Prediction of heart failure and all-cause mortality using cardiac ultrasomics in patients with breast cancer.

Breast cancer chemotherapy/immunotherapy can be associated with treatment-limiting cardiotoxicity. Radiomics techniques applied to ultrasound, known as ultrasomics, can be used in cardio-oncology to leverage echocardiography for added prognostic value. To utilize ultrasomics features collected prior to antineoplastic therapy to enhance prediction of mortality and heart failure (HF) in patients with breast cancer. Patients were retrospectively recruited in a study at the West Virginia University Cancer Institute. The final inclusion criteria were met by a total of 134 patients identified for the study. Patients were imaged using echocardiography in the parasternal long axis prior to receiving chemotherapy. All-cause mortality and HF, developed during treatment, were the primary outcomes. 269 features were assessed, grouped into four major classes: demographics (n = 21), heart function (n = 7), antineoplastic medication (n = 17), and ultrasomics (n = 224). Data was split into an internal training (60%, n = 81) and testing (40%, n = 53) set. Ultrasomics features augmented classification of mortality (area under the curve (AUC) 0.89 vs. 0.65, P = 0.003), when compared to demographic variables. When developing a risk prediction score for each feature category, ultrasomics features were significantly associated with both mortality (P = 0.031, log-rank test) and HF (P = 0.002, log-rank test). Further, only ultrasomics features provided significant improvement over demographic variables when predicting mortality (C-Index: 0.78 vs. 0.65, P = 0.044) and HF (C-Index: 0.77 vs. 0.60, P = 0.017), respectively. With further investigation, a clinical decision support tool could be developed utilizing routinely obtained patient data alongside ultrasomics variables to augment treatment regimens.

Neutrophil lymphocyte ratio (NLR) and systemic immune inflammatory index (SII) for the differential diagnosis of CT-negative mild acute ischemic stroke and transient ischemic attack.

Background: A number of acute ischemic stroke (AIS) cases may be misdiagnosed as transient ischemic attack (TIA), due to no infarct on initial computed tomography scan and/or mild deficits upon presentation. Several studies have found that the neutrophil-lymphocyte ratio (NLR) is an accurate differential diagnostic biomarker for AIS versus TIA; however, no study has evaluated the use of the NLR in differentiating CT negative AIS from TIA. Furthermore, the systemic immune-inflammation index (SII) is a relatively novel immune biomarker that has been shown to be positively correlated with AIS severity, poor functional outcomes and mortality. The purpose of this study is to determine if NLR or SII can be used as a diagnostic biomarker for the differential diagnosis of mild AIS with a negative CT upon admission and TIA. Methods: We performed a retrospective medical record review of patients diagnosed with either AIS or TIA. We collected peripheral white blood cell counts within 24 h of symptom onset and calculated the NLR and SII. Logistic regression was utilized to determine if NLR or SII are significant predictors of CT negative mild AIS. Results: CT negative mild AIS patients were 2 times as likely to have an NLR ≥ 2.71 compared to TIA patients, and CT negative mild AIS patients were 2.1 times as likely to have an SII ≥ 595 compared to TIA patients. Conclusion: NLR and SII are easily obtained biomarkers that can be used in early clinical decision making in cases of mild AIS with negative CT scan upon admission.

Leukocyte Biomarkers for the Differential Diagnosis of Mild Acute Ischemic Stroke, Transient Ischemic Attack, and Stroke Mimic.

Introduction The differential diagnosis of transient ischemic attack (TIA) versus mild acute ischemic stroke (AIS) during the initial presentation to the emergency department is often difficult, as the diagnosis of both TIA and AIS relies on the presence of focal neurologic signs. As such, roughly 50% of patients with transient or mild neurologic deficits have an uncertain diagnosis prior to neuroimaging. Biomarkers, particularly leukocyte biomarkers, may be used by clinicians to diagnose mild AIS prior to neuroimaging, and this study is the first to describe the use of leukocyte biomarkers for the differentiation of mild AIS, TIA, and stroke mimic. Methods We performed a retrospective chart review of patients discharged from a local hospital with a discharge diagnosis of either TIA or AIS. Past medical history and complete blood cell count with differential upon admission were collected for all subjects. Statistical analyses were performed to compare immune cell parameters between the two groups. For all comparisons, logistic regression analysis was used to assess the effect of confounding variables, such as age, gender, and medical history for each study variable. Results Of all the immune parameters assessed in this study, the neutrophil percentage was the only significant biomarker that significantly differed between study groups. After adjustment for confounding variables using stepwise logistic regression, mild AIS patients were 5.3 times more likely than TIA cases to have a neutrophil percentage above the normal range. Conclusion Our results suggest that clinicians may utilize neutrophil percentage as an additional piece of information that may aid in their diagnosis of mild AIS versus TIA.