This study of patients with acute myelogenous leukemia (AML) age 60 years analyzed the association between patients' performance indices-Hematopoietic Stem Cell Transplantation Comorbidity Index (HCT-CI), Karnofsky Performance Score (KPS), and European Society for Blood and Marrow Transplantation (EBMT) risk score-before undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) and quality of life (QoL), quantified using the Functional Assessment of Cancer Therapy-Bone Marrow Transplant Scale (FACT-BMT), in the first year after allo-HSCT. Over a period of 7 years, 48 evaluable patients underwent reduced-intensity conditioning allo-HSCT. The median patient age was 65 years (range, 60 to 74 years), with 2-year and 5-year overall survival (OS) of 65.8% and 52.3%, respectively. A significant improvement across all QoL scores was observed over the 12 months post-HSCT. An HCT-CI of 0 was associated with improved general QoL (FACT-G) score at 6 months compared with patients with an HCT-CI of 1 to 2 (P= .032). At 12 months post-HSCT, a pretransplantation HCT-CI 3 was correlated with lower QoL scores across the domains (symptom-related QoL [FACT-TOI], P= .036; FACT-G, P= .05; BMTrelated QoL [FACT-BMT], P= .036). A pretransplantation KPS score of 100 versus 80 to 90 was predictive of improved QoL at 6 months post-HSCT (FACT-TOI, P = .009; FACT-G, P= .001; FACT-BMT, P= .002) but not at 1 year post-HSCT. We demonstrate that KPS and HCT-CI can predict QoL in the early post-transplantation period, with a favorable overall survival in a selected cohort of AML patients age 60 years.

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Introduction. Left ventricular diastolic dysfunction (LVDD) and atrial fibrillation (AF) are connected by pathophysiology and prevalence. LVDD remains underdiagnosed in critically ill patients despite potentially significant therapeutic implications since direct measurement cannot be performed in routine care at the bedside, and echocardiographic assessment of LVDD in AF is impaired. We propose a novel approach that allows us to infer the diastolic stiffness, β, a key quantitative parameter of diastolic function, from standard monitoring data by solving the nonlinear, ill-posed inverse problem of parameter estimation for a previously described mechanistic, physiological model of diastolic filling. The beat-to-beat variability in AF offers an advantageous setting for this. Methods. By employing a global optimization algorithm, β is inferred from a simple six parameter and an expanded seven parameter model of left ventricular filling. Optimization of all parameters was limited to the interval ]0, 400[ and initialized randomly on large intervals encompassing the support of the likelihood function. Routine ECG and arterial pressure recordings of 17 AF and 3 sinus rhythm (SR) patients from the PhysioNet MGH/MF Database were used as inputs. Results. Estimation was successful in 15 of 17 AF patients, while in the 3 SR patients, no reliable estimation was possible. For both models, the inferred β (0.065 ± 0.044 ml−1 vs. 0.038 ± 0.033 ml−1 (p=0.02) simple vs. expanded) was compatible with the previously described (patho) physiological range. Aortic compliance, α, inferred from the expanded model (1.46 ± 1.50 ml/mmHg) also compared well with literature values. Conclusion. The proposed approach successfully inferred β within the physiological range. This is the first report of an approach quantifying LVDF from routine monitoring data in critically ill AF patients. Provided future successful external validation, this approach may offer a tool for minimally invasive online monitoring of this crucial parameter.