Value of nutritional indices in predicting survival free from pump replacement and driveline infections in centrifugal left ventricular assist devices.

Objective: There is a paucity of data assessing the impact of nutritional status on outcomes in patients supported with the HeartMate 3 (HM3) left ventricular assist device (LVAD). Methods: Patients ≥18 years of age who underwent HM3 LVAD implantation between 2015 and 2020 were identified from a single tertiary care center. The primary outcome assessed was death or device replacement. A secondary outcome of driveline infection was also evaluated. Kaplan-Meier survival analysis and a multivariate Cox-proportional hazards model were used to identify predictors of outcome. Results: Of the 289 patients identified, 94 (33%) experienced a primary outcome and 96 (33%) a secondary outcome during a median follow-up time of 2.3 years. Independent predictors of the primary outcome included peripheral vascular disease (hazard ratio [HR], 3.40; 95% confidence interval [CI], 1.66-6.97, P < .01), diabetes mellitus (HR, 0.46; 95% CI, 0.27-0.80, P < .01), body mass index ≥40 kg/m2 (HR, 2.63 per 1 kg/m2 increase; 95% CI, 1.22-5.70, P < .05), preoperative creatinine level (HR, 1.86 per 1 mg/dL increase; 95% CI, 1.31-2.65, P < .01), and preoperative prognostic nutritional index (PNI) score (HR, 0.88 per 1-point increase; 95% CI, 0.81-0.96, P < .01). Independent predictors of driveline infection included age at the time of implantation (HR, 0.97; 95% CI, 0.96-0.99, P < .01) and diabetes mellitus (HR, 1.79; 95% CI, 1.17-2.73, P < .01). Conclusions: Preoperative PNI scores may independently predict mortality and the need for device replacement in patients with HM3 LVAD. Routine use of the PNI score during preoperative evaluation and, when possible, supplementation to PNI >33, may be of value in this population.

Development and Validation of a Natural Language Processing Model to Identify Low-Risk Pulmonary Embolism in Real Time to Facilitate Safe Outpatient Management.

STUDY OBJECTIVE: This study aimed to (1) develop and validate a natural language processing model to identify the presence of pulmonary embolism (PE) based on real-time radiology reports and (2) identify low-risk PE patients based on previously validated risk stratification scores using variables extracted from the electronic health record at the time of diagnosis. The combination of these approaches yielded an natural language processing-based clinical decision support tool that can identify patients presenting to the emergency department (ED) with low-risk PE as candidates for outpatient management. METHODS: Data were curated from all patients who received a PE-protocol computed tomography pulmonary angiogram (PE-CTPA) imaging study in the ED of a 3-hospital academic health system between June 1, 2018 and December 31, 2020 (n=12,183). The "preliminary" radiology reports from these imaging studies made available to ED clinicians at the time of diagnosis were adjudicated as positive or negative for PE by the clinical team. The reports were then divided into development, internal validation, and temporal validation cohorts in order to train, test, and validate an natural language processing model that could identify the presence of PE based on unstructured text. For risk stratification, patient- and encounter-level data elements were curated from the electronic health record and used to compute a real-time simplified pulmonary embolism severity (sPESI) score at the time of diagnosis. Chart abstraction was performed on all low-risk PE patients admitted for inpatient management. RESULTS: When applied to the internal validation and temporal validation cohorts, the natural language processing model identified the presence of PE from radiology reports with an area under the receiver operating characteristic curve of 0.99, sensitivity of 0.86 to 0.87, and specificity of 0.99. Across cohorts, 10.5% of PE-CTPA studies were positive for PE, of which 22.2% were classified as low-risk by the sPESI score. Of all low-risk PE patients, 74.3% were admitted for inpatient management. CONCLUSION: This study demonstrates that a natural language processing-based model utilizing real-time radiology reports can accurately identify patients with PE. Further, this model, used in combination with a validated risk stratification score (sPESI), provides a clinical decision support tool that accurately identifies patients in the ED with low-risk PE as candidates for outpatient management.

Eliminating Health Disparities in Atrial Fibrillation, Heart Failure, and Dyslipidemia: A Path Toward Achieving Pharmacoequity.

PURPOSE OF REVIEW: Pharmacoequity refers to the goal of ensuring that all patients have access to high-quality medications, regardless of their race, ethnicity, gender, or other characteristics. The goal of this article is to review current evidence on disparities in access to cardiovascular drug therapies across sociodemographic subgroups, with a focus on heart failure, atrial fibrillation, and dyslipidemia. RECENT FINDINGS: Considerable and consistent disparities to life-prolonging heart failure, atrial fibrillation, and dyslipidemia medications exist in clinical trial representation, access to specialist care, prescription of guideline-based therapy, drug affordability, and pharmacy accessibility across racial, ethnic, gender, and other sociodemographic subgroups. Researchers, health systems, and policy makers can take steps to improve pharmacoequity by diversifying clinical trial enrollment, increasing access to inpatient and outpatient cardiology care, nudging clinicians to increase prescription of guideline-directed medical therapy, and pursuing system-level reforms to improve drug access and affordability.

Institutional review of predictors of in-hospital and 30-day discharge mortality in neurosurgical patients.

OBJECTIVE: Risk of adverse events from neurosurgical diagnoses is high. It is not well described whether there are any demographic, admission, or discharge factors that are associated with inpatient or post-discharge mortality outcomes in neurosurgical patients. The aim of this study is to identify the differences in predictors of mortality during inpatient stay and within 30 days of discharge. METHODS: This was a single-institution, retrospective cohort analysis of mortality. Our patient cohort of 11,477 was defined as all adult patients who were discharged (dead or alive) from an inpatient stay between January 1, 2014, and December 31, 2018, and were either admitted to a neurosurgical service or underwent a neurosurgical procedure during that admission. RESULTS: Out of 11,477 patients, 224 (1.95 %) and 290 (2.53 %) died inpatient and within 30 days of discharge, respectively. In multivariate analysis, the independent predictors of inpatient mortality were older age, female gender, diagnostic group, high present on admission severity of illness (POA-SOI) and present on admission risk of mortality (POA-ROM), intensive care unit (ICU) care, and palliative care consult (all p < 0.05). The predictors of mortality within 30-day discharge were older age, admission urgency, admission specialty type, palliative care consult, and discharge disposition (all p < 0.01). CONCLUSION: Older age and palliative care consult were significant predictors of both inpatient and within 30 days of discharge mortality. Admission SOI (>3) and ROM (>3) and ICU care were significant predictors for inpatient mortality while discharge disposition (home health, skilled nursing facility) was important for 30-day mortality.

Diagnostic utility of exome sequencing in the evaluation of neuromuscular disorders.

OBJECTIVE: To evaluate the diagnostic yield and workflow of genome-scale sequencing in patients with neuromuscular disorders (NMDs). METHODS: We performed exome sequencing in 93 undiagnosed patients with various NMDs for whom a molecular diagnosis was not yet established. Variants on both targeted and broad diagnostic gene lists were identified. Prior diagnostic tests were extracted from the patient's medical record to evaluate the use of exome sequencing in the context of their prior diagnostic workup. RESULTS: The overall diagnostic yield of exome sequencing in our cohort was 12.9%, with one or more pathogenic or likely pathogenic variants identified in a causative gene associated with the patient's disorder. Targeted gene lists had the same diagnostic yield as a broad NMD gene list in patients with clear neuropathy or myopathy phenotypes, but evaluation of a broader set of disease genes was needed for patients with complex NMD phenotypes. Most patients with NMD had undergone prior testing, but only 10/16 (63%) of these procedures, such as muscle biopsy, were informative in pointing to a final molecular diagnosis. CONCLUSIONS: Genome-scale sequencing or analysis of a panel of relevant genes used early in the evaluation of patients with NMDs can provide or clarify a diagnosis and minimize invasive testing in many cases.

Germline Analysis from Tumor-Germline Sequencing Dyads to Identify Clinically Actionable Secondary Findings.

PURPOSE: To evaluate germline variants in hereditary cancer susceptibility genes among unselected cancer patients undergoing tumor-germline sequencing. EXPERIMENTAL DESIGN: Germline sequence data from 439 individuals undergoing tumor-germline dyad sequencing through the LCCC1108/UNCseq™ (NCT01457196) study were analyzed for genetic variants in 36 hereditary cancer susceptibility genes. These variants were analyzed as an exploratory research study to determine whether pathogenic variants exist within the germline of patients undergoing tumor-germline sequencing. Patients were unselected with respect to indicators of hereditary cancer predisposition. RESULTS: Variants indicative of hereditary cancer predisposition were identified in 19 (4.3%) patients. For about half (10/19), these findings represent new diagnostic information with potentially important implications for the patient and their family. The others were previously identified through clinical genetic evaluation secondary to suspicion of a hereditary cancer predisposition. Genes with pathogenic variants included ATM, BRCA1, BRCA2, CDKN2A, and CHEK2 In contrast, a substantial proportion of patients (178, 40.5%) had Variants of Uncertain Significance (VUS), 24 of which had VUS in genes pertinent to the presenting cancer. Another 143 had VUS in other hereditary cancer genes, and 11 had VUS in both pertinent and nonpertinent genes. CONCLUSIONS: Germline analysis in tumor-germline sequencing dyads will occasionally reveal significant germline findings that were clinically occult, which could be beneficial for patients and their families. However, given the low yield for unexpected germline variation and the large proportion of patients with VUS results, analysis and return of germline results should adhere to guidelines for secondary findings rather than diagnostic hereditary cancer testing. Clin Cancer Res; 22(16); 4087-94. ©2016 AACRSee related commentary by Mandelker, p. 3987.