Clinical trial NCT06633848: Establishment of Clinical Prediction Model for Postoperative Symptomatic Spinal Epidural Hematoma
Official title: Establishment of Artificial Intelligence Algorithms Based Clinical Prediction Model for Patients with Postoperative Symptomatic Spinal Epidural Hematoma After Spinal Surgery
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Spinal Epidural Hematoma
Keywords: artificial intelligence algorithm
clinical prediction model
postoperative symptomatic spinal epidural hematoma
Lead sponsor: Peking University Third Hospital
Sponsor class: OTHER
First posted: 2024-10-09
Enrollment: 2000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: patients with spinal disorders who come to Peking University Third Hospital for treatment

Brief summary: The goal of this observational study is to establish a clinical prediction model based on artificial intelligence algorithms for patients with postoperative symptomatic spinal epidural hematoma(PSSEH) after spinal surgery. The investigators will collect the features of 2000 patients as the training set to train the models using AI algorithms, then recruit a prospective cohort of 2000 patients to test if the trained model is precise and consistent to predict the occurrence of PSSEH as well as to find out whether there is any new risk factor of PSSEH.

Detailed description: Firstly, the investigators plan to collect the features of 2000 patients who received spinal surgery at Peking University Third Hospital from January 2014 to December 2024, including those with PSSEH and the controls, as the training set to build up a prediction model based on multiple AI algorithms. Then, the investigators will choose the optimal model through comparing various features, assessing the robustness of the model quantitatively using k-fold cross validation and exploring the influence of all features on the output of the final model by means such as SHAP. Lastly, the investigators will recruit a prospective cohort of approximately 2000 patients who receive spinal surgery from January 2025 to December 2026 at Peking University Third Hospital and collect the same features as the training set to test if the trained prediction model is precise and consistent to predict the occurrence of PSSEH and whether there is any feature , undiscovered before, that is strongly related to PSSEH.

Eligibility criteria: Inclusion Criteria:

* patients who will receive spinal surgery from January 2025 to December 2026 at Peking University Third Hospital

Exclusion Criteria:

* patients with a history of lumbar trauma before admission;
* patients who suffer from malignant tumor;
* patients with systemic infection;
* patients who quit the study midway

Primary outcomes:
measure: if the patients have postoperative symptomatic spinal epidural hematoma
timeFrame: within 2 weeks after spinal surgery
Secondary outcomes:
Other outcomes:
Locations:
Study officials:
References:
citation: Negulyaev YA, Markwardt F. Block by extracellular Mg2+ of single human purinergic P2X4 receptor channels expressed in human embryonic kidney cells. Neurosci Lett. 2000 Feb 4;279(3):165-8. doi: 10.1016/s0304-3940(99)00976-3.
citation: Goldstein CL, Bains I, Hurlbert RJ. Symptomatic spinal epidural hematoma after posterior cervical surgery: incidence and risk factors. Spine J. 2015 Jun 1;15(6):1179-87. doi: 10.1016/j.spinee.2013.11.043. Epub 2013 Dec 6.
citation: Xia T, Zhou F, Chu H, Tan LA, Sun Y, Wang S. Incidence and risk factors of postoperative symptomatic spinal epidural hematoma in cervical spine surgery: a single center, retrospective study of 18,220 patients. Eur Spine J. 2022 Oct;31(10):2753-2760. doi: 10.1007/s00586-022-07301-z. Epub 2022 Jul 10.
citation: Chen Q, Zhong X, Liu W, Wong C, He Q, Chen Y. Incidence of postoperative symptomatic spinal epidural hematoma requiring surgical evacuation: a systematic review and meta-analysis. Eur Spine J. 2022 Dec;31(12):3274-3285. doi: 10.1007/s00586-022-07421-6. Epub 2022 Oct 19.