Survival Tree Provides Individualized Estimates of Survival After Lung Transplant.

INTRODUCTION: Identifying contributors to lung transplant survival is vital in mitigating mortality. To enhance individualized mortality estimation and determine variable interaction, we employed a survival tree algorithm utilizing recipient and donor data. METHODS: United Network Organ Sharing data (2000-2021) were queried for single and double lung transplants in adult patients. Graft survival time <7 d was excluded. Sixty preoperative and immediate postoperative factors were evaluated with stepwise logistic regression on mortality; final model variables were included in survival tree modeling. Data were split into training and testing sets and additionally validated with 10-fold cross validation. Survival tree pruning and model selection was based on Akaike information criteria and log-likelihood values. Estimated survival probabilities and log-rank pairwise comparisons between subgroups were calculated. RESULTS: A total of 27,296 lung transplant patients (8175 single; 19,121 double lung) were included. Stepwise logistic regression yielded 47 significant variables associated with mortality. Survival tree modeling returned six significant factors: recipient age, length of stay from transplant to discharge, recipient ventilator duration post-transplant, double lung transplant, recipient reintubation post-transplant, and donor cytomegalovirus status. Eight subgroups consisting of combinations of these factors were identified with distinct Kaplan-Meier survival curves. CONCLUSIONS: Survival trees provide the ability to understand the effects and interactions of covariates on survival after lung transplantation. Individualized survival probability with this technique found that preoperative and postoperative factors influence survival after lung transplantation. Thus, preoperative patient counseling should acknowledge a degree of uncertainty given the influence of postoperative factors.

"Interventions to increase adherence to oral therapies in breast cancer patients: A systematic review based on the behavior change technique taxonomy".

OBJECTIVE: High rates of non-adherence to oral medications in breast cancer (BC) patients have been reported. Here we provide an up-to-date systematic review of the interventions aimed at increasing adherence to oral medication in BC patients, with a particular focus on the content of the interventions. METHODS: PubMed, Scopus, Embase and Ovid databases and reference lists of relevant studies were searched through October 2022. Studies which (1) described an intervention aimed at increasing adherence to oral anticancer medication, (2) included (or planned to include) at least one sub-group of BC patients, (3) were written in English, and (4) with full-text available were included. The contents of the interventions were coded using the Behavior Change Technique Taxonomy. Quality assessment was conducted using Downs and Black scale. RESULTS: Thirty-six studies met the inclusion criteria and involved a total sample of 28,528 BC patients. Interventions were mainly delivered with eHealth devices (n = 21) and most of them used mobile app. Other studies used in-person modalities (e.g., CBT, relaxation technique) or written materials (e.g., psycho-educational booklet). The behavior change techniques most frequently implemented were "problem solving," "social support," "information about health consequences," and "prompts/cues". Quality assessment revealed that the higher risk of bias refers to the selection process. CONCLUSIONS: The use of reminders, monitoring patients' medication-taking behaviors and giving feedback were the most frequently implemented techniques in those interventions that resulted significant. If these preliminary observations were to be confirmed by future comparative studies, they should be taken into account when developing new interventions.

A machine learning approach to high-risk cardiac surgery risk scoring.

INTRODUCTION: In patients undergoing high-risk cardiac surgery, the uncertainty of outcome may complicate the decision process to intervene. To augment decision-making, a machine learning approach was used to determine weighted personalized factors contributing to mortality. METHODS: American College of Surgeons National Surgical Quality Improvement Program was queried for cardiac surgery patients with predicted mortality ≥10% between 2012 and 2019. Multiple machine learning models were investigated, with significant predictors ultimately used in gradient boosting machine (GBM) modeling. GBM-trained data were then used for local interpretable model-agnostic explanations (LIME) modeling to provide individual patient-specific mortality prediction. RESULTS: A total of 194 patient deaths among 1291 high-risk cardiac surgeries were included. GBM performance was superior to other model approaches. The top five factors contributing to mortality in LIME modeling were preoperative dialysis, emergent cases, Hispanic ethnicity, steroid use, and ventilator dependence. LIME results individualized patient factors with model probability and explanation of fit. CONCLUSIONS: The application of machine learning techniques provides individualized predicted mortality and identifies contributing factors in high-risk cardiac surgery. Employment of this modeling to the Society of Thoracic Surgeons database may provide individualized risk factors contributing to mortality.

The Application of a Hospital Medical Surge Preparedness Index to Assess National Pandemic and Other Mass Casualty Readiness.

EXECUTIVE SUMMARY: This article describes the use and findings of the Hospital Medical Surge Preparedness Index (HMSPI) tool to improve the understanding of hospitals' ability to respond to mass casualty events such as the COVID-19 pandemic. For this investigation, data from the U.S. Census Bureau, the Dartmouth Atlas Project, and the 2005 to 2014 annual surveys of the American Hospital Association (AHA) were analyzed. The HMSPI tool uses variables from the AHA survey and the other two sources to allow facility, county, and referral area index calculations. Using the three data sets, the HMSPI also allows for an index calculation for per capita ratios and by political (state or county) boundaries. In this use case, the results demonstrated increases in county and state HMSPI scores through the period of analysis; however, no statistically significant difference was found in HMSPI scores between 2013 and 2014. The HMSPI builds on the limited scientific foundation of medical surge preparedness and could serve as an objective and standardized measure to assess the nation's medical readiness for crises such as the COVID-19 pandemic and other large-scale emergencies such as mass shootings. Future studies are encouraged to refine the score, assess the validity of the HMSPI, and evaluate its relevance in response to future legislative and executive policies that affect preparedness measures.

Recommendations for the Prevention of Bisphosphonate-Related Osteonecrosis of the Jaw: A Systematic Review.

OBJECTIVES: The aim of this study was to assess the quality of and outline the differences among recommendations of published clinical practice guidelines (CPGs) for the management of bisphosphonate-associated osteonecrosis of the jaw. METHODS: We conducted a systematic literature search in PubMed, Cochrane, Embase, Web of Science, and Google web site. We selected CPGs supported by a nongovernmental organization or national institutes, related to bisphosphonate-associated osteonecrosis of the jaw in adults, in English language, and dated from January 2008 onward. The validity of each included CPG was appraised according to 2 validated appraisal tools for CPG that were independently used by 2 reviewers. RESULTS: We identified 724 articles, of which 13 were included based on our eligibility criteria. Most CPGs were of good quality based on the appraisal tools for CPGs used in this study. CONCLUSION: We did not find consensus on all the recommendations of the evaluated CPGs. Thus, each clinical case must be assessed individually, considering the risks and benefits on the proposed dental treatment.

Agreement of olecranon fractures before and after the exposure to four classification systems.

BACKGROUND: Although classification systems of olecranon fractures are important to help choose the best treatment and to predict prognosis, their degree of observer agreement is poorly investigated. The objective of this study was to investigate the intraobserver and interobserver reliability of currently used classification systems for olecranon fractures. Our hypothesis is that the Colton classification presents an acceptable agreement because it is simpler to use; on the other hand, considering the AO classification's complexity, we expect it to reach a lower level of agreement. METHODS: Radiographic images of elbow joint fractures were classified according to Colton, AO, Mayo, and Schatzker classification systems. The raters were 8 orthopedic surgeons split into 2 groups with 4 participants each, one with specialists in upper extremity surgery and the other with orthopedic surgeons without a specific focus on upper extremity surgery. This first procedure was the pretest training, aimed at calibrating participants' judgment. Image classification was conducted after all training was completed. After 30 days from the initial rating session, the test was conducted once again following the exact same procedures. RESULTS: The Colton classification has substantial intraobserver and interobserver agreement for specialists and nonspecialists. The Schatzker classification revealed a fair agreement for both specialists and nonspecialists. A fair concordance was also found for the Mayo classification. The AO classification demonstrated a moderate rate of agreement for specialists, whereas nonspecialists presented slight intraobserver agreement. CONCLUSION: No classification system is widely accepted because it can be affected by interobserver variability, which can raise questions about its use in a research as well as in a clinical context.

Perceptions about female urinary incontinence: a systematic review.

INTRODUCTION AND HYPOTHESIS: Perceptions about urinary incontinence (UI) may have a differential impact on treatment-seeking behaviors. Thus, we aimed to systematically review perceptions regarding UI in women of different racial and ethnic populations. METHODS: MEDLINE, EMBASE, Scirus, Google Scholar, Open J-Gate, AgeLine, and Global Health (CABI) were searched from January 1980 to August 2011. We included qualitative studies that described knowledge, perception, or personal views about UI in women. Studies were excluded if they did not specify race/ethnicity of subjects, if they reported on non-UI urinary symptoms, or if they were performed exclusively in men. Three independent reviewers screened all studies. The relevance, appropriateness, transparency, and soundness (RATS) scale for qualitative research was used to assess study quality. Because of the qualitative data, meta-analyses were not performed. RESULTS: Of 3,676 citations, 23 studies met the inclusion criteria. Based on the RATS scale, these were categorized into 11 high-, 2 moderate-, and 10 low-quality studies. Dominant themes fell into two categories, UI management and UI experience, and were similar across racial/ethnic groups. Across multiple studies, women reiterated a preference for discussing UI with other women, even if this was not a physician. Non-white women expressed self-blame and perceived UI as a negative outcome from childbirth or prior sexual experiences. Latina women maintained more secrecy around this issue, even amongst family members. CONCLUSIONS: Women across different racial and ethnic groups share similar UI management strategies and UI experiences. However, perceptions about UI may differ in certain populations. These findings could be useful when considering future educational strategies regarding UI in women.

Systematic review and metasummary of attitudes toward research in emergency medical conditions.

Emergency departments are challenging research settings, where truly informed consent can be difficult to obtain. A deeper understanding of emergency medical patients' opinions about research is needed. We conducted a systematic review and meta-summary of quantitative and qualitative studies on which values, attitudes, or beliefs of emergent medical research participants influence research participation. We included studies of adults that investigated opinions toward emergency medicine research participation. We excluded studies focused on the association between demographics or consent document features and participation and those focused on non-emergency research. In August 2011, we searched the following databases: MEDLINE, EMBASE, Google Scholar, Scirus, PsycINFO, AgeLine and Global Health. Titles, abstracts and then full manuscripts were independently evaluated by two reviewers. Disagreements were resolved by consensus and adjudicated by a third author. Studies were evaluated for bias using standardised scores. We report themes associated with participation or refusal. Our initial search produced over 1800 articles. A total of 44 articles were extracted for full-manuscript analysis, and 14 were retained based on our eligibility criteria. Among factors favouring participation, altruism and personal health benefit had the highest frequency. Mistrust of researchers, feeling like a 'guinea pig' and risk were leading factors favouring refusal. Many studies noted limitations of informed consent processes in emergent conditions. We conclude that highlighting the benefits to the participant and society, mitigating risk and increasing public trust may increase research participation in emergency medical research. New methods for conducting informed consent in such studies are needed.

Use of lung allografts from brain-dead donors after cardiopulmonary arrest and resuscitation.

RATIONALE: Patients who progress to brain death after resuscitation from cardiac arrest have been hypothesized to represent an underused source of potential organ donors; however, there is a paucity of data regarding the viability of lung allografts after a period of cardiac arrest in the donor. OBJECTIVES: To analyze postoperative complications and survival after lung transplant from brain-dead donors resuscitated after cardiac arrest. METHODS: The United Network for Organ Sharing database records donors with cardiac arrest occurring after brain death. Adult recipients of lung allografts from these arrest/resuscitation donors between 2005 and 2011 were compared with nonarrest donors. Propensity score matching was used to reduce the effect of confounding. Postoperative complications and overall survival were assessed using McNemar's test for correlated binary proportions and Kaplan-Meier methods. MEASUREMENTS AND MAIN RESULTS: A total of 479 lung transplant recipients from arrest/resuscitation donors were 1:1 propensity matched from a cohort of 9,076 control subjects. Baseline characteristics in the 1:1-matched cohort were balanced. There was no significant difference in perioperative mortality, airway dehiscence, dialysis requirement, postoperative length of stay (P ≥ 0.38 for all), or overall survival (P = 0.52). A subanalysis of the donor arrest group demonstrated similar survival when stratified by resuscitation time quartile (P = 0.38). CONCLUSIONS: There is no evidence of inferior outcomes after lung transplant from brain-dead donors who have had a period of cardiac arrest provided that good lung function is preserved and the donor is otherwise deemed acceptable for transplantation. Potential expansion of the donor pool to include cardiac arrest as the cause of brain death requires further study.

Clinical Applications of Machine Learning.

Objective: This review introduces interpretable predictive machine learning approaches, natural language processing, image recognition, and reinforcement learning methodologies to familiarize end users. Background: As machine learning, artificial intelligence, and generative artificial intelligence become increasingly utilized in clinical medicine, it is imperative that end users understand the underlying methodologies. Methods: This review describes publicly available datasets that can be used with interpretable predictive approaches, natural language processing, image recognition, and reinforcement learning models, outlines result interpretation, and provides references for in-depth information about each analytical framework. Results: This review introduces interpretable predictive machine learning models, natural language processing, image recognition, and reinforcement learning methodologies. Conclusions: Interpretable predictive machine learning models, natural language processing, image recognition, and reinforcement learning are core machine learning methodologies that underlie many of the artificial intelligence methodologies that will drive the future of clinical medicine and surgery. End users must be well versed in the strengths and weaknesses of these tools as they are applied to patient care now and in the future.

OnetoMap Meta-Data: Healthcare Analytics Through Research.

INTRODUCTION: Big Data has revolutionized healthcare research through the three Vs: volume, veracity, and variety. This study introduces the OnetoMap meta-data repository, a centralized inventory developed in collaboration with the University of South Florida's Department of Surgery. METHODS: The repository offers extensive details about each database, including its primary purpose, available variables, and examples of high-impact research utilizing these databases. It aims to create a centralized inventory, enabling researchers to locate and link relevant datasets efficiently. Each dataset is described using standardized criteria to ensure clarity and usability, such as data type, source, collection methods, and potential linkages to other datasets.  Results: Currently, the OnetoMap repository contains descriptions of 49 datasets, with ongoing updates to include new datasets and additional data years. These datasets include a range of data types, including cross-sectional and longitudinal, gathered through claims, registries, electronic health records, and surveys. The repository is hosted on GitHub, enabling version control, collaboration, and open access. Effective search functionalities and descriptive categorization enhance the findability of datasets. DISCUSSION: The data repository includes comprehensive records of patient health statuses, socioeconomic profiles, hospital structures, and physician practices, enabling nuanced interventions and addressing complex healthcare needs. It also promotes interdisciplinary research and accelerates novel discoveries by providing a centralized source of diverse data and facilitating collaboration among research teams. CONCLUSION: The OnetoMap meta-data repository represents a significant advancement in healthcare research by providing a centralized, detailed, and easily accessible repository of clinical research databases. Future directions include implementing automatic annual updates of datasets, exploring automatic dataset linkage, providing monthly updates on published research, creating a user chat space for enhanced collaboration, and developing code applets for simplified data analysis. These efforts will ensure that the repository remains current, functional, and accessible, ultimately facilitating new discoveries and insights in healthcare outcomes research.

Is nonoperative management of appendicitis inferior in the COVID-19 era?

BACKGROUND: Previous studies on nonoperative management (NOM) of acute appendicitis (AA) indicated comparable outcomes to surgery, but the effect of COVID-19 infection on appendicitis outcomes remains unknown. Thus, we evaluate appendicitis outcomes during the COVID-19 pandemic to determine the effect of COVID-19 infection status and treatment modality. We hypothesized that active COVID-19 patients would have worse outcomes than COVID-negative patients, but that outcomes would not differ between recovered COVID-19 and COVID-negative patients. Moreover, we hypothesized that outcomes would not differ between nonoperative and operative management groups, regardless of COVID-19 status. METHODS: We queried the National COVID Cohort Collaborative from 2020 to 2023 to identify adults with AA who underwent operative or NOM. COVID-19 status was denoted as follows: COVID-negative, COVID-active, or COVID-recovered. Intention to treat was used for NOM. Propensity score-balanced analysis was performed to compare outcomes within COVID groups, as well as within treatment modalities. RESULTS: A total of 37,868 patients were included: 34,866 COVID-negative, 2,540 COVID-active, and 460 COVID-recovered. COVID-active and recovered less often underwent operative management. Unadjusted, there was no difference in mortality between COVID groups for operative management. There was no difference in rate of failure of NOM between COVID groups. Adjusted analysis indicated, compared with operative, NOM carried higher odds of mortality and readmission for COVID-negative and COVID-active patients. CONCLUSION: This study demonstrates higher odds of mortality among NOM of appendicitis and near equivalent outcomes for operative management regardless of COVID-19 status. We conclude that NOM of appendicitis is associated with worse outcomes for COVID-active and COVID-negative patients. In addition, we conclude that a positive COVID test or recent COVID-19 illness alone should not preclude a patient from appendectomy for AA. Surgeon clinical judgment of a patient's physiology and surgical risk should, of course, inform the decision to proceed to the operating room. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level III.

Artificial Intelligence in Surgical Research: Accomplishments and Future Directions.

MINI-ABSTRACT: The study introduces various methods of performing conventional ML and their implementation in surgical areas, and the need to move beyond these traditional approaches given the advent of big data. OBJECTIVE: Investigate current understanding and future directions of machine learning applications, such as risk stratification, clinical data analytics, and decision support, in surgical practice. SUMMARY BACKGROUND DATA: The advent of the electronic health record, near unlimited computing, and open-source computational packages have created an environment for applying artificial intelligence, machine learning, and predictive analytic techniques to healthcare. The "hype" phase has passed, and algorithmic approaches are being developed for surgery patients through all stages of care, involving preoperative, intraoperative, and postoperative components. Surgeons must understand and critically evaluate the strengths and weaknesses of these methodologies. METHODS: The current body of AI literature was reviewed, emphasizing on contemporary approaches important in the surgical realm. RESULTS AND CONCLUSIONS: The unrealized impacts of AI on clinical surgery and its subspecialties are immense. As this technology continues to pervade surgical literature and clinical applications, knowledge of its inner workings and shortcomings is paramount in determining its appropriate implementation.

Expanded analysis for patients with acute cholecystitis indicates outcomes vary based on COVID-19 status and treatment modality.

BACKGROUND: The impact of different phases of COVID-19 infection on outcomes from acute calculous cholecystitis (ACC) is not well understood. Therefore, we examined outcomes of acute cholecystitis during the COVID-19 pandemic, comparing the effect of different treatment modalities and COVID-19 infection status. We hypothesized that patients with acute COVID-19 would have worse outcomes than COVID-negative patients, but there would be no difference between COVID-negative and COVID-recovered patients. METHODS: We used 2020-2023 National COVID Cohort Collaborative data to identify adults with ACC. Treatment (antibiotics-only, cholecystostomy tube, or cholecystectomy) and COVID-19 status (negative, active, or recovered) were collected. Treatment failure of nonoperative managements was noted. Adjusted analysis using a series of generalized linear models controlled for confounders (age, sex, body mass index, Charlson comorbidity index, severity at presentation, and year) to better assess differences in outcomes among treatment groups, as well as between COVID-19 groups. RESULTS: In total, 32,433 patients (skewed count) were included: 29,749 COVID-negative, 2112 COVID-active, and 572 (skewed count) COVID-recovered. COVID-active had higher rates of sepsis at presentation. COVID-negative more often underwent cholecystectomy. Unadjusted, COVID-active had higher 30-day mortality, 30-day complication, and longer length of stay than COVID-negative and COVID-recovered. Adjusted analysis revealed cholecystectomy carried lower odds of mortality for COVID-active and COVID-negative patients than antibiotics or cholecystostomy. COVID-recovered patients' mortality was unaffected by treatment modality. Treatment failure from antibiotics was more common for COVID-negative patients. CONCLUSION: Acute cholecystitis outcomes are affected by phase of COVID-19 infection and treatment modality. Cholecystectomy does not lead to worse outcomes for COVID-active and COVID-recovered patients than nonoperative treatments; thus, these patients can be considered for cholecystectomy if their physiology is not prohibitive.

Addressing disparities in European cancer outcomes: a qualitative study Protocol of the BEACON project.

Introduction: Health disparities represent a crucial factor in cancer survival rates, awareness, quality of life, and mental health of people receiving a cancer diagnosis and their families. Income, education, geographic location, and ethnicity are some of the most important underlying reasons for health disparities in cancer across Europe. Costs of healthcare, access to information, psycho-oncological support options, integration of cancer research and innovative care, and multidisciplinary cancer teams are the main target areas when it comes to addressing disparities in the cancer context. As part of the Beacon Project (BEACON), we developed a protocol for a qualitative study to explore and identify any relevant reasons for cancer inequalities and disparities in Europe. Methods: Our four stakeholders namely, cancer patients, healthcare providers, researchers, and policymakers will be recruited online, facilitated by collaborative efforts with cancer organizations from various European countries, including but not limited to Italy, Croatia, Estonia, and Slovenia. Qualitative online focus group discussions for each stakeholder will be conducted and transcribed. Subsequently, thematic analysis will be used to identify reasons and aspects that may contribute to the existing disparities in cancer outcomes at various levels of engagement and from different stakeholders' perspectives. Results from focus groups will inform a subsequent Delphi study and a SWOT analysis methodology. Discussion: Although advances in medical research, cancer screening and treatment options are constantly progressing, disparities in access to and awareness of healthcare in cancer patients are even more noticeable. Thus, mapping the capacity and capability of cancer centres in the European Union, creating decision support tools that will assist the four stakeholders' information needs and improving the quality of European cancer centres will be the main objectives of the BEACON project. The current protocol will outline the methodological and practical procedures to conduct online focus group discussions with different stakeholders.

Correction: A Machine Learning Model to Predict Patients' Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial.

[This corrects the article DOI: 10.2196/48852.].

Collaborating with cancer patients and informal caregivers in a European study on quality of life: protocol to embed patient and public involvement within the EUonQoL project.

BACKGROUND: Patient and public involvement (PPI) has become an essential part of health research. There is a need for genuine involvement in order to ensure that research is relevant to patients. This can then improve the quality, relevance, and impact of health research, while at the same time reducing wasted research and in doing so bringing science and society closer together. Despite the increasing attention for this involvement, it is not yet common practice to report on proposed activities. An article reporting planned PPI could provide guidance and inspiration for the wider academic community in future activities. Therefore, this current article aims to describe the way in which PPI principles are incorporated in the research project called "Quality of Life in Oncology: measuring what matters for cancer patients and survivors in Europe (EUonQoL)." This project aims to develop a new set of questionnaires to enable cancer patients to assess their quality of life, entitled the EUonQoL-Kit. METHODS: The first step is to recruit cancer patients and their informal caregivers as co-researchers in order to train them to collaborate with the researchers. Based on their skills and preferences, they are then assigned to several of the project's work packages. Their individual roles, tasks, and responsibilities regarding the work packages, to which they have been assigned, are evaluated and adapted when necessary. The impact of their involvement is evaluated by both the researchers and co-researchers. DISCUSSION: PPI is a complex and dynamic process. As such, the overall structure of the research may be defined while at the same time leaving room for certain aspects to be filled in later. Our research is, we believe, relevant as co-researcher involvement in such a large European project as EUonQoL is a new development.

High risks for adverse outcomes after gastric bypass surgery following failed gastric banding: a population-based trend analysis of the United States.

OBJECTIVES: The objectives of this investigation were to (1) compare short-term outcomes for patients undergoing primary gastric bypass surgery with those who had gastric bypass procedures performed as a rescue procedure after failed gastric banding and (2) study trends in the frequency of reoperations between 2005 and 2008 for patients who had prior gastric banding. BACKGROUND: The use of gastric banding to treat obesity has increased drastically in the United States. However, the frequency of reoperations related to gastric banding and associated short-term outcomes are unknown. METHODS: The Nationwide Inpatient Sample from 2005 to 2008 was used for this population-based study. Descriptive statistics as well as unadjusted and risk-adjusted generalized linear models were performed to assess adverse short-term outcomes. RESULTS: A total of 66,303 patients were included in the analysis, 63,171 (95.3%) underwent a primary gastric bypass procedure and 3132 patients (4.7%) underwent a gastric band-related reoperation. Patients undergoing a gastric bypass procedure concomitant with a band-related reoperation had more intraoperative complications [risk-adjusted odds ratio (OR): 2.3, P = 0.002] and postoperative complications (risk-adjusted OR: 8.0, P < 0.001), were at higher risk of reoperations/reinterventions (risk-adjusted OR: 6.0, P < 0.001), increased length of hospital stay (adjusted mean difference: 0.89 days, P < 0.001), and higher hospital charges (adjusted mean difference: $13,257, P < 0.001). The number of gastric band-related reoperations increased from 579 in 2005 to 1132 in 2008 (196%). CONCLUSIONS: The number of reoperations after gastric banding is rapidly increasing in the United States. To our knowledge, this is the first population-based study providing strong evidence that patients undergoing gastric bypass procedure after failed gastric banding have more adverse outcomes than those undergoing gastric bypass alone. The broad indication for gastric banding should be reaffirmed for the US population.

A systematic review of the psychometric properties of self-reported scales assessing burn contractures reveals the need for a new tool to measure contracture outcomes.

Approximately 40% of burn patients develop scar contractures. It is unknown which scar contracture therapy best optimizes activities of daily living (ADL).The appropriateness of self-reported outcome tools in measuring anti-scar contracture therapies has not been assessed. We conducted a systematic review to determine the quality of existing self-reported scales in measuring ADL among burn patients by analyzing and comparing psychometric properties-factor analysis, validity, reliability, and responsiveness. EMBASE, LILACS, American Psychological Association PsycNET databases were searched for relevant articles. Forty-one articles discussing 10 burn and non-burn-specific scales met eligibility criteria of ADL assessment, and available psychometric analyses. A common strength in most scales was good overall reliability. Common weaknesses were insufficient data on factor analyses, content validity specific to ADL assessment, and responsiveness. The psychometric analyses studies on these scales had poor sample variability. There is insufficient data on the dimensionality and responsiveness of existing scales to support their use for measuring ADL in burn patients. Existing scales do not comprehensively measure ADLs as an isolated parameter. A psychometrically valid, comprehensive self-reported burn contracture scale that measures ADLs among a diverse group of burn patients needs to be developed to optimize burn contracture treatments and develop new therapies.

Quality of life and functional capacity after long-term right ventricular pacing in pediatrics and young adults with congenital atrioventricular block.

BACKGROUND: Although several studies have demonstrated deleterious consequences of chronic right ventricular (RV) pacing on ventricular function and synchronicity, its effects on health-related quality of life (HRQoL) and functional exercise capacity remain uncertain. We aimed to evaluate the effect of RV pacing on HRQoL and functional capacity of children and young adults with congenital complete atrioventricular block (CCAVB). METHODS: We included 66 consecutive subjects with RV cardiac pacemaker due to CCAVB and under clinical follow-up for more than 1 year. Multidimensional HRQoL scores were evaluated by Short Form-36 Health Survey (SF-36) and Child Health Questionnaire-Parent Form 50 (CHQ-PF50). Functional capacity was tested by a 6-minute walk distance test (6MWDT). Association analysis was performed to examine if any demographic and clinical characteristics were associated with lower HRQoL scores and shorter distances at the 6MWDT. RESULTS: Domains presenting lower HRQoL scores were vitality (64.0 ± 17.3), mental health (67.3 ± 8.0), role emotional (69.7 ± 35.8) in the SF-36 questionnaire; general health perceptions (61.3 ± 8.3), general behavior (61.9 ± 15.6), parental impact-emotional (67.7 ± 28.7) in the CHQ-PF50. Female gender (P = 0.009), left ventricular ejection fraction lower than 55% (P = 0.013), cardiovascular drugs (P = 0.003) were significantly associated with lower HRQoL scores. Average distance traveled during the 6MWDT was 539.8 ± 82.9 m. The 6MWDT showed significant association with age (P = 0.006) and cardiovascular drugs (P = 0.024). CONCLUSIONS: Chronic RV pacing did not affect the HRQoL and physical capacity of pediatrics and young subjects. Female gender, ventricular function, and cardiovascular drugs were associated with lower HRQoL scores. Older subjects walked shorter distances in the 6MWDT, as well as subjects who were taking cardiovascular drugs.