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Introduction -Diffuse large B-cell lymphoma (DLBCL) is a frequent and aggressive lymphoma. First line of treatment associates an anti-CD20 immunotherapy with an anthracycline-based chemotherapy (R-CHOP). After this treatment, 30% of patients present primary refractory disease or early relapse within two years (R/R DLBCL). At date, CAR-T cells improve the prognosis of patients with R/R DLBCL compared with high-dose chemotherapy followed by autologous stem-cell transplant. However, predicting this failure remains a challenge at time of diagnosis. Current standard tools as the R-IPI score have many weaknesses, particularly for patients most at risk. A multitude of clinical, biological and PET data are available and could help to precise R/R DLBCL probability. In this study, we propose a new strategy based on machine learning and exploitation of a large dataset to early detect patients with high risk of R/R DLBCL at diagnosis.

Introduction- Postdural-puncture headache (PDPH) is the most common complication after lumbar puncture, probably due to leakage of cerebrospinal fluid (CSF) from the dural defect into the epidural space. Most cases of PDPH occur within 8 days of a lumbar puncture and may be associated with other symptoms, such as photophobia, nausea or neurological complications. In this context, PDPH is a debilitating condition that significantly impacts quality of life. While several risk factors have been proposed to participate in PDPH etiology, no preventive or therapeutic measures have robustly proven their efficacity . Among PDPH-related risk factors, needle tip shape has been shown to influence the incidence of PDPH, especially in the context of diagnostic LP. The purpose of this study was to assess the incidence of PDPH using conventional (cutting-type) or atraumatic (pencil-point) spinal needles in hematological patients.