13 research outputs found
Personalized diagnosis in suspected myocardial infarction
Background: In suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hscTn)- based approaches. These require fixed assay-specific thresholds and timepoints, without directly integrating clinical information. Using machine-learning techniques including hs-cTn and clinical routine variables, we aimed to build a digital tool to directly estimate the individual probability of MI, allowing for numerous hs-cTn assays. Methods: In 2,575 patients presenting to the emergency department with suspected MI, two ensembles of machine-learning models using single or serial concentrations of six different hs-cTn assays were derived to estimate the individual MI probability ( ARTEMIS model). Discriminative performance of the models was assessed using area under the receiver operating characteristic curve (AUC) and logLoss. Model performance was validated in an external cohort with 1688 patients and tested for global generalizability in 13 international cohorts with 23,411 patients. Results: Eleven routinely available variables including age, sex, cardiovascular risk factors, electrocardiography, and hs-cTn were included in the ARTEMIS models. In the validation and generalization cohorts, excellent discriminative performance was confirmed, superior to hs-cTn only. For the serial hs-cTn measurement model, AUC ranged from 0.92 to 0.98. Good calibration was observed. Using a single hs-cTn measurement, the ARTEMIS model allowed direct rule-out of MI with very high and similar safety but up to tripled efficiency compared to the guideline- recommended strategy. Conclusion We developed and validated diagnostic models to accurately estimate the individual probability of MI, which allow for variable hs-cTn use and flexible timing of resampling. Their digital application may provide rapid, safe and efficient personalized patient care
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Comparing transplant outcomes in ALL patients after haploidentical with PTCy or matched unrelated donor transplantation
We compared outcomes of 1461 adult patients with acute lymphoblastic leukemia (ALL) receiving hematopoietic cell transplantation (HCT) from a haploidentical (n = 487) or matched unrelated donor (MUD; n = 974) between January 2005 and June 2018. Graft-versus-host disease (GVHD) prophylaxis was posttransplant cyclophosphamide (PTCy), calcineurin inhibitor (CNI), and mycophenolate mofetil (MMF) for haploidentical, and CNI with MMF or methotrexate with/without antithymoglobulin for MUDs. Haploidentical recipients were matched (1:2 ratio) with MUD controls for sex, conditioning intensity, disease stage, Philadelphia-chromosome status, and cytogenetic risk. In the myeloablative setting, day +28 neutrophil recovery was similar between haploidentical (87%) and MUD (88%) (P = .11). Corresponding rates after reduced-intensity conditioning (RIC) were 84% and 88% (P = .47). The 3-month incidence of grade II-IV acute GVHD (aGVHD) and 3-year chronic GVHD (cGVHD) was similar after haploidentical compared with MUD: myeloablative conditioning, 33% vs 34% (P = .46) for aGVHD and 29% vs 31% for cGVHD (P = .58); RIC, 31% vs 30% (P = .06) for aGVHD and 24% vs 29% for cGVHD (P = .86). Among patients receiving myeloablative regimens, 3-year probabilities of overall survival were 44% and 51% with haploidentical and MUD (P = .56). Corresponding rates after RIC were 43% and 42% (P = .6). In this large multicenter case-matched retrospective analysis, despite the limitations of a registry-based study (ie, unavailability of key elements such as minimal residual disease testing), our analysis indicated that outcomes of patients with ALL undergoing HCT from a haploidentical donor were comparable with 8 of 8 MUD transplantations