonstrated that sphingosine kinases (SphK) and their product, sphingosine-1-phosphate (S1P), enhance the replication of influenza, measles, and hepatitis B virus (HBV). In contrast, ceramides, particularly S1P and SphK1, influence the expression of type I interferon (IFN-I) by modulating upstream antiviral signaling and enhancing dendritic cell maturation, differentiation, and positioning in tissue. The synthetic molecule α-galactosylceramide has also been shown to stimulate natural killer cell activation and interferon (IFN)-γ secretion. However, to date, clinical trials have failed to demonstrate any clinical benefit for sphingolipids in the treatment of cancer or HBV infection. Taken together, these findings show that sphingolipids play an important and underappreciated role in the control of virus replication and the innate immune response.

Testing Mean Differences among Groups: Multivariate and Repeated Measures Analysis with Minimal Assumptions.

To date, there is a lack of satisfactory inferential techniques for the analysis of multivariate data in factorial designs, when only minimal assumptions on the data can be made. Presently available methods are limited to very particular study designs or assume either multivariate normality or equal covariance matrices across groups, or they do not allow for an assessment of the interaction effects across within-subjects and between-subjects variables. We propose and methodologically validate a parametric bootstrap approach that does not suffer from any of the above limitations, and thus provides a rather general and comprehensive methodological route to inference for multivariate and repeated measures data. As an example application, we consider data from two different Alzheimer's disease (AD) examination modalities that may be used for precise and early diagnosis, namely, single-photon emission computed tomography (SPECT) and electroencephalogram (EEG). These data violate the assumptions of classical multivariate methods, and indeed classical methods would not have yielded the same conclusions with regards to some of the factors involved.

Single Molecule Hydrodynamic Separation Allows Sensitive and Quantitative Analysis of DNA Conformation and Binding Interactions in Free Solution.

Limited tools exist that are capable of monitoring nucleic acid conformations, fluctuations, and distributions in free solution environments. Single molecule free solution hydrodynamic separation enables the unique ability to quantitatively analyze nucleic acid biophysics in free solution. Single molecule fluorescent burst data and separation chromatograms can give layered insight into global DNA conformation, binding interactions, and molecular distributions. First, we show that global conformation of individual DNA molecules can be directly visualized by examining single molecule fluorescent burst shapes and that DNA exists in a dynamic equilibrium of fluctuating conformations as it is driven by Poiseuille flow through micron-sized channels. We then show that this dynamic equilibrium of DNA conformations is reflected as shifts in hydrodynamic mobility that can be perturbed using salt and ionic strength to affect packing density. Next, we demonstrate that these shifts in hydrodynamic mobility can be used to investigate hybridization thermodynamics and binding interactions. We distinguish and classify multiple interactions within a single sample, and demonstrate quantification amidst large concentration differences for the detection of rare species. Finally, we demonstrate that these differences can resolve perfect complement, 2 bp mismatched, and 3 bp mismatched sequences. Such a system can be used to garner diverse information about DNA conformation and structure, and potentially be extended to other molecules and mixed-species interactions, such as between nucleic acids and proteins or synthetic polymers.

IL-10 Induces T Cell Exhaustion During Transplantation of Virus Infected Hearts.

BACKGROUND/AIMS: Unexpected transmissions of viral pathogens during solid organ transplantation (SOT) can result in severe, life-threatening diseases in transplant recipients. Immune activation contributes to disease onset. However mechanisms balancing the immune response against transmitted viral infection through organ transplantation remain unknown. Methods & RESULTS: Here we found, using lymphocytic choriomeningitis virus (LCMV), that transplantation of LCMV infected hearts led to exhaustion of virus specific CD8+ T cells, viral persistence in organs and survival of graft and recipient. Genetic depletion of Interleukin-10 (IL-10) resulted in strong immune activation, graft dysfunction and death of mice, suggesting that IL-10 was a major regulator of CD8+ T cell exhaustion during SOT. In the presence of memory CD8+ T cells, virus could be controlled. However sufficient antiviral immune response resulted in acute rejection of transplanted heart. CONCLUSION: We found that virus transmitted via SOT could not be controlled by naïve mice recipients due to IL-10 mediated CD8+ T cell exhaustion which thereby prevented immunopathology and graft failure whereas memory mice recipients were able to control the virus and induced graft failure.

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.

Racial disparities in surgical outcomes after mastectomy in 223 000 female breast cancer patients: a retrospective cohort study.

BACKGROUND: Breast cancer mortality and treatment differ across racial groups. It remains unclear whether such disparities are also reflected in perioperative outcomes of breast cancer patients undergoing mastectomy. STUDY DESIGN: The authors reviewed the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (2008-2021) to identify female patients who underwent mastectomy for oncological purposes. The outcomes were stratified by five racial groups (white, Black/African American, Asian, American Indian/Alaska Native, and Native Hawaiian/Pacific Islander) and included 30-day mortality, reoperation, readmission, surgical and medical complications, and non-home discharge. RESULTS: The study population included 222 947 patients, 68% ( n =151 522) of whom were white, 11% ( n =23 987) Black/African American, 5% ( n =11 217) Asian, 0.5% ( n =1198) American Indian/Alaska Native, and 0.5% ( n =1018) Native Hawaiian/Pacific Islander. While 136 690 (61%) patients underwent partial mastectomy, 54 490 (24%) and 31 767 (14%) women received simple and radical mastectomy, respectively. Overall, adverse events occurred in 17 222 (7.7%) patients, the largest portion of which were surgical complications ( n =7246; 3.3%). Multivariable analysis revealed that being of Asian race was protective against perioperative complications [odds ratio (OR)=0.71; P <0.001], whereas American Indian/Alaska Native women were most vulnerable to the complication occurrence (OR=1.41; P <0.001). Black/African American patients had a significantly lower risk of medical (OR=0.59; P <0.001) and surgical complications (OR=0.60; P <0.001) after partial and radical mastectomy, respectively, their likelihood of readmission (OR=1.14; P =0.045) following partial mastectomy was significantly increased. CONCLUSION: The authors identified American Indian/Alaska Native women as particularly vulnerable to complications following mastectomy. Asian patients experienced the lowest rate of complications in the perioperative period. The authors' analyses revealed comparable confounder-adjusted outcomes following partial and complete mastectomy between Black and white races. Their findings call for care equalization in the field of breast cancer surgery.

Surgical Outcomes and Sociodemographic Disparities Across All Races: An ACS-NSQIP and NHIS Multi-Institutional Analysis of Over 7.5 Million Patients.

Background: This study aims to fill the gap in large-scale, registry-based assessments by examining postoperative outcomes across diverse races/ethnicities. The focus is on identifying disparities and comparing them with socioeconomic demographics. Methods: In a registry-based cohort study using the 2008 to 2020 American College of Surgeons National Surgical Quality Improvement Program, we evaluated 24 postoperative outcomes through multivariable analysis, incorporating 28 preoperative risk factors. In a separate, independent analysis of the 2019 to 2020 National Health Interview Survey (NHIS) database, we examined sociodemographic racial/ethnic normative data. Results: Among 7,504,734 American College of Surgeons National Surgical Improvement Database patients specifying race, 83.8% were White (WT), 11.8% Black or African American (B/AA), 3.3% Asian (AS), 0.7% American Indian or Alaska Native (AI/AN), 0.4% Native Hawaiian or Pacific Islander (NH/PI), 7.3% Hispanic. Reoperation trends reveal favorable outcomes for WT, AS, and NH/PI patients compared with B/AA and AI/AN patients. AI/AN patients exhibit higher rates of wound healing issues, while AS patients experience lower rates. AS and B/AA patients are more prone to transfusions, with B/AA patients showing elevated rates of pulmonary embolism, deep vein thrombosis, renal failure, and insufficiency. Disparities in discharge destinations exist. Hispanic patients fare better than non-WT Hispanic patients, contingent on race. Racial groups (excluding Hispanic patients) with superior surgical outcomes from the NSQIP analysis were found in the NHIS analysis to report higher wealth, better healthcare access, improved food security, greater functional and societal independence, and lower frailty. Conclusions: Our study underscores racial disparities in surgical outcomes. Focused investigations into these complications could reveal underlying causes, informing healthcare policies to enhance surgical care universally.

The significance of timing in breast reconstruction after mastectomy: An ACS-NSQIP analysis.

BACKGROUND: A variety of breast reconstruction (BR) options are available. The significance of timing on outcomes remains debated. This study aims to compare complications in breast cancer patients undergoing implant-based and autologous BR immediately after mastectomy or at a delayed time point. METHODS: We reviewed the ACS-NSQIP database (2008-2021) to identify all female patients who underwent BR for oncological purposes. Outcomes were stratified by technique (implant-based versus autologous) and timing (immediate versus delayed), and included 30-day mortality, reoperation, (unplanned) readmission, and surgical and medical complications. RESULTS: A total of 21,560 patients were included: 11,237 (52%) implant-based (9791/87% immediate, 1446/13% delayed) and 10,323 (48%) autologous (8378/81% immediate, 1945/19% delayed). Complications occurred in 3666 (17%) patients (implant-based: n = 1112/11% immediate, n = 64/4.4% delayed cohorts; Autologous: n = 2073/25% immediate, n = 417/21% delayed cohorts). In propensity score weighting (PSW) analyses, immediate BR was associated with significantly more complications than delayed BR (p < 0.0001). This was the case for both implant-based and autologous BR, with a greater difference between the two time points noted in implant-based. Confounder-adjusted multivariable analyses confirmed these results. CONCLUSION: At the 30-day time point, delayed BR is associated with significantly lower complication rates than immediate BR, in both the implant-based and autologous cohorts. These findings are not a blanket recommendation in favor of immediate and/or delayed BR. Instead, our insights may guide surgeons and patients in decision-making and help refine patients' eligibility in a case-by-case workup.

Physical and Mental Recovery after Aortic Valve Surgery in Non-Elderly Patients: Native Valve-Preserving Surgery vs. Prosthetic Valve Replacement.

Background: Exercise capacity and patient-reported outcomes are increasingly considered crucial following aortic valve (AV) surgery in non-elderly adults. We aimed to prospectively evaluate the effect of native valve preservation compared with prosthetic valve replacement. Methods: From October 2017 to August 2020, 100 consecutive non-elderly patients undergoing surgery for severe AV disease were included. Exercise capacity and patient-reported outcomes were evaluated upon admission, and 3 months and 1 year postoperatively. Results: In total, 72 patients underwent native valve-preserving procedures (AV repair or Ross procedure, NV group), and 28 patients, prosthetic valve replacement (PV group). Native valve preservation was associated with an increased risk of reoperation (weighted hazard ratio: 10.57 (95% CI: 1.24-90.01), p = 0.031). The estimated average treatment effect on six-minute walking distance in NV patients at 1 year was positive, but not significant (35.64 m; 95% CI: -17.03-88.30, adj. p = 0.554). The postoperative physical and mental quality of life was comparable in both groups. Peak oxygen consumption and work rate were better at all assessment time points in NV patients. Marked longitudinal improvements in walking distance (NV, +47 m (adj. p < 0.001); PV, +25 m (adj. p = 0.004)) and physical (NV, +7 points (adj. p = 0.023); PV, +10 points (adj. p = 0.005)) and mental quality of life (NV, +7 points (adj. p < 0.001); PV, +5 points (adj. p = 0.058)) from the preoperative period to the 1-year follow-up were observed. At 1 year, there was a tendency of more NV patients reaching reference values of walking distance. Conclusions: Despite the increased risk of reoperation, physical and mental performance markedly improved after native valve-preserving surgery and was comparable to that after prosthetic aortic valve replacement.

Regularization approaches in clinical biostatistics: A review of methods and their applications.

A range of regularization approaches have been proposed in the data sciences to overcome overfitting, to exploit sparsity or to improve prediction. Using a broad definition of regularization, namely controlling model complexity by adding information in order to solve ill-posed problems or to prevent overfitting, we review a range of approaches within this framework including penalization, early stopping, ensembling and model averaging. Aspects of their practical implementation are discussed including available R-packages and examples are provided. To assess the extent to which these approaches are used in medicine, we conducted a review of three general medical journals. It revealed that regularization approaches are rarely applied in practical clinical applications, with the exception of random effects models. Hence, we suggest a more frequent use of regularization approaches in medical research. In situations where also other approaches work well, the only downside of the regularization approaches is increased complexity in the conduct of the analyses which can pose challenges in terms of computational resources and expertise on the side of the data analyst. In our view, both can and should be overcome by investments in appropriate computing facilities and educational resources.

The surgical patient of yesterday, today, and tomorrow-a time-trend analysis based on a cohort of 8.7 million surgical patients.

BACKGROUND: Global healthcare delivery is challenged by the aging population and the increase in obesity and type 2 diabetes. The extent to which such trends affect the cohort of patients the authors surgically operate on remains to be elucidated. Comprising of 8.7 million surgical patients, the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) database can be analyzed to investigate the echo of general population dynamics and forecast future trends. MATERIAL AND METHODS: The authors reviewed the ACS-NSQIP database (2008-2020) in its entirety, extracting patient age, BMI, and diabetes prevalence. Based on these data, the authors forecasted future trends up to 2030 using a drift model. RESULTS: During the review period, median age increased by 3 years, and median BMI by 0.9 kg/m2. The proportion of patients with overweight, obesity class I, and class II rates increased. The prevalence of diabetes rose between 2008 (14.9%) and 2020 (15.3%). The authors forecast the median age in 2030 to reach 61.5 years and median BMI to climb to 29.8 kg/m2. Concerningly, in 2030, eight of ten surgical patients are projected to have a BMI above normal. Diabetes prevalence is projected to rise to 15.6% over the next decade. CONCLUSION: General population trends echo in the field of surgery, with the surgical cohort aging at an alarmingly rapid rate and increasingly suffering from obesity and diabetes. These trends show no sign of abating without dedicated efforts and call for urgent measures and fundamental re-structuring for improved future surgical care.