Dataset Information

A Conditional Inference Tree Model for Predicting Sleep-Related Breathing Disorders in Patients With Chiari Malformation Type 1: Description and External Validation.

ABSTRACT:

Study objectives

The aim of this study is to generate and validate supervised machine learning algorithms to detect patients with Chiari malformation (CM) 1 or 1.5 at high risk of the development of sleep-related breathing disorders (SRBD) using clinical and neuroradiological parameters.

Methods

We prospectively included two independent datasets. A training dataset (n = 90) was used to obtain the best model, whereas a second dataset was used to validate it (n = 74). In both cohorts, the same clinical, neuroradiological, and sleep studies were carried out. We used two supervised machine learning approaches, multiple logistic regression (MLR) and the unbiased recursive partitioning technique conditional inference tree (URP-CTREE), to detect patients at high risk of SRBD. We then compared the accuracy, sensitivity, and specificity of the two prediction models.

Results

Age (odds ratio [OR] 1.1 95% confidence interval [CI] 1.05-1.17), sex (OR 0.19 95% CI 0.05-0.67), CM type (OR 4.36 95% CI 1.14-18.5), and clivus length (OR 1.14 95% CI 1.01-1.31) were the significant predictor variables for a respiratory disturbance index (RDI) cutoff that was ? 10 events/h using MLR. The URP-CTREE model predicted that patients with CM-1 who were age 52 years or older and males with CM-1 who were older than 29 years had a high risk of SRBD. The accuracy of predicting patients with an RDI ? 10 events/h was similar in the two cohorts but in the URP-CTREE model, specificity was significantly greater when compared to MLR in both study groups.

Conclusions

Both MLR and URP-CTREE predictive models are useful for the diagnosis of SRBD in patients with CM. However, URP-CTREE is easier to apply and interpret in clinical practice.

SUBMITTER: Ferre A

PROVIDER: S-EPMC6329533 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

A Conditional Inference Tree Model for Predicting Sleep-Related Breathing Disorders in Patients With Chiari Malformation Type 1: Description and External Validation.

Ferré Álex Á Poca María A MA de la Calzada María Dolore MD Moncho Dulce D Urbizu Aintzane A Romero Odile O Sampol Gabriel G Sahuquillo Juan J

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine 20190115 1

<h4>Study objectives</h4>The aim of this study is to generate and validate supervised machine learning algorithms to detect patients with Chiari malformation (CM) 1 or 1.5 at high risk of the development of sleep-related breathing disorders (SRBD) using clinical and neuroradiological parameters.<h4>Methods</h4>We prospectively included two independent datasets. A training dataset (n = 90) was used to obtain the best model, whereas a second dataset was used to validate it (n = 74). In both cohort ...[more]

PMID: 30621833

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Project description:BackgroundPseudomeningoceles (PMCs) as abnormal collections of cerebrospinal fluid are quite common findings on follow-up MRI after Chiari decompression surgery (CDS). However, the importance of their identification has not been truly determined, especially when PMCs are described occasionally in the process of radiological follow-up. We retrospectively analyzed surgical outcomes and imaging findings after CDS depending upon the occurrence and thickness of PMCs.MethodsA total of 76 adult patients who underwent CDS were analyzed. The clinical and radiological outcomes of patients with a pseudomeningocele (wPMC) were evaluated and compared to those of patients without a pseudomeningocele (w/oPMC). Radiological morphometric measurements were performed and compared between groups. Comparisons of the maximal PMC thickness were made within the wPMC group.ResultsPMCs were recognized in 27 (35.5%) patients, of whom 3 (11.1%) required reoperation. Differences in satisfactory result rates regarding gestalt assessment and Chicago Chiari Outcome Scale were statistically insignificant between the w/oPMC and wPMC groups (p = 1 and p = 0.56, respectively). The postoperative syringomyelia decrease and cerebellar tonsil elevation were similar between the groups (p = 1 and p = 0.74, respectively) in the long-term follow-up. Additionally, the clinical or radiological outcomes with radiological details were not related to PMC thickness in the long-term follow-up. However, radiological details showed the cooccurrence of PMCs with a postsurgical of cerebello-tentorial distance increase (p < 0.05), basion-pontomedullary sulcus distance decrease (p < 0.05) and tonsillo-graft distance decrease (p < 0.05).ConclusionsWe found no significant relationships between PMC presence or thickness and clinical or radiological outcomes. However, postoperative changes within the posterior fossa associated with PMCs resemble brain sagging, which occurs in intracranial hypotension. Therefore, extradural cerebrospinal fluid escape may also be responsible for symptoms in some patients with PMCs after CDS.

Project description:OBJECT:Chiari malformation Type I (CM-I) is characterized by hindbrain deformity. We investigated the effects of craniocervical decompression surgery on the anatomical features of hindbrain deformity with a prospective MRI study of patients with CM-I. METHODS:A prospective longitudinal study was conducted in 48 patients with CM-I (39 with syringomyelia) treated with craniocervical decompression. Clinical examinations and cervical MRI were performed before surgery and 1 week, 3-6 months, and annually after surgery. Hindbrain deformity was defined by tonsillar ectopia, pointed cerebellar tonsils, and/or cervicomedullary protuberance. The length of the clivus, basiocciput (sphenooccipital synchondrosis to basion), supraocciput (internal occipital protuberance to opisthion), and anteroposterior (AP) width of CSF pathways at the foramen magnum were measured and compared with those from 18 healthy volunteers (control group). RESULTS:Before surgery, the patients' posterior fossa bones were short and their CSF pathways were narrow. All patients had tonsillar ectopia (mean [± SD] 12.3 ± 5.1 mm; normal 0.3 ± 1.0). The majority of patients had pointed tonsils and more than two-thirds exhibited a cervicomedullary protuberance. Clivus and basiocciput lengths were significantly shorter than the values obtained in the control group. However, the supraocciput length did not differ significantly from control measurements. The mean bulbopontine sulcus distance superior to the basion was 9.5 ± 2.6 mm (vs 13.6 ± 2.8 mm in controls; p < 0.0001). The AP widths of the CSF pathways at the level of the foramen magnum were significantly narrowed. After surgery, CSF pathways significantly expanded both ventrally and dorsally. By 3-6 months after surgery, pointed tonsils became round, cervicomedullary protuberance disappeared, and tonsillar ectopia diminished by 51% (to 6.0 ± 3.3 mm; p < 0.0001). CONCLUSIONS:The cerebellar tonsils and brainstem assumed a normal appearance within 6 months after craniocervical decompression. These findings support the concept that the CM-I is not a congenital malformation of the neural elements but rather an acquired malformation that arises from pulsatile impaction of the cerebellar tonsils into the foramen magnum. Clinical trial registration no.: NCT00001327.

Dataset Information

A Conditional Inference Tree Model for Predicting Sleep-Related Breathing Disorders in Patients With Chiari Malformation Type 1: Description and External Validation.

Study objectives

Methods

Results

Conclusions

Publications

A Conditional Inference Tree Model for Predicting Sleep-Related Breathing Disorders in Patients With Chiari Malformation Type 1: Description and External Validation.

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