Outpatient insulin use in type 2 diabetes mellitus and acute respiratory distress syndrome outcomes: A retrospective cohort study.

BACKGROUND: The impact of type 2 diabetes mellitus (T2DM) on acute respiratory distress syndrome (ARDS) is debatable. T2DM was suspected to reduce the risk and complications of ARDS. However, during coronavirus disease 2019 (COVID-19), T2DM predisposed patients to ARDS, especially those who were on insulin at home. AIM: To evaluate the impact of outpatient insulin use in T2DM patients on non-COVID-19 ARDS outcomes. METHODS: We conducted a retrospective cohort analysis using the Nationwide Inpatient Sample database. Adult patients diagnosed with ARDS were stratified into insulin-dependent diabetes mellitus (DM) (IDDM) and non-insulin-dependent DM (NIDDM) groups. After applying exclusion criteria and matching over 20 variables, we compared cohorts for mortality, duration of mechanical ventilation, incidence of acute kidney injury (AKI), length of stay (LOS), hospitalization costs, and other clinical outcomes. RESULTS: Following 1:1 propensity score matching, the analysis included 274 patients in each group. Notably, no statistically significant differences emerged between the IDDM and NIDDM groups in terms of mortality rates (32.8% vs 31.0%, P = 0.520), median hospital LOS (10 d, P = 0.537), requirement for mechanical ventilation, incidence rates of sepsis, pneumonia or AKI, median total hospitalization costs, or patient disposition upon discharge. CONCLUSION: Compared to alternative anti-diabetic medications, outpatient insulin treatment does not appear to exert an independent influence on in-hospital morbidity or mortality in diabetic patients with non-COVID-19 ARDS.

Automatic Implantable Cardioverter Defibrillator (AICD) Implantation as Secondary Prevention of Cardiac Sarcoidosis-Associated Ventricular Tachycardia.

Background: Cardiac sarcoidosis can cause a wide range of symptoms, including shortness of breath, chest pain, oedema, and fatal arrhythmias such as ventricular tachycardia (VT). Because the symptoms can be nonspecific, diagnosing cardiac sarcoidosis can be challenging. Treatment options may include corticosteroids to reduce inflammation, immunosuppressive drugs to prevent further damage, medications to control symptoms, ablation procedures, and defibrillators to prevent cardiac arrest. Case: A 60-year-old woman who has sarcoidosis affecting multiple organs including cardiac sarcoidosis, non-ischemic cardiomyopathy with reduced ejection fraction, and hypertension, was admitted with tachycardia, shortness of breath, and a recently fired automatic implantable cardioverter defibrillator (AICD). Three months prior, the patient was admitted for a syncopal episode and diagnosed with cardiac sarcoidosis through cardiac magnetic resonance imaging (MRI) and positron emission tomography (PET), which demonstrated active inflammation, and an AICD was implanted. During this admission, the patient had an episode of ventricular tachycardia and was treated with amiodarone and lidocaine. The patient received steroids, sacubitril/valsartan, and methotrexate. After 48 hours of observation, the patient was discharged without further events. Conclusion: Cardiac sarcoidosis is a rare but serious disease that can lead to life-threatening cardiac complications such as ventricular tachycardia. Early diagnosis and aggressive management are crucial for improving outcomes and preventing sudden cardiac death. AICD implantation as a secondary prevention in cardiac sarcoidosis might prevent cardiac arrest." LEARNING POINTS: Cardiac sarcoidosis can present with non-specific symptoms and lead to life-threatening arrhythmias such as ventricular tachycardia, emphasising the importance of early diagnosis and aggressive management to prevent sudden cardiac death.A multidisciplinary approach involving imaging modalities such as cardiac magnetic resonance imaging (MRI) and positron emission tomography (PET) scans, along with histological findings, is crucial for accurately diagnosing cardiac sarcoidosis, as endomyocardial biopsy alone has low sensitivity.Implantation of an automatic implantable cardioverter defibrillator (AICD) as a secondary prevention measure should be considered in cardiac sarcoidosis patients, even in elderly individuals with mildly to moderately reduced ejection fraction, to prevent fatal arrhythmias and sudden cardiac death.

Leveraging home health aides to improve outcomes in heart failure: A pilot study protocol.

Heart failure (HF) affects six million people in the U.S., is associated with high morbidity, mortality, and healthcare utilization.(1, 2) Despite a decade of innovation, the majority of interventions aimed at reducing hospitalization and readmissions in HF have not been successful.(3-7) One reason may be that most have overlooked the role of home health aides and attendants (HHAs), who are often highly involved in HF care.(8-13) Despite their contributions, studies have found that HHAs lack specific HF training and have difficulty reaching their nursing supervisors when they need urgent help with their patients. Here we describe the protocol for a pilot randomized control trial (pRCT) assessing a novel stakeholder-engaged intervention that provides HHAs with a) HF training (enhanced usual care arm) and b) HF training plus a mobile health application that allows them to chat with a nurse in real-time (intervention arm). In collaboration with the VNS Health of New York, NY, we will conduct a single-site parallel arm pRCT with 104 participants (HHAs) to evaluate the feasibility, acceptability, and effectiveness (primary outcomes: HF knowledge; HF caregiving self-efficacy) of the intervention among HHAs caring for HF patients. We hypothesize that educating and better integrating HHAs into the care team can improve their ability to provide support for patients and outcomes for HF patients as well (exploratory outcomes include hospitalization, emergency department visits, and readmission). This study offers a novel and potentially scalable way to leverage the HHA workforce and improve the outcomes of the patients for whom they care. Clinical trial.gov registration: NCT04239911.

LSCS-Net: A lightweight skin cancer segmentation network with densely connected multi-rate atrous convolution.

The rising occurrence and notable public health consequences of skin cancer, especially of the most challenging form known as melanoma, have created an urgent demand for more advanced approaches to disease management. The integration of modern computer vision methods into clinical procedures offers the potential for enhancing the detection of skin cancer . The UNet model has gained prominence as a valuable tool for this objective, continuously evolving to tackle the difficulties associated with the inherent diversity of dermatological images. These challenges stem from diverse medical origins and are further complicated by variations in lighting, patient characteristics, and hair density. In this work, we present an innovative end-to-end trainable network crafted for the segmentation of skin cancer . This network comprises an encoder-decoder architecture, a novel feature extraction block, and a densely connected multi-rate Atrous convolution block. We evaluated the performance of the proposed lightweight skin cancer segmentation network (LSCS-Net) on three widely used benchmark datasets for skin lesion segmentation: ISIC 2016, ISIC 2017, and ISIC 2018. The generalization capabilities of LSCS-Net are testified by the excellent performance on breast cancer and thyroid nodule segmentation datasets. The empirical findings confirm that LSCS-net attains state-of-the-art results, as demonstrated by a significantly elevated Jaccard index.

ECG-based cardiac arrhythmias detection through ensemble learning and fusion of deep spatial-temporal and long-range dependency features.

Cardiac arrhythmia is one of the prime reasons for death globally. Early diagnosis of heart arrhythmia is crucial to provide timely medical treatment. Heart arrhythmias are diagnosed by analyzing the electrocardiogram (ECG) of patients. Manual analysis of ECG is time-consuming and challenging. Hence, effective automated detection of heart arrhythmias is important to produce reliable results. Different deep-learning techniques to detect heart arrhythmias such as Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Transformer, and Hybrid CNN-LSTM were proposed. However, these techniques, when used individually, are not sufficient to effectively learn multiple features from the ECG signal. The fusion of CNN and LSTM overcomes the limitations of CNN in the existing studies as CNN-LSTM hybrids can extract spatiotemporal features. However, LSTMs suffer from long-range dependency issues due to which certain features may be ignored. Hence, to compensate for the drawbacks of the existing models, this paper proposes a more comprehensive feature fusion technique by merging CNN, LSTM, and Transformer models. The fusion of these models facilitates learning spatial, temporal, and long-range dependency features, hence, helping to capture different attributes of the ECG signal. These features are subsequently passed to a majority voting classifier equipped with three traditional base learners. The traditional learners are enriched with deep features instead of handcrafted features. Experiments are performed on the MIT-BIH arrhythmias database and the model performance is compared with that of the state-of-art models. Results reveal that the proposed model performs better than the existing models yielding an accuracy of 99.56%.

GLP-1 receptor agonists: A novel pharmacotherapy for binge eating (Binge eating disorder and bulimia nervosa)? A systematic review.

Objective: Systematically review evidence on using GLP-1RAs for reducing BEB in BED and BN. Methods: Comprehensive literature search (PubMed and Google Scholar) conducted for studies evaluating GLP-1Ras for BEB. Extracted data on study characteristics, efficacy, and safety. Results: Studies show that GLP-1RAs (liraglutide and dulaglutide) reduce BE frequency and comorbidities in addition to favorable psychiatric side effect profile compared to current options. However, large-scale, blinded placebo-controlled trials are lacking. Conclusion: Early findings suggest promising effects of GLP-1RAs on BEB. However, rigorous clinical trials are needed to firmly establish efficacy, dosing, safety, and comparative effectiveness before considering GLP-1RAs a viable novel approach.

Antisenescence Therapy Improves Function in a Human Model of Cardiac Fibrosis-on-a-Chip.

Cardiac fibrosis is a significant contributor to heart failure and is characterized by abnormal ECM deposition and impaired contractile function. We have previously developed a model of cardiac fibrosis via TGF-ß treatment of engineered microtissues using heart-on-a-chip technology which incorporates human induced pluripotent stem cell-derived cardiomyocytes and cardiac fibroblasts. Here, we describe that these cardiac fibrotic tissues expressed markers associated with cellular senescence via transcriptomic analysis. Treatment of fibrotic tissues with the senolytic drugs dasatinib and quercetin (D+Q) led to an improvement of contractile function, reduced passive tension, and downregulated senescence-related gene expression, an outcome we were previously unable to achieve using standard-of-care drugs. The improvement in functional parameters was also associated with a reduction in fibroblast density, though no changes in absolute collagen deposition were observed. This study demonstrates the benefit of senolytic treatment for cardiac fibrosis in a human-relevant model, supporting data in animal models, and will enable the further elucidation of cell-specific effects of senolytics and how they impact cardiac fibrosis and senescence.

Deep learning for ECG Arrhythmia detection and classification: an overview of progress for period 2017-2023.

Cardiovascular diseases are a leading cause of mortality globally. Electrocardiography (ECG) still represents the benchmark approach for identifying cardiac irregularities. Automatic detection of abnormalities from the ECG can aid in the early detection, diagnosis, and prevention of cardiovascular diseases. Deep Learning (DL) architectures have been successfully employed for arrhythmia detection and classification and offered superior performance to traditional shallow Machine Learning (ML) approaches. This survey categorizes and compares the DL architectures used in ECG arrhythmia detection from 2017-2023 that have exhibited superior performance. Different DL models such as Convolutional Neural Networks (CNNs), Multilayer Perceptrons (MLPs), Transformers, and Recurrent Neural Networks (RNNs) are reviewed, and a summary of their effectiveness is provided. This survey provides a comprehensive roadmap to expedite the acclimation process for emerging researchers willing to develop efficient algorithms for detecting ECG anomalies using DL models. Our tailored guidelines bridge the knowledge gap allowing newcomers to align smoothly with the prevailing research trends in ECG arrhythmia detection. We shed light on potential areas for future research and refinement in model development and optimization, intending to stimulate advancement in ECG arrhythmia detection and classification.

Machine learning: Predicting hospital length of stay in patients admitted for lupus flares.

BACKGROUND: Although rare, severe systemic lupus erythematosus (SLE) flares requiring hospitalization account for most of the direct costs of SLE care. New machine learning (ML) methods may optimize lupus care by predicting which patients will have a prolonged hospital length of stay (LOS). Our study uses a machine learning approach to predict the LOS in patients admitted for lupus flares and assesses which features prolong LOS. METHODS: Our study sampled 5831 patients admitted for lupus flares from the National Inpatient Sample Database 2016-2018 and collected 90 demographics and comorbidity features. Four machine learning (ML) models were built (XGBoost, Linear Support Vector Machines, K Nearest Neighbors, and Logistic Regression) to predict LOS, and their performance was evaluated using multiple metrics, including accuracy, receiver operator area under the curve (ROC-AUC), precision-recall area under the curve (PR- AUC), and F1-score. Using the highest-performing model (XGBoost), we assessed the feature importance of our input features using Shapley value explanations (SHAP) to rank their impact on LOS. RESULTS: Our XGB model performed the best with a ROC-AUC of 0.87, PR-AUC of 0.61, an F1 score of 0.56, and an accuracy of 95%. The features with the most significant impact on the model were "the need for a central line," "acute dialysis," and "acute renal failure." Other top features include those related to renal and infectious comorbidities. CONCLUSION: Our results were consistent with the established literature and showed promise in ML over traditional methods of predictive analyses, even with rare rheumatic events such as lupus flare hospitalizations.

Methodological and Reporting Quality of Noninferiority Randomized Controlled Trials Comparing Antiretroviral Therapies: A Systematic Review.

BACKGROUND: It is unclear whether the reporting quality of antiretroviral (ARV) noninferiority (NI) randomized controlled trials (RCTs) has improved since the CONSORT guideline release in 2006. The primary objective of this systematic review was assessing the methodological and reporting quality of ARV NI-RCTs. We also assessed reporting quality by funding source and publication year. METHODS: We searched Medline, Embase, and Cochrane Central from inception to 14 November 2022. We included NI-RCTs comparing ≥2 ARV regimens used for human immunodeficiency virus treatment or prophylaxis. We used the Cochrane Risk of Bias 2.0 tool to assess risk of bias. Screening and data extraction were performed blinded and in duplicate. Descriptive statistics were used to summarize data; statistical tests were 2 sided, with significance defined as P < .05. The systematic review was prospectively registered (PROSPERO CRD42022328586), and not funded. RESULTS: We included 160 articles reporting 171 trials. Of these articles, 101 (63.1%) did not justify the NI margin used, and 28 (17.5%) did not provide sufficient information for sample size calculation. Eighty-nine of 160 (55.6%) reported both intention-to-treat and per-protocol analyses, while 118 (73.8%) described missing data handling. Ten of 171 trials (5.9%) reported potentially misleading results. Pharmaceutical industry-funded trials were more likely to be double-blinded (28.1% vs 10.3%; P = .03) and to describe missing data handling (78.5% vs 59.0%; P = .02). The overall risk of bias was low in 96 of 160 studies (60.0%). CONCLUSIONS: ARV NI-RCTs should improve NI margin justification, reporting of intention-to-treat and per-protocol analyses, and missing data handling to increase CONSORT adherence.

Modeling Heart Diseases on a Chip: Advantages and Future Opportunities.

Heart disease is a significant burden on global health care systems and is a leading cause of death each year. To improve our understanding of heart disease, high quality disease models are needed. These will facilitate the discovery and development of new treatments for heart disease. Traditionally, researchers have relied on 2D monolayer systems or animal models of heart disease to elucidate pathophysiology and drug responses. Heart-on-a-chip (HOC) technology is an emerging field where cardiomyocytes among other cell types in the heart can be used to generate functional, beating cardiac microtissues that recapitulate many features of the human heart. HOC models are showing great promise as disease modeling platforms and are poised to serve as important tools in the drug development pipeline. By leveraging advances in human pluripotent stem cell-derived cardiomyocyte biology and microfabrication technology, diseased HOCs are highly tuneable and can be generated via different approaches such as: using cells with defined genetic backgrounds (patient-derived cells), adding small molecules, modifying the cells' environment, altering cell ratio/composition of microtissues, among others. HOCs have been used to faithfully model aspects of arrhythmia, fibrosis, infection, cardiomyopathies, and ischemia, to name a few. In this review, we highlight recent advances in disease modeling using HOC systems, describing instances where these models outperformed other models in terms of reproducing disease phenotypes and/or led to drug development.

Chikungunya: An Emerging Public Health Concern.

Purpose of Review: The worldwide spread of chikungunya over the past two decades calls for greater knowledge and awareness of the virus, its route of transmission, methods of diagnosis, and the use of available treatment and prevention measures. Recent Findings: Chikungunya virus infection, an Aedes mosquito-borne febrile disease, has spread from Africa and Asia to Europe and the Americas and from the tropics and subtropics to temperate regions. International travel is a pivotal influence in the emergence of chikungunya as a global public health threat, as evidenced by a growing number of published reports on travel-related chikungunya infections. The striking features of chikungunya are arthralgia and arthritis, and the disease is often mistaken for dengue. Although mortality is low, morbidity can be profound and persistent. Current treatment for chikungunya is supportive; chikungunya vaccines and therapeutics are in development. Travelers planning to visit areas where the mosquito vectors are present should be advised on preventive measures. Summary: Chikungunya is an emerging disease in the Americas. Frequent travel, the presence of at least two competent mosquito species, and a largely naïve human population in the Western Hemisphere create a setting conducive to future outbreaks. Awareness of the disease and its manifestations is critical to effectively and safely manage and limit its impact. Vaccines in late-stage clinical trials offer a new pathway to prevention.

In high-risk outpatients with COVID-19, remdesivir reduced COVID-19-related hospitalization or all-cause death at 28 d.

SOURCE CITATION: Gottlieb RL, Vaca CE, Paredes R, et al. Early remdesivir to prevent progression to severe Covid-19 in outpatients. N Engl J Med. 2022;386:305-15. 34937145.

Secondary Analysis of a Systematic Review: Are Antifungal Noninferiority Trials at Risk of Eroding Effectiveness Because of Biocreep?

Noninferiority randomized controlled trial (RCT) effectiveness may erode when results favor the active control over time and when a decreasingly effective control arm is used in serial trials. We analyzed 32 antifungal noninferiority RCTs (NI-RCTs) for these scenarios in this secondary analysis of a systematic review. Our exploratory analysis suggests that the erosion risk in the effectiveness of antifungal noninferiority trials is uncommon. Findings are limited by small sample size and overall risk of bias.

Methodological and reporting quality of non-inferiority randomized controlled trials comparing antifungal therapies: a systematic review.

BACKGROUND: Detailed reporting is essential in non-inferiority randomized controlled trials (NI-RCTs) to assess evidence quality, as these trials inform standards of care. OBJECTIVES: The primary objective was to evaluate the methodological and reporting quality of antifungal NI-RCTs. DATA SOURCES: Medline, EMBASE, the Cochrane CENTRAL and the United States Federal Drug Administration (FDA) drugs database were searched to 9 September 2020. STUDY ELIGIBILITY CRITERIA: NI-RCTs differing by antifungal formulation, type, dose, administration and/or duration were included. Articles were independently assessed in duplicate using quality indicators developed by the Consolidated Standards of Reporting Trials (CONSORT) group. PARTICIPANTS: Patients enrolled in antifungal trials for prophylactic and therapeutic use. METHODS: The Cochrane RoB 2.0 tool was used to assess risk of bias. Descriptive statistics were used; all statistical tests were two sided. RESULTS: Of 32 included studies, 22 (68.7%) did not justify the NIM. Handling of missing data was not described in 20 (62.5%). Intention-to-treat (ITT) and per-protocol (PP) analyses were both reported in 12/32 (37.5%) studies. Eleven of 32 studies (34.3%) reported potentially misleading conclusions. Industry-financed studies were more likely to report only the ITT analysis (n = 14/27, 51.9%). Methodological and reporting quality was unaffected by publication year; risk of bias from missing data changed over time. Overall risk of bias across included studies was moderate to high, with high risk in randomization process (n = 8/32, 25%), missing outcome data (n = 5/32, 15.6%), and selection of reported result (n = 9/32, 28.1%). CONCLUSIONS: Justification of the non-inferiority margin, reporting of ITT and PP analyses, missing data handling description, and ensuring conclusions are consistent with reported data is necessary to improve CONSORT adherence. Small sample size and overall risk of bias are study limitations. (Systematic Review Registration Number PROSPERO CRD42020219497).

Engineered human cardiac microtissues: The state-of-the-(he)art.

Due to the integration of recent advances in stem cell biology, materials science, and engineering, the field of cardiac tissue engineering has been rapidly progressing toward developing more accurate functional 3D cardiac microtissues from human cell sources. These engineered tissues enable screening of cardiotoxic drugs, disease modeling (eg, by using cells from specific genetic backgrounds or modifying environmental conditions) and can serve as novel drug development platforms. This concise review presents the most recent advances and improvements in cardiac tissue formation, including cardiomyocyte maturation and disease modeling.

Unique cysteine-enriched, D2L5 and D4L6 extracellular loops in CaV3 T-type channels alter the passage and block of monovalent and divalent ions.

Invertebrate LCaV3 shares the quintessential features of vertebrate CaV3 T-type channels, with a low threshold of channel activation, rapid activation and inactivation kinetics and slow deactivation kinetics compared to other known Ca2+ channels, the CaV1 and CaV2 channels. Unlike the vertebrates though, CaV3 T-type channels in non-cnidarian invertebrates possess an alternative exon 12 spanning the D2L5 extracellular loop, which alters the invertebrate LCaV3 channel into a higher Na+ and lower Ca2+ current passing channel, more resembling a classical NaV1 Na+ channel. Cnidarian CaV3 T-type channels can possess genes with alternative cysteine-rich, D4L6 extracellular loops in a manner reminiscent of the alternative cysteine-rich, D2L5 extracellular loops of non-cnidarian invertebrates. We illustrate here that the preferences for greater Na+ or Ca2+ ion current passing through CaV3 T-type channels are contributed by paired cysteines within D2L5 and D4L6 extracellular loops looming above the pore selectivity filter. Swapping of invertebrate tri- and tetra-cysteine containing extracellular loops, generates higher Na+ current passing channels in human CaV3.2 channels, while corresponding mono- and di-cysteine loop pairs in human CaV3.2 generates greater Ca2+ current passing, invertebrate LCaV3 channels. Alanine substitutions of unique D2L5 loop cysteines of LCaV3 channels increases relative monovalent ion current sizes and increases the potency of Zn2+ and Ni2+ block by ~ 50× and ~ 10× in loop cysteine mutated channels respectively, acquiring characteristics of the high affinity block of CaV3.2 channels, including the loss of the slowing of inactivation kinetics during Zn2+ block. Charge neutralization of a ubiquitous aspartate residue of calcium passing CaV1, CaV2 and CaV3 channels, in the outer pore of the selectivity filter residues in Domain II generates higher Na+ current passing channels in a manner that may resemble how the unique D2L5 extracellular loops of invertebrate CaV3 channels may confer a relatively higher peak current size for Na+ ions over Ca2+ The extracellular loops of CaV3 channels are not engaged with accessory subunit binding, as the other Na+ (NaV1) and Ca2+ (CaV1/CaV2) channels, enabling diversity and expansion of cysteine-bonded extracellular loops, which appears to serve, amongst other possibilities, to alter to the preferences for passage of Ca2+ or Na+ ions through invertebrate CaV3 channels.

Human cardiac fibrosis-on-a-chip model recapitulates disease hallmarks and can serve as a platform for drug testing.

While interstitial fibrosis plays a significant role in heart failure, our understanding of disease progression in humans is limited. To address this limitation, we have engineered a cardiac-fibrosis-on-a-chip model consisting of a microfabricated device with live force measurement capabilities using co-cultured human cardiac fibroblasts and pluripotent stem cell-derived cardiomyocytes. Transforming growth factor-ß was used as a trigger for fibrosis. Here, we have reproduced the classic hallmarks of fibrosis-induced heart failure including high collagen deposition, increased tissue stiffness, BNP secretion, and passive tension. Force of contraction was significantly decreased in fibrotic tissues that displayed a transcriptomic signature consistent with human cardiac fibrosis/heart failure. Treatment with an anti-fibrotic drug decreased tissue stiffness and BNP secretion, with corresponding changes in the transcriptomic signature. This model represents an accessible approach to study human heart failure in vitro, and allows for testing anti-fibrotic drugs while facilitating the real-time assessment of cardiomyocyte function.

Implementation and evaluation of a quality and safety tool for ambulatory strongyloidiasis patients at high risk of adverse outcome.

BACKGROUND: Strongyloidiasis is a common infection in Canadian migrants that can cause life-threatening hyperinfection in immunosuppressed hosts. We designed and implemented a safety tool to guide management of patients with Strongyloides in order to prevent adverse outcomes. Methods: Patients treated at our centre for strongyloidiasis from January 1, 2013 to December 31, 2015 were identified through our ivermectin access log. Patients were categorized into pre-implementation and post-implementation groups. A retrospective chart review for predefined variables was conducted. RESULTS: Of 37 patients with strongyloidiasis, 26 were in the pre-implementation group and 11 were in the post-implementation group. Documented seroreversion (positive to negative) occurred in 42.1% of patients pre-implementation and 62.5% of patients post-implementation (p = 0.420). Documented stool clearance occurred in 80.0% of patients pre-implementation and 100.0% of patients post-implementation (p = 1.000). More patients were screened for HTLV-1 coinfection post-implementation (80.0%) versus pre-implementation (30.8%) (p = 0.011). Loss to follow-up after treatment occurred in 23.1% of patients pre-implementation and 20.0% of patients post-implementation (p = 1.000). CONCLUSIONS: The safety tool may be useful in the treatment of patients with strongyloidiasis to improve documentation of patient outcomes and standardize care. Future research should include a powered prospective study.

Video-thoracoscopic approach, without suture, of late thoracic esophageal perforations. / Abordagem vídeo-toracoscópica, sem sutura, das perfurações do esôfago torácico diagnosticadas tardiamente.

OBJECTIVES: to evaluate the use of video-thoracoscopy, in the treatment of late perforations of the thoracic esophagus, without suture or organ resection. METHODS: retrospective analysis of patients with late diagnosis (> 12 hours) of thoracic esophageal perforation treated by video-thoracoscopy, without suture or organ resection, over a 15-year period. RESULTS: sixteen patients were operated on, ten men and six women, aged between 48 and 66 years, with time between the diagnosis of the perforation and the surgery ranging from 16 to 26 hours. All patients underwent video-thoracoscopy, with pulmonary decortication, pleural loculations approach, opening of the mediastinal pleura near the perforation site and debridement of the devitalized tissues, followed by double drainage of the pleural cavity. No esophageal suture or resection was performed, and the patients evolved with complete closure of the lesions, without deaths. CONCLUSION: the video-thoracoscopic surgical approach was able to control pleural infection, pulmonary expansion and enable complete regeneration of the esophagus with late-diagnosed perforation.

OBJETIVOS: avaliar a utilização da vídeo-toracoscopia, no tratamento das perfurações tardias do esôfago torácico, sem sutura ou ressecção do órgão. MÉTODOS: análise retrospectiva de pacientes com diagnóstico tardio (>12 horas) de perfuração do esôfago torácico tratados por vídeo-toracoscopia, sem sutura ou ressecção do órgão, num período de 15 anos. RESULTADOS: foram operados 16 pacientes, sendo dez homens e seis mulheres, com idades entre 48 e 66 anos e com tempo entre o diagnóstico da perfuração e a cirurgia variando entre 16 e 26 horas. Todos os pacientes foram submetidos a vídeo-toracoscopia, com decorticação pulmonar, abordagem das loculações pleurais, abertura da pleura mediastinal junto ao local da perfuração e desbridamento dos tecidos desvitalizados, seguido por dupla drenagem da cavidade pleural. Não foi realizada sutura ou ressecção esofagiana, e os pacientes evoluíram com fechamento completo das lesões, sem óbitos. CONCLUSÃO: a abordagem cirúrgica vídeo-toracoscópica mostrou-se capaz de controlar a infecção pleural, a expansão pulmonar e possibilitar a completa regeneração do esôfago com perfuração diagnosticada tardiamente.