The value of serum uric acid levels to differentiate causes of transient loss of consciousness

Serum uric acid predicts therapeutic response to midodrine hydrochloride in children with vasovagal syncope: a pilot study

Serum uric acid (UA) level has been proven to be related to several cardiovascular and metabolic diseases. In the present study, we examined if baseline serum UA level could predict the therapeutic efficacy of midodrine hydrochloride on vasovagal syncope (VVS) in children. The pediatric VVS patients who received midodrine hydrochloride from November 2008 to October 2022 were enrolled. After a median treatment duration of 3 months, the therapeutic effect was evaluated. According to the patients' responses to midodrine hydrochloride, which was determined by the recurrence of syncope, they were divided into effective and ineffective groups. The baseline variables were explored using univariable and multivariate logistic analysis. The predictive efficacy was assessed by receiver operating characteristic curve (ROC), precision-recall curve (PR), Hosmer-Lemeshow test, calibration curve, and decision curve analysis (DCA). Totally, 53 participants were included in the study. Among the 51 patients who were successfully followed up, 29 (56.9%) responded to midodrine hydrochloride (effective group), and the other 22 (43.1%) failed to respond to midodrine hydrochloride (ineffective group). The participants in effective group had lower baseline serum UA level than those in ineffective group (276.5 ± 73 μmol/L vs. 332.7 ± 56 μmol/L, p = 0.004). Multivariable logistic analysis showed that serum UA was associated with the therapeutic response (odds ratio (OR): 0.985, 95% confidence interval (CI): 0.974-0.997, p = 0.01). ROC analysis indicated that using baseline serum UA < 299 μmol/L as a threshold value yielded a sensitivity of 77.3% and a specificity of 79.3% in predicting the treatment response to midodrine hydrochloride. The area under the PR curve was 0.833. Hosmer-Lemeshow test yielded a p value of 0.58, and calibration plot indicated that the model was well-fitted. DCA demonstrated that treatment decision depending on the baseline serum UA level resulted in a favorable net benefit.   Conclusion: This pilot study suggested that the baseline serum UA level could be taken as a predictor of therapeutic effect of midodrine hydrochloride on VVS in children. What is Known: • Empirical and unselected use of midodrine hydrochloride has an unfavorable therapeutic effect on VVS in children. Serum uric acid (UA) is closely linked to cardiovascular events. What is New: • A low baseline serum UA level successfully predicts the therapeutic effectiveness of midodrine hydrochloride on VVS in children.

Differentiation of epilepsy and psychogenic nonepileptic events based on body fluid characteristics

OBJECTIVE

Differential diagnosis between epileptic seizures and psychogenic nonepileptic events (PNEEs) is a worldwide problem for neurologists. The present study aims to identify important characteristics from body fluid tests and develop diagnostic models based on them.

METHODS

This is a register-based observational study in patients with a diagnosis of epilepsy or PNEEs at West China Hospital of Sichuan University. Data from body fluid tests between 2009 and 2019 were used as a training set. We constructed models with a random forest approach in eight training subsets divided by sex and categories of tests, including electrolyte, blood cell, metabolism, and urine tests. Then, we collected data prospectively from patients between 2020 and 2022 to validate our models and calculated the relative importance of characteristics in robust models. Selected characteristics were finally analyzed with multiple logistic regression to establish nomograms.

RESULTS

A total of 388 patients, including 218 with epilepsy and 170 with PNEEs, were studied. The AUROCs of random forest models of electrolyte and urine tests in the validation phase achieved 80.0% and 79.0%, respectively. Carbon dioxide combining power, anion gap, potassium, calcium, and chlorine in electrolyte tests and specific gravity, pH, and conductivity in urine tests were selected for the logistic regression analysis. C (ROC) of the electrolyte and urine diagnostic nomograms achieved 0.79 and 0.85, respectively.

SIGNIFICANCE

The application of routine indicators of serum and urine may help in the more accurate identification of epileptic and PNEEs.

ES-RED (Early Seizure Recurrence in the Emergency Department) Calculator: A Triage Tool for Seizure Patients

Seizure is a common neurological presentation in patients visiting the emergency department (ED) that requires time for evaluation and observation. Timely decision and disposition standards for seizure patients need to be established to prevent overcrowding in the ED and achieve patients’ safety. Here, we conducted a retrospective cohort study to predict early seizure recurrence in the ED (ES-RED). We randomly assigned 688 patients to the derivation and validation cohorts (2:1 ratio). Prediction equations extracted routine clinical and laboratory information from EDs using logistic regression (Model 1) and machine learning (Model 2) methods. The prediction equations showed good predictive performance, the area under the receiver operating characteristics curve showing 0.808 in Model 1 [95% confidential interval (CI): 0.761–0.853] and 0.805 in Model 2 [95% CI: 0.747–0.857] in the derivation cohort. In the external validation, the models showed strong prediction performance of 0.739 [95% CI: 0.640–0.824] in Model 1 and 0.738 [95% CI: 0.645–0.819] in Model 2. Intriguingly, the lowest quartile group showed no ES-RED after 6 h. The ES-RED calculator, our proposed prediction equation, would provide strong evidence for safe and appropriate disposition of adult resolved seizure patients from EDs, reducing overcrowding and delays and improving patient safety.

Can Assessment of the Tongue on Brain MRI Aid Differentiation of Seizure from Alternative Causes of Transient Loss of Consciousness?

BACKGROUND AND PURPOSE

Transient loss of consciousness is commonly evaluated in the emergency department. Although typically caused by epileptic seizure, syncope, or psychogenic nonepileptic seizure, the underlying etiology is frequently misdiagnosed. Lateral tongue bites are reportedly a specific clinical finding of seizure. We have observed tongue signal abnormality suggesting bite injury on brain MR imaging after seizures. We hypothesized an association between tongue signal abnormality and seizure diagnosis among patients in the emergency department imaged for transient loss of consciousness. Our purposes were to determine the prevalence of tongue signal abnormality among this population and the predictive performance for seizure diagnosis.

MATERIALS AND METHODS

For this retrospective study including 82 brain MR imaging examinations, 2 readers independently assessed tongue signal abnormality on T2-weighted and T2-weighted FLAIR images. Discrepancies were resolved by consensus, and interrater reliability (Cohen κ) was calculated. The final diagnosis was recorded. Proportions were compared using the Fisher exact test.

RESULTS

Tongue signal abnormality was present on 19/82 (23%) MR imaging examinations. Interrater reliability was "substantial" (κ = 0.77). Seizure was diagnosed among 18/19 (95%) patients with tongue signal abnormality and 29/63 (46%) patients without it (P < .001). In our cohort, tongue signal abnormality conveyed 97% specificity, 95% positive predictive value, and 63% accuracy for seizure diagnosis.

CONCLUSIONS

Tongue signal abnormality was observed in 23% of the study cohort and conveyed 97% specificity and 95% positive predictive value for seizure diagnosis. By assessing and reporting tongue signal abnormality, radiologists may facilitate a timely and accurate diagnosis of seizure among patients imaged for transient loss of consciousness.

Association of Hyperuricemia With Acute Kidney Injury: Case Series Report Among Patients Hospitalized With General Tonic-Clonic Seizures

Background:

Urate nephropathy is a rare cause of acute kidney injury. Although most risk factors are associated with chemotherapy, tumor lysis syndrome or rhabdomyolysis, occurrence following severe seizure has also been reported. Uric acid measurement following convulsion is rarely performed and, therefore, the incidence of hyperuricemia in this context is unknown.

Objective:

The objective is to present a case of urate nephropathy following generalized tonic-clonic seizure (GTCS) and to investigate the kinetics of serum uric acid and creatinine levels in a series of patients admitted for severe seizures.

Design:

Retrospective case report and prospective case series.

Setting:

Emergency room department and neurology unit of a tertiary care hospital.

Patients:

The study included 13 hospitalized patients for severe GTCS.

Measurements:

Type, timing, and duration of seizure episodes were documented. Demographic data, weight, hypouricemic therapy, and baseline serum creatinine were recorded. Blood samples (uric acid, creatinine, blood gas, lactate, and creatinine kinase) and urine samples (uric acid, creatinine, and dipstick) were prospectively collected at Day 0, 1, 2, and 3 following the GTCS episode.

Methods:

We identified and described one rare case of urate nephropathy following GTCS. Then, we presented the kinetic of uric acid and creatinine levels and the acute kidney injury incidence over the follow-up period. All analyses were using descriptive statistics.

Results:

During the study period, 13 patients with a median tonic-clonic seizure duration of 5.0 minutes (interquartile range [IQR], 2.0–12.5) were included. From day 0 to day 3, the median serum uric acid level decreased from 346.0 µmol/L (IQR, 155.0–377.5) to 178.0 µmol/L (IQR, 140.0–297.5) and median serum creatinine from 73.0 µmol/L (IQR, 51.0–80.0) to 57.0 µmol/L (IQR, 44.0–70.0). Acute kidney injury occurred in four patients.

Limitations:

This is a single-center observational study with small sample size, which does not allow us to demonstrate causality between the increase of uric acid levels observed and the occurrence of acute kidney injury. A delay between the first sampling and seizure episodes was observed and could explain the limited increase of uric acid levels captured.

Conclusions:

There is a signal for an acute increase of uric acid levels following a severe seizure before returning to baseline within 3 days. During that period, there might be an increased risk of acute kidney injury, although these changes seem to be usually mild and reversible. Our findings suggest that routine serum uric acid measurement in patients presenting with GTCS could help to identify those patients at risk of developing acute kidney injury as a result of acute hyperuricemia. Further larger studies are required to confirm the effectiveness of such screening in acute kidney injury prevention.

Trial Registration:

As an observational noninterventional study, no registration was required.