Post-traumatic hydrocephalus: the Cinderella of Neurotrauma

et al. 2022

Preprint

Background: Post-hemorrhagic hydrocephalus (PHH) is a common complication of cerebral, ventricular, and subarachnoid hemorrhage, and craniocerebral injury. There is lacking research on risk factors and prediction models associated with PHH. This present study aimed to analyze the risk factors of PHH and establish a risk-scoring system through a large-scale study. Methods: A retrospective study of 382 patients with intracranial hemorrhage assessed age, history and diagnosis, Glasgow coma score (GCS), and fever duration. After univariate and logistic regression analysis, risk scoring system was established according to independent risk factors. Area under curve (AUC) was used to evaluate the scoring system and validate the accuracy of the dataResults: Of the 382 patients, 133 (34.8%) had PHH, 43 (11.3%) received surgical treatment. We determined the age, GCS, days (total fever time when body temperature ≥ 38.5◦C), and cerebrospinal fluid total protein (CSF-TP) x time (from the onset of the disease to the obtainment of CSF-TP after lumbar puncture) as the important risk factors for PHH. Factor classification showed that age > 60 years old [odds ratio (OR): 0.347, II = 5 points], GCS < 5 (OR: 0.09, IV = 10 points), GCS 6-8 (OR = 0.232, III = 6 points), fever days > 9 (OR: 0.202, III = 7 points), fever days 5-9 (OR: 0.341, II = 5 points), CSF-TP x time > 14,4000 group (OR: 0.267, IV = 6 points), and CSF-TP x time 9,601-14,400 group (OR: 0.502, III = 3 points) were independent risk factors. The result of the receiver operating characteristic (ROC) prediction showed that AUC = 0.790 (0.744-0.836). Low-risk (IV-VII), moderate (VIII-X), and high-risk group (XI-XIII) incidence of PHH, respectively: 11.76%, 50.55%, and 70.00% (p < 0.001). The coincidence rates in the validation cohort were 26.00%, 74.07%, and 100.0% (p < 0.001), respectively. AUC value was 0.860 (0.780 - 0.941).Conclusion: The predictive model was conducive in determining the occurrence of PHH and facilitating early intervention.

Section: Pathogenesis Of Phhmentioning

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Section: Risk Factors Of Phhmentioning

confidence: 99%

See 1 more Smart Citation

Prediction of Adult Post-hemorrhagic Hydrocephalus: A Risk Score Based on Clinical Data

et al. 2022

Preprint

“…The incidence of hydrocephalus occurring after subarachnoid hemorrhage varies between 15 and 37%, of which approximately 17‒21% require permanent cerebrospinal fluid (CSF) shunt operations 16 . The incidence of hydrocephalus after TBI ranges from 10.84% to 29% 17 , 18 . In the clinic, we often encounter such phenomena: ICH accompanied by hematoma breaking into the ventricle; IVH extending into subarachnoid space and; SAH may accumulate in the ventricle or be accompanied by a hematoma.…”

Section: Discussionmentioning

confidence: 99%

Prediction of adult post-hemorrhagic hydrocephalus: a risk score based on clinical data

et al. 2022

Sci Rep

There is lacking research on risk factors and prediction models associated with Post-hemorrhagic hydrocephalus (PHH). Thus, this present study aimed to analyze the risk factors of PHH and establish a risk-scoring system through a large-scale study. A retrospective study of 382 patients with intracranial hemorrhage assessed age, history and diagnosis, Glasgow coma score (GCS), and fever time. After univariate and logistic regression analysis, a risk scoring system was established according to independent risk factors and evaluated using the area under the curve (AUC). Of the 382 patients, 133 (34.8%) had PHH, 43 (11.3%) received surgical treatment. Factor classification showed that age > 60 years old [odds ratio (OR): 0.347, II = 5 points], GCS < 5 (OR: 0.09, IV = 10 points), GCS 6‒8 (OR = 0.232, III = 6 points), fever time > 9 (OR: 0.202, III = 7 points), fever time 5–9 (OR: 0.341, II = 5 points), CSF-TP x time > 14,4000 group (OR: 0.267, IV = 6 points), and CSF-TP x time 9,601‒14,400 group (OR: 0.502, III = 3 points) were independent risk factors. The result of the receiver operating characteristic (ROC) prediction showed that AUC = 0.790 (0.744‒0.836). Low-risk (IV-VII), moderate (VIII-X), and high-risk group (XI-XIII) incidence of PHH were 11.76%, 50.55%, and 70.00% (p < 0.001), respectively. The coincidence rates in the validation cohort were 26.00%, 74.07%, and 100.0% (p < 0.001), respectively. AUC value was 0.860 (0.780‒0.941). The predictive model was conducive to determining the occurrence of PHH and facilitating early intervention.

“…ere have been studies evaluating the effect of decompression craniectomy. e main content is to explore the relationship between the treatment effect and surgical complications [5].…”

Section: Introductionmentioning

confidence: 99%

Neural Network Segmentation Algorithm-Based Magnetic Resonance Imaging to Explore the Relationship between Cerebrospinal Fluid Flow with Communicating Hydrocephalus after Decompressive Craniectomy for Craniocerebral Injury

Zhang

2021

Scientific Programming

This study aimed to explore the application value of magnetic resonance imaging optimized by neural network segmentation algorithm in analyzing the relationship between cerebrospinal fluid changes after decompressive craniectomy and the occurrence of communicating hydrocephalus. 100 patients with craniocerebral injury undergoing decompressive craniectomy in hospital were selected as research subjects. The collected MRI images were processed using the OTSU algorithm, the cerebrospinal fluid flow rate was calculated based on the observation results, and the MRI based on the neural network segmentation algorithm was used to analyze the relationship between the occurrence of communicating hydrocephalus with the cerebrospinal fluid flow after decompressive craniectomy for craniocerebral injury. Additionally, the dynamics of the flow of cerebrospinal fluid in the midbrain aqueduct was analyzed. After decompressive craniectomy for craniocerebral injury, of the 24 cases of cerebrospinal fluid accumulation, 23 cases had hydrocephalus; of the 55 cases of cerebrospinal fluid flow disorder, hydrocephalus occurred in 47 cases; and of the 21 cases of normal cerebrospinal fluid, no patients had hydrocephalus. For patients with communicating hydrocephalus, the cerebrospinal fluid flow at the aqueduct was obviously accelerated and the flow was increased. From this, the differential diagnosis of cerebrospinal fluid and communicating hydrocephalus can be further confirmed. The results showed that the third ventricle of the study group was significantly reduced, and the flow of cerebrospinal fluid was similar to that of normal people. It suggested that decompressive craniectomy can relieve communicating hydrocephalus. In patients with communicating hydrocephalus, the cerebrospinal fluid flow at the aqueduct was significantly accelerated, the flow amount was increased, and the blocked flow of cerebrospinal fluid can also lead to hydrocephalus, which further clarified the relationship between the occurrence of communicating hydrocephalus with the flow of cerebrospinal fluid. In short, the neural network segmentation algorithm-based magnetic resonance imaging demonstrated a good value in the analysis of craniocerebral injury, from which the doctor observed that the cerebrospinal fluid flow at the aqueduct was significantly accelerated. Its detection of brain complications after decompressive craniectomy was also effective.