Development and analytical validation of a 25-gene next generation sequencing panel that includes the BRCA1 and BRCA2 genes to assess hereditary cancer risk.

BACKGROUND: Germline DNA mutations that increase the susceptibility of a patient to certain cancers have been identified in various genes, and patients can be screened for mutations in these genes to assess their level of risk for developing cancer. Traditional methods using Sanger sequencing focus on small groups of genes and therefore are unable to screen for numerous genes from several patients simultaneously. The goal of the present study was to validate a 25-gene panel to assess genetic risk for cancer in 8 different tissues using next generation sequencing (NGS) techniques. METHODS: Twenty-five genes associated with hereditary cancer syndromes were selected for development of a panel to screen for risk of these cancers using NGS. In an initial technical assessment, NGS results for BRCA1 and BRCA2 were compared with Sanger sequencing in 1864 anonymized DNA samples from patients who had undergone previous clinical testing. Next, the entire gene panel was validated using parallel NGS and Sanger sequencing in 100 anonymized DNA samples. Large rearrangement analysis was validated using NGS, microarray comparative genomic hybridization (CGH), and multiplex ligation-dependent probe amplification analyses (MLPA). RESULTS: NGS identified 15,877 sequence variants, while Sanger sequencing identified 15,878 in the BRCA1 and BRCA2 comparison study of the same regions. Based on these results, the NGS process was refined prior to the validation of the full gene panel. In the validation study, NGS and Sanger sequencing were 100% concordant for the 3,923 collective variants across all genes for an analytical sensitivity of the NGS assay of >99.92% (lower limit of 95% confidence interval). NGS, microarray CGH and MLPA correctly identified all expected positive and negative large rearrangement results for the 25-gene panel. CONCLUSION: This study provides a thorough validation of the 25-gene NGS panel and indicates that this analysis tool can be used to collect clinically significant information related to risk of developing hereditary cancers.

A Case-Based Approach to the Management of Patients with Chronic Coronary Disease: Updates from the 2023 AHA/ACC Guidelines.

The 2023 American Heart Association (AHA)/American College of Cardiology (ACC) Multisociety Guideline for the Management of Patients with Chronic Coronary Disease presents important updates to the care of patients with chronic coronary disease (1). The recommendations of these guidelines inform the care for patients with (1) asymptomatic coronary artery disease, (2) stable angina or equivalent symptoms (e.g., dyspnea upon exertion), (3) symptomatic nonobstructive coronary disease including coronary microvascular dysfunction and vasospasm, and (4) left ventricular (LV) systolic dysfunction with known coronary artery disease. In this review, we aim to demonstrate key recommendations in the 2023 guideline using the following four hypothetical cases.

Using Machine Learning for Early Prediction of Cardiogenic Shock in Patients With Acute Heart Failure.

Background: Despite technological and treatment advancements over the past 2 â€‹decades, cardiogenic shock (CS) mortality has remained between 40% and 60%. Our objective was to develop an algorithm that can continuously monitor heart failure patients and partition them into cohorts of high and low risk for CS. Methods: We retrospectively studied 24,461 patients hospitalized with acute decompensated heart failure, 265 of whom developed CS, in the Johns Hopkins Health System. Our cohort identification approach is based on logistic regression and makes use of vital signs, lab values, and medication administrations recorded during the normal course of care. Results: Our algorithm identified patients at high risk of CS. Patients in the high-risk cohort had 10.2 times (95% confidence interval, 6.1-17.2) higher prevalence of CS than those in the low-risk cohort. Patients who experienced CS while in the high-risk cohort were first deemed high risk a median of 1.7 â€‹days (interquartile range, 0.8-4.6) before CS diagnosis was made by their clinical team. To evaluate actionability, we randomly selected 50 patients designated as high risk who did develop CS and 50 who did not. On review of true positive cases, from the time of model identification as high risk to the eventual diagnosis of CS, 12% of patients had possible inappropriate therapy, and for 50% of patients, more tailored therapy options existed. On review of the false positive cases, 44% of cases were considered at high risk of CS or end-stage cardiomyopathy by their clinical teams or went onto develop other types of shock. Conclusions: This risk model was able to predict patients at higher risk of CS in a time frame that allowed a change in clinical care. The actionability evaluation demonstrates a possible opportunity to intervene as part of a CS algorithm for escalation of care.

Free Tissue Breast Reconstruction.

Free tissue transfer serves as a modern workhorse for breast reconstruction. Advancements in microsurgical technique have allowed for the development of free flap procedures that produce an aesthetic breast while minimizing donor site morbidity. Here, the authors review the use of different free flap procedures for breast reconstruction with a focus on the preferred and most commonly used flap, the deep inferior epigastric perforator flap. Each flap has its advantages and drawbacks, and certain patient risk factors increase postoperative complications. Other techniques of breast reconstruction including pedicled flaps and adjunctive fat grafting are also briefly discussed.

Does this patient need telemetry? An analysis of telemetry ordering practices at an academic medical center.

INTRODUCTION: The American Heart Association and Choosing Wisely campaign recommend guideline-based usage of telemetry. Inappropriate use leads to increased costs, alarm fatigue, and inefficient nursing care. This study assesses provider ordering practices for telemetry at a US-based academic hospital. METHODS: This retrospective study includes all telemetry orders in the medicine and progressive care units from April 2014 to March 2015. Indications were grouped into categories per American Heart Association guidelines. RESULTS: The top 3 cardiac indications included angina/acute coronary syndrome (35.3%), arrhythmias (19.7%), and heart failure (10.2%). However, noncardiac indications accounted for 20.2% of orders, including respiratory conditions (17.4%), infection (17.4%), substance abuse (14.0%), bleeding (12.4%), vital sign monitoring (10.4%), altered mental status (7.0%), and pulmonary embolus/deep vein thrombosis (7.0%). CONCLUSIONS: One-fifth of patients were monitored on telemetry for noncardiac indications. We recommend further study on the benefits and risks of telemetry in these patients and systems-based changes for appropriate usage.