Child Neurology: Arterial ischemic stroke in a 12-year-old patient with cardiac myxomas

Coffee, Elizabeth; Sankhla, Neal; Bass, Rachel; Dure, Leon S.; Rashid, Shazia

doi:10.1212/wnl.0000000000009060

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…10 A literature review on pediatric cardiac myxoma by Tona et al identified 43 published pediatric cases of stroke caused by cardiac myxoma, with a subsequent three additional cases noted since publication. 3,11,12 Endovascular thrombectomy and timing of surgical myxoma resection was available for seven patients (15%), ranging from one to ten days (1 day [n = 1], 2 days [n = 4], 7 days [n = 1], 10 days [n = 1]). Thrombolysis in cerebral infarction score of 3 was reported in three cases, TICI 2b was reported in two cases, and two other cases did not report their achieved TICI scores.…”

Section: Discussionmentioning

confidence: 99%

Early Surgical Resection of Left Atrial Myxoma After Thromboembolic Stroke

Martin,

Devejian,

Paul

et al. 2023

World J Pediatr Congenit Heart Surg

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Section: Discussionmentioning

confidence: 99%

Early Surgical Resection of Left Atrial Myxoma After Thromboembolic Stroke

Martin,

Devejian,

Paul

et al. 2023

World J Pediatr Congenit Heart Surg

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“…Although several risk factors of embolism (i.e., size of tumor and sex) (11, 12) in CM-IS patients have been reported, they are still controversial. Currently, the occurrence of CM-IS is believed to result from the interaction of multiple risk factors such as age (13)(14)(15), sex (12, [16][17][18], past medical history (19,20), and tumor characteristics (21)(22)(23).…”

Section: Introductionmentioning

confidence: 99%

Risk factors assessment and a Bayesian network model for predicting ischemic stroke in patients with cardiac myxoma

Cai

Qiao

et al. 2023

Front. Cardiovasc. Med.

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ObjectiveThis study aims to identify relevant risk factors, assess the interactions between variables, and establish a predictive model for ischemic stroke (IS) in patients with cardiac myxoma (CM) using the Bayesian network (BN) approach.MethodsData of patients with CM were collected from three tertiary comprehensive hospitals in Beijing from January 2002 to January 2022. Age, sex, medical history, and information related to CM were extracted from the electronic medical record system. The BN model was constructed using the tabu search algorithm, and the conditional probability of each node was calculated using the maximum likelihood estimation method. The probability of each node of the network and the interrelationship between IS and its related factors were qualitatively and quantitatively analyzed. A receiver operating characteristic (ROC) curve was also plotted. Sensitivity, specificity, and area under the curve (AUC) values were calculated and compared between the BN and logistic regression models to evaluate the efficiency of the predictive model.ResultsA total of 416 patients with CM were enrolled in this study, including 61 with and 355 without IS. The BN model found that cardiac symptoms, systemic embolic symptoms, platelet counts, and tumor with high mobility were directly associated with the occurrence of IS in patients with CM. The BN model for predicting CM-IS achieved higher scores on AUC {0.706 [95% confidence interval (CI), 0.639–0.773]} vs. [0.697 (95% CI, 0.629–0.766)] and sensitivity (99.44% vs. 98.87%), but lower scores on accuracies (85.82% vs. 86.06%) and specificity (6.56% vs. 11.48%) than the logistic regression model.ConclusionCardiac symptoms, systemic embolic symptoms, platelet counts, and tumor with high mobility are candidate predictors of IS in patients with CM. The BN model was superior or at least non-inferior to the traditional logistic regression model, and hence is potentially useful for early IS detection, diagnosis, and prevention in clinical practice.

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