Study on the Prognostic Prediction Model of Patients With Acute Intracerebral Hemorrhage by Artificial Intelligence

NCT05424614 | Unknown

• 1 other identifier: 2022-2-1074
• Study Type: observational
• Target: 150
• Locations: 1 country
• Sites: 1

Brief Summary

Spontaneous intracerebral hemorrhage(SICH) is the most lethal and disabling stroke. Timely and accurate assessment of patient prognosis could facilitate clinical decision making and stratified management of patients and is important for improving patient clinical prognosis. However, current studies on the prediction of prognosis of patients with SICH are limited and only include a single variable, with less precise results and inconvenient clinical application, which may lead to delays in effective patient treatment. Our group's previous studies on SICH showed that hematoma heterogeneity and the degree of contrast extravasation within the hematoma are closely related to the clinical outcome of patients, but they are difficult to describe quantitatively based on imaging signs. Based on this, we propose to use radiomics to quantitatively extract hematoma features from NCCT and CTA images, combine them with patients' clinical information and laboratory tests, study their relationship with the prognosis of cerebral hemorrhage, and use artificial intelligence to establish a rapid and accurate prognostic prediction model for patients with SICH, which is of great significance to guide clinical individualized treatment.

Conditions

Cerebral Hemorrhage; Prognosis; Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• patient outcome

  Neurological recovery status was measured by the modified Rankin Scale

  3 month

Study Arms (1)

intracerebral hemorrhage group

Patients with the intracerebral hemorrhage who presented to the hospital within 24 hours of symptom onset

Other: Functional outcome follow-up of patients

Interventions

Functional outcome follow-up of patients OTHER

Patients were followed up by telephone after discharge, every 4 weeks, until the end of the 3-month follow-up. Their functional status was determined based on the MRS score (modified Rankin Scale). Those with less than 3 points were defined as having a good prognosis, and those with more than 3 points were defined as having a poor prognosis

intracerebral hemorrhage group

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with acute cerebral hemorrhage (within 6 hours of the onset of symptoms) who presented to the hospital between May 2022 and September 2024 and had complete medical records.

You may qualify if:

• \. aged 18-80 years; 2. patients diagnosed with acute cerebral hemorrhage by CT examination; 3. complete non-contrast CT and CTA images; 4. the time interval from onset to the first baseline CT and CTA examination is less than 6 hours; 5. follow-up data within 3 months; 6. agree and sign a written document.

You may not qualify if:

• \. Patients with secondary aneurysm hemorrhage; 2. Patients with secondary hemorrhage of cerebrovascular malformation; 3. Patients with dissecting aneurysm hemorrhage; 4. Patients with cerebral infarction hemorrhage transformation; 5. Patients lost to follow-up within 3 months; 6. CT or CTA images have a heavy artefact.

Sponsors & Collaborators

• Beijing Neurosurgical Institute: lead

Study Sites (1)

Beijing Tiantan Hospital, Capital Medical University

Beijing, Beijing Municipality, 100070, China

RECRUITING

Related Publications (9)

• Pszczolkowski S, Manzano-Patron JP, Law ZK, Krishnan K, Ali A, Bath PM, Sprigg N, Dineen RA. Quantitative CT radiomics-based models for prediction of haematoma expansion and poor functional outcome in primary intracerebral haemorrhage. Eur Radiol. 2021 Oct;31(10):7945-7959. doi: 10.1007/s00330-021-07826-9. Epub 2021 Apr 16.

  PMID: 33860831 BACKGROUND

• Xie H, Ma S, Wang X, Zhang X. Noncontrast computer tomography-based radiomics model for predicting intracerebral hemorrhage expansion: preliminary findings and comparison with conventional radiological model. Eur Radiol. 2020 Jan;30(1):87-98. doi: 10.1007/s00330-019-06378-3. Epub 2019 Aug 5.

  PMID: 31385050 BACKGROUND

• Guo R, Zhang R, Liu R, Liu Y, Li H, Ma L, He M, You C, Tian R. Machine Learning-Based Approaches for Prediction of Patients' Functional Outcome and Mortality after Spontaneous Intracerebral Hemorrhage. J Pers Med. 2022 Jan 14;12(1):112. doi: 10.3390/jpm12010112.

  PMID: 35055424 BACKGROUND

• Gregorio T, Pipa S, Cavaleiro P, Atanasio G, Albuquerque I, Chaves PC, Azevedo L. Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis. BMC Med Res Methodol. 2018 Nov 20;18(1):145. doi: 10.1186/s12874-018-0613-8.

  PMID: 30458727 BACKGROUND

• Fu F, Sun S, Liu L, Gu H, Su Y, Li Y. Iodine Sign as a Novel Predictor of Hematoma Expansion and Poor Outcomes in Primary Intracerebral Hemorrhage Patients. Stroke. 2018 Sep;49(9):2074-2080. doi: 10.1161/STROKEAHA.118.022017.

  PMID: 30354984 BACKGROUND

• Wang J, Wang W, Liu Y, Zhao X. Associations Between Levels of High-Sensitivity C-Reactive Protein and Outcome After Intracerebral Hemorrhage. Front Neurol. 2020 Oct 6;11:535068. doi: 10.3389/fneur.2020.535068. eCollection 2020.

  PMID: 33123072 BACKGROUND

• Menon G, Johnson SE, Hegde A, Rathod S, Nayak R, Nair R. Neutrophil to lymphocyte ratio - A novel prognostic marker following spontaneous intracerebral haemorrhage. Clin Neurol Neurosurg. 2021 Jan;200:106339. doi: 10.1016/j.clineuro.2020.106339. Epub 2020 Oct 28.

  PMID: 33183885 BACKGROUND

• Morotti A, Arba F, Boulouis G, Charidimou A. Noncontrast CT markers of intracerebral hemorrhage expansion and poor outcome: A meta-analysis. Neurology. 2020 Oct 6;95(14):632-643. doi: 10.1212/WNL.0000000000010660. Epub 2020 Aug 26.

  PMID: 32847959 BACKGROUND

• Tseng WC, Wang YF, Wang TG, Hsiao MY. Early spot sign is associated with functional outcomes in primary intracerebral hemorrhage survivors. BMC Neurol. 2021 Mar 20;21(1):131. doi: 10.1186/s12883-021-02146-3.

  PMID: 33743639 BACKGROUND

MeSH Terms

Conditions

Cerebral Hemorrhage

Condition Hierarchy (Ancestors)

Intracranial Hemorrhages; Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases; Hemorrhage; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Shengjun Sun

  Beijing Neurosurgical Instuitute

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Shengjun Sun

CONTACT

13611293369; sunshengjun0212@163.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 15, 2022
• First Posted: June 21, 2022
• Study Start: May 13, 2022
• Primary Completion: September 30, 2024
• Study Completion: December 30, 2024
• Last Updated: June 21, 2022

Record last verified: 2022-05

Locations

CN (1)