Egan Futtrup (sontoast4)

OBJECTIVE In patients with non-Hodgkin lymphoma (NHL), we investigated F FDG PET/computed tomography (CT) parameters, clinical findings, laboratory parameters, and bone marrow involvement (BMI) status for predictive methods in progression-free survival (PFS) and overall survival (OS), and whether F FDG PET/CT could take the place of bone marrow biopsy (BMB). METHODS The performance of F FDG PET/CT (BMPET) was evaluated. The prognostic value of maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), stage, international prognostic index (IPI) score, IPI risk, lactate dehydrogenase (LDH), B2 microglobulin, Ki67 proliferation index, and the presence of BMI was evaluated for OS and PFS. Kaplan-Meier curves were drawn for each designated cutoff value, and 5-year PFS and 7-year OS were evaluated using log-rank analysis. RESULTS The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of BMPET and BMB to identify BMI were 69, 100, 86.1, 80, 100%, and 81.6, 100, 92.5, 89, 100%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of BMPET in patients with Ki67- proliferation index >25% were all 100%. BMPET, IPI risk, MTV, and LDH were found to be independent prognostic predictors for PFS, whereas BMPET, SUVmax, and MTV for OS. Five-year PFS analysis estimated as follows BMPET (+) = 22%, BMPET (-) = 80%, LDH ≤ 437 (U/L) = 86%, LDH > 437 (U/L) = 51%, MTV ≤ 56 (cm) = 87%, MTV > 56 (cm) = 49%, low IPI risk = 87%, intermediate IPI risk = 69%, high IPI risk = 25%. Seven-year OS analysis was found as SUVmax ≤ 17.6 = 80%, SUVmax > 17.6 = 48%, MTV ≤ 56 (cm) = 84.4%, MTV > 56 (cm) = 45.8%, BMPET (-) = 72.5%, BMPET (+) = 42%. CONCLUSION In the Ki-67 proliferation index > 25% group, F FDG PET/CT was able to differentiate BMI independently from NHL subgroups. We recommend using this method with large patient groups. MTV and BMPET were independent prognostic indicators for OS and PFS and may help to determine high-risk patients.OBJECTIVE Timely pre-hospital diagnosis and treatment of acute coronary syndrome (ACS) are required to achieve optimal outcomes. Clinical decision support systems (CDSS) are platforms designed to integrate multiple data and can aid with management decisions in the pre-hospital environment. The review aim was to describe the accuracy of CDSS and individual components in the pre-hospital ACS management. METHODS This systematic review examined the current literature regarding the accuracy of CDSS for ACS in the pre-hospital setting, the influence of computer-aided decision making and of four components electrocardiogram, biomarkers, patient history and examination findings. The impact of these components on sensitivity, specificity, positive and negative predictive values was assessed. RESULTS A total of 11,439 articles were identified from a search of databases, of which 199 were screened against the eligibility criteria. Eight studies were found to meet the eligibility and quality criteria. There was marked heterogeneity between studies which precluded formal meta-analysis. However, individual components analysis found that patient history led to significant improvement in the sensitivity and negative predictive values. Linsitinib IGF-1R inhibitor CDSS which incorporated all four components tended to show higher sensitivities and negative predictive values. CDSS incorporating computer-aided electrocardiogram diagnosis showed higher specificities and positive predictive values. CONCLUSIONS Although heterogeneity precluded meta-analysis, this review emphasises the potential of ACS CDSS in pre-hospital environments that incorporate patient history in addition to integration of multiple components. The higher sensitivity of certain components, along with higher specificity of computer-aided decision-making, highlights the opportunity for developing an integrated algorithm with computer-aided decision support.BACKGROUND Low-soc