[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"diffusion-tensor-imaging-prognosis\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:diffusion-tensor-imaging-prognosis":24},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":14,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":4,"briefSummary":22,"conditions":23,"keywords":25,"overallStatus":31,"whyStopped":4,"lastUpdateSubmitDate":32,"lastUpdatePostDateStruct":33,"startDateStruct":36,"completionDateStruct":38,"leadSponsor":40,"locationsCount":43},"100659367","description-of-clinicians-predictive-abilities-before-and-after-a-diffusion-tensor-imaging-dti-100659367",false,"NCT07863414","Description of Clinicians' Predictive Abilities Before and After a Diffusion Tensor Imaging (DTI)","Neuro-FORECAST","Inclusion Criteria:\n\n* For clinicians:\n* Clinicians with a medical degree\n* Prescribers of DTI for the following patients\n\nFor patients :\n\n* Patients aged 18 years or older\n* Patients for whom a brain MRI with a DTI sequences is prescribed, during or following resuscitation as part of their care.\n* A close relative or trusted person informed of the research and who has not objected to the patient's participation in the study. Given the altered state of consciousness of these patients, the patient is unable to express their objection.\n\nExclusion Criteria:\n\nFor clinicians - Clinician's refusal to complete the study questionnaires\n\nFor patients:\n\n\\- DTI measurements (anisotropy fraction and mean diffusivity) not feasible before or after treatment","ALL","18 Years",{"count":19,"type":20},220,"ESTIMATED","OBSERVATIONAL","With a mortality rate of over 13% in the neuro-intensive care unit, 86% of which are related to the withdrawal of active treatment, predicting a reliable neurological prognosis is of paramount importance in neuro-intensive care to help clinicians inform family members appropriately and tailor care to the patient's presumed wishes. This also helps justify aggressive resuscitation in patients with a presumed good prognosis and, conversely, avoid keeping patients with a poor neurological prognosis alive against their presumed wishes.\n\nCurrent guidelines recommend multimodal neuro-prognostication, in which the clinician synthesizes prognostic data from the clinical examination, EEG, plasma or CSF biomarkers, and imaging to collaboratively develop an individualized prognosis, even though no study has evaluated the quality of this multimodal prognosis. Furthermore, existing variations depending on the nosological context make this approach complex and likely difficult to replicate.\n\nBrain MRI is an important tool for neuroprognostics in patients with neurological injuries, and for this reason it is commonly used in clinical practice as part of this multimodal approach.\n\nMore specifically, brain MRI with diffusion tensor sequences is a validated prognostic tool in post-anoxic coma and traumatic brain injury, as well as, more recently, in subarachnoid hemorrhage, strokes, and hypoglycemia. However, it has not yet been compared to multimodal neuroprognostics performed by the clinician.\n\nThe primary objective is to compare the prognostic performance of two prescribing clinicians with diffusion tensor MRI before and after the MRI scan is performed.\n\nPrimary outcome measure: to compare the prognostic performance regarding unfavorable outcomes (Glasgow Outcome Scale Extended \\\u003C 5) at 12 months between the two prescribing clinicians and diffusion tensor MRI before and after the MRI scan is performed.\n\nA secondary objective will be, among other things, to study the informational gain provided by MRI in improving clinicians' predictions after receiving the MRI results.\n\nIntensive care clinicians constitute the target population. These are clinicians caring for an intensive care patient with a brain injury who order a brain MRI for prognostic purposes as part of patient care and multimodal neuroprognostics.\n\nOn the day of the MRI, two clinicians will complete the research questionnaire assessing the patient's prognosis the day before or a few hours before the MRI (on the same day). Then, as soon as the MRI results are available, the same two clinicians will complete the same questionnaire assessing the patient's prognosis after reviewing the MRI results. Patient data regarding the pathology and prognostic factors will be collected at this time.\n\nFinally, surviving patients will be interviewed at 1 year regarding their independence using the Glasgow Outcome Scale Extended (GOSE) and their quality of life using the Medical Outcomes Study Short Form General Health Survey (SF-12) via a telephone call.\n\nWe plan to include 220 patients and approximately 70 clinicians across 8 recruiting centers over a 2-year enrollment period. With a 12-month follow-up period, the total duration of the study will be 3 years.\n\nThe statistical analysis will include a description of clinicians' ability to distinguish patient prognosis by measuring the area under the Receiver Operating Characteristic (ROC) curve, or AUC. The prediction concerns an unfavorable outcome, defined as a GOSE score of 1 to 4. Since we had no pre-study data on clinicians' performance in predicting an unfavorable outcome at the time of a prognostic MRI, the inclusion target was set based on data from a previous study at 220 patients, which corresponds to the number of patients we planned to enroll over a 2-year period.",[24],"Diffusion Tensor Imaging Prognosis",[26,27,28,29,30],"diffusion tensor imaging","delayed awakening","clinicians'prognosis","prediction","brain injury","NOT_YET_RECRUITING","2026-10-02",{"date":34,"type":35},"2026-10-07","ACTUAL",{"date":37,"type":20},"2026-11",{"date":39,"type":20},"2030-01",{"name":41,"class":42},"Assistance Publique - Hôpitaux de Paris","OTHER",8]