Oral and topical analgesia in pediatric electrodiagnostic studies.

INTRODUCTION/AIMS: Electrodiagnostic examinations, such as nerve conduction studies (NCS) and needle electromyography (EMG), are perceived as painful by children and their parents/guardians. Methods to reduce peri-procedural pain improve compliance and have neurocognitive and neuropsychiatric benefits. This study aimed to assess the efficacy of combined oral and topical analgesics (COTA), oral analgesics (OA), and placebo in reducing pain during NCS/EMG in children. METHODS: We performed a double-blind, randomized, placebo-controlled trial on children presenting to our neurophysiology lab. Patients were stratified into two age groups (6M-6Y and 7Y-18Y) and randomized into three arms: COTA, OA, and placebo. Pain scores post-NCS/EMG were assessed using the Modified Behavioral Pain Scale (MBPS) and Faces Pain Scale-Revised (FPS-R). RESULTS: One hundred thirteen participants were enrolled. A comparison of participants from both age groups combined revealed no significant differences in guardian FPS-R scores across all arms for NCS and EMG. A significant difference in the distribution of post-NCS FPS-R score severities in children aged 7Y-18Y was noted between OA and placebo (p = .007). EMG was more painful than NCS across all arms (p < .05). In children aged 6M-6Y undergoing at least 10 muscle samplings during EMG, those receiving COTA had significantly lower pain scores (p = .014). DISCUSSION: This study reveals the complexity of pediatric pain perception during NCS/EMG and highlights that other methods to reduce experienced pain are required. Our findings suggest that procedural characteristics, such as number of muscles sampled, may influence the effectiveness of analgesia and serve as a foundation for future research aimed at optimizing pain management strategies.

Should substitution monotherapy or combination therapy be used after failure of the first antiseizure medication? Observations from a 30-year cohort study.

OBJECTIVES: To assess the temporal trends in the use of second antiseizure (ASM) regimens and compare the efficacy of substitution monotherapy and combination therapy after failure of initial monotherapy in people with epilepsy. METHODS: This was a longitudinal observational cohort study conducted at the Epilepsy Unit of the Western Infirmary in Glasgow, Scotland. We included patients who were newly treated for epilepsy with ASMs between July 1982, and October 2012. All patients were followed up for a minimum of 2 years. Seizure freedom was defined as no seizure for at least 1 year on unchanged medication at the last follow up. RESULTS: During the study period, 498 patients were treated with a second ASM regimen after failure of the initial ASM monotherapy, of whom 346 (69%) were prescribed combination therapy and 152 (31%) were given substitution monotherapy. The proportion of patients receiving second regimen as combination therapy increased during the study period from 46% in first epoch (1985-1994) to 78% in the last (2005-2015) (RR = 1.66, 95% CI: 1.17-2.36, corrected-p = .010). Overall, 21% (104/498) of the patients achieved seizure freedom on the second ASM regimen, which was less than half of the seizure-free rate on the initial ASM monotherapy (45%, p < .001). Patients who received substitution monotherapy had similar seizure-free rate compared with those who received combination therapy (RR = 1.17, 95% CI: 0.81-1.69, p = .41). Individual ASMs used, either alone or in combination, had similar efficacy. However, the subgroup analysis was limited by small sample sizes. SIGNIFICANCE: The choice of second regimen used based on clinical judgment was not associated with treatment outcome in patients whose initial monotherapy failed due to poor seizure control. Alternative approaches such as machine learning should be explored to aid individualized selection of the second ASM regimen.

Treatment Outcomes of Newly Diagnosed Epilepsy: A Systematic Review and Meta-analysis.

BACKGROUND AND OBJECTIVES: Understanding the multi-faceted treatment outcomes of newly diagnosed epilepsy is critical for developing rational therapeutic strategies. A meta-analysis was conducted to derive pooled estimates of a range of seizure outcomes in children and adults with newly diagnosed epilepsy commenced on antiseizure medication treatment, and to identify factors associated with different outcomes. METHODS: PubMed/EMBASE were screened for eligible articles between 1 January, 1995 and 1 May, 2021 to include unselected cohort studies with a ≥ 12-month follow-up of seizure outcomes. Proportions of patients seizure free at different follow-up timepoints and their characteristics at the study population level were extracted. The patients were group-wise aggregated using a random-effects model. Primary outcomes were proportions of patients with cumulative 1-year seizure freedom (C1YSF), and 1-year and 5-year terminal seizure freedom (T1YSF and T5YSF). Secondary outcomes included the proportions of patients with early sustained seizure freedom, drug-resistant epilepsy and seizure-free off antiseizure medication at the last follow-up (off antiseizure medications). A separate random-effects meta-analysis was performed for nine predictors of importance. RESULTS: In total, 39 cohorts (total n = 21,139) met eligibility criteria. They included 15 predominantly adult cohorts (n = 12,024), 19 children (n = 6569), and 5 of mixed-age groups (n = 2546). The pooled C1YSF was 79% (95% confidence interval [CI] 74-83). T1YSF was 68% (95% CI 63-72) and T5YSF was 69% (95% CI 62-75). Children had higher C1YSF (85% vs 68%, p < 0.001) and T1YSF than adult cohorts (74% vs 61%, p = 0.007). For secondary outcomes, 33% (95% CI 27-39) of patients achieved early sustained seizure freedom, 17% (95% CI 13-21) developed drug resistance, and 39% (95% CI 30-50) were off antiseizure medications at the last follow-up. Studies with a longer follow-up duration correlated with higher C1YSF (p < 0.001) and being off antiseizure medications (p = 0.045). Outcomes were not associated with study design (prospective vs retrospective), cohort size, publication year, or the earliest date of recruitment. Predictors of importance in newly diagnosed epilepsy include etiology, epilepsy type, abnormal diagnostics (neuroimaging, examination, and electroencephalogram findings), number of seizure types, and pre-treatment seizure burden. CONCLUSIONS: Seizure freedom is achieved with currently available antiseizure medications in most patients with newly diagnosed epilepsy, yet this is often not immediate, may not be sustainable, and has not improved over recent decades. Symptomatic etiology, abnormal neuro-diagnostics, and increased pre-treatment seizure burden and seizure types are important predictors for unfavorable outcomes in newly diagnosed epilepsy. The study findings may be used as a quantitative benchmark on the efficacy of future antiseizure medication therapy for this patient population.

Development and Validation of a Deep Learning Model for Predicting Treatment Response in Patients With Newly Diagnosed Epilepsy.

Importance: Selection of antiseizure medications (ASMs) for epilepsy remains largely a trial-and-error approach. Under this approach, many patients have to endure sequential trials of ineffective treatments until the "right drugs" are prescribed. Objective: To develop and validate a deep learning model using readily available clinical information to predict treatment success with the first ASM for individual patients. Design, Setting, and Participants: This cohort study developed and validated a prognostic model. Patients were treated between 1982 and 2020. All patients were followed up for a minimum of 1 year or until failure of the first ASM. A total of 2404 adults with epilepsy newly treated at specialist clinics in Scotland, Malaysia, Australia, and China between 1982 and 2020 were considered for inclusion, of whom 606 (25.2%) were excluded from the final cohort because of missing information in 1 or more variables. Exposures: One of 7 antiseizure medications. Main Outcomes and Measures: With the use of the transformer model architecture on 16 clinical factors and ASM information, this cohort study first pooled all cohorts for model training and testing. The model was trained again using the largest cohort and externally validated on the other 4 cohorts. The area under the receiver operating characteristic curve (AUROC), weighted balanced accuracy, sensitivity, and specificity of the model were all assessed for predicting treatment success based on the optimal probability cutoff. Treatment success was defined as complete seizure freedom for the first year of treatment while taking the first ASM. Performance of the transformer model was compared with other machine learning models. Results: The final pooled cohort included 1798 adults (54.5% female; median age, 34 years [IQR, 24-50 years]). The transformer model that was trained using the pooled cohort had an AUROC of 0.65 (95% CI, 0.63-0.67) and a weighted balanced accuracy of 0.62 (95% CI, 0.60-0.64) on the test set. The model that was trained using the largest cohort only had AUROCs ranging from 0.52 to 0.60 and a weighted balanced accuracy ranging from 0.51 to 0.62 in the external validation cohorts. Number of pretreatment seizures, presence of psychiatric disorders, electroencephalography, and brain imaging findings were the most important clinical variables for predicted outcomes in both models. The transformer model that was developed using the pooled cohort outperformed 2 of the 5 other models tested in terms of AUROC. Conclusions and Relevance: In this cohort study, a deep learning model showed the feasibility of personalized prediction of response to ASMs based on clinical information. With improvement of performance, such as by incorporating genetic and imaging data, this model may potentially assist clinicians in selecting the right drug at the first trial.

Machine learning models for decision support in epilepsy management: A critical review.

PURPOSE: There remain major challenges for the clinician in managing patients with epilepsy effectively. Choosing anti-seizure medications (ASMs) is subject to trial and error. About one-third of patients have drug-resistant epilepsy (DRE). Surgery may be considered for selected patients, but time from diagnosis to surgery averages 20 years. We reviewed the potential use of machine learning (ML) predictive models as clinical decision support tools to help address some of these issues. METHODS: We conducted a comprehensive search of Medline and Embase of studies that investigated the application of ML in epilepsy management in terms of predicting ASM responsiveness, predicting DRE, identifying surgical candidates, and predicting epilepsy surgery outcomes. Original articles addressing these 4 areas published in English between 2000 and 2020 were included. RESULTS: We identified 24 relevant articles: 6 on ASM responsiveness, 3 on DRE prediction, 2 on identifying surgical candidates, and 13 on predicting surgical outcomes. A variety of potential predictors were used including clinical, neuropsychological, imaging, electroencephalography, and health system claims data. A number of different ML algorithms and approaches were used for prediction, but only one study utilized deep learning methods. Some models show promising performance with areas under the curve above 0.9. However, most were single setting studies (18 of 24) with small sample sizes (median number of patients 55), with the exception of 3 studies that utilized large databases and 3 studies that performed external validation. There was a lack of standardization in reporting model performance. None of the models reviewed have been prospectively evaluated for their clinical benefits. CONCLUSION: The utility of ML models for clinical decision support in epilepsy management remains to be determined. Future research should be directed toward conducting larger studies with external validation, standardization of reporting, and prospective evaluation of the ML model on patient outcomes.

Characteristics and treatment outcomes of newly diagnosed epilepsy in older people: A 30-year longitudinal cohort study.

OBJECTIVES: To describe the clinical characteristics and evaluate the long-term treatment outcomes in older people with newly diagnosed epilepsy over the past 30 years. METHODS: We included patients newly diagnosed with epilepsy and commenced on antiseizure medications (ASMs) at age 65 years or older between July 1982 and October 2012 at the Western infirmary in Glasgow, Scotland. They were followed up until April 2016 or death. Seizure freedom was defined as no seizure for at least 1 year on unchanged medication at the last follow-up. RESULTS: A total of 201 patients (median age 73 years, 59% male) were included. The median duration from initial seizure to starting treatment was 8 months (interquartile range: 3.0-24.0 months); 42.2% (85/201) patients had more than five seizures before commencing treatment. Brain imaging showed potentially epileptogenic lesions in 19.7% (38/193) of patients and other abnormalities in 56.5% (109/193); 78.6% patients (158/201) were seizure-free at the last follow-up, of whom 94.9% were taking monotherapy. Concomitant aspirin use (n = 80) was associated with a lower probability of being seizure-free (relative risk 0.82, 95% confidence interval 0.70-0.97; P = .02). The use of second-generation ASMs as the initial monotherapy increased from 31.5% (23/73) before 2000 to 70.3% (90/128, P < .001) from 2000 onward. However, the seizure freedom rates (67.1% vs 55.5%; P = .35) and intolerable adverse-effect rates (16.4% vs 19.5%; P = .45) did not show any significant difference. SIGNIFICANCE: There was often a long interval between seizure onset and the initiation of treatment in older people with new-onset epilepsy, although the majority responded well to ASM treatment. Brain imaging showed a high rate of abnormalities. Despite the increased use of second-generation ASMs, treatment outcomes in later-onset epilepsy have not improved over time. The possible effect of aspirin on treatment response warrants further investigation.

Approach to exaggerated startle reflex: a case of hyperekplexia minor.

A broad set of conditions may present with an exaggerated startle reflex in clinics. This, combined with the overall rarity of these disorders, may pose diagnostic uncertainty in the mind of the treating physician. Herein, we report a case of a patient who presented to us with the complaint of exaggerated startle reflex and outline a simple approach towards characterisation of these disorders.

Making an objective diagnosis of tetanus-utility of a simple neurophysiological test.

Tetanus remains a significant cause of mortality especially in the developing world. Early diagnosis and institution of treatment is critical to prevent fatal complications. The diagnosis is made on clinical grounds, which may sometimes be difficult, especially in case of localised tetanus. Being able to diagnose tetanus objectively is invaluable in such cases. In this regard, masseter inhibitory reflex (MIR) is a simple neurophysiological test that can be performed at the bedside. Herein, we report a case of craniocervical tetanus that was objectively diagnosed using MIR and adequately treated.

Recognizing Movement Disorder Emergencies - A Practical Review For Non-Neurologist.

Neurology still remains one of the most underserved specialties of medicine in Pakistan with roughly one neurologist per million people. Movement disorders (MD) are neurological problems that interfere with patient's motor abilities and diagnosis is typically clinical. In this review, we describe a practical approach to common MD emergencies that may be encountered by a non-neurologist physician, emphasizing on formulating a working diagnosis and their immediate management. Movement disorder emergencies can be classified based on MD phenomenology and we will provide a brief overview of dystonia including acute dystonic reaction, PAID syndrome and dystonic storm; chorea, myoclonus including serotonin syndrome and startle disease; and rigidity including neuroleptic malignant syndrome and malignant hyperthermia.

Evaluation of quality of warfarin therapy by assessing patient's time in therapeutic range at a tertiary care hospital in Pakistan.

OBJECTIVE: To assess the time in therapeutic range in patients on warfarin anti-coagulation therapy. METHODS: The retrospective chart review was conducted at Aga Khan University Hospital, Karachi, and comprised data of patients having undergone anti-coagulation with warfarin from January 2013 to April 2015. To determine the mean time in therapeutic range, Rosendaal method was used. Association of time in therapeutic range with the composite outcome, bleeding and thromboembolic events was also assessed. Percentage of patients with time in therapeutic range <60% was calculated. RESULTS: There were 92 patients whose median time in therapeutic range was 34.9% (interquartile range: 20.0- 55.7). Overall, 71(77.2%) patients had time in therapeutic range below 60% which had statistically significant correlation with the composite outcome (p<0.05). Number of comorbids was significant in predicting time in therapeutic range and patients with time in therapeutic range< 60% (p<0.05). CONCLUSION: Subjects had poor anti-coagulation quality. It might be prudent to move towards novel oral anticoagulant drugsas the first choice for therapeutic anti-coagulation.

Ischaemic pituitary tumour apoplexy and concurrent meningitis: a diagnostic dilemma.

Pituitary tumour apoplexy is a rare but potentially life threatening clinical syndrome that mostly results from haemorrhage in the pre-existent tumour. Pure ischaemic subtype of apoplexy is even rarer. The presentation can be hard to differentiate clinically from bacterial meningitis. Moreover, the presence of one does not necessarily exclude the other and early diagnosis of both conditions is imperative for timely management. We report a case of ischaemic pituitary tumour apoplexy that may have precipitated in the setting of bacterial meningitis.

Frequency of worsening liver function in severe dengue hepatitis patients receiving paracetamol: A retrospective analysis of hospital data.

OBJECTIVE: To determine the frequency of worsening liver function among hospital in-patients with severe dengue hepatitis receiving paracetamol. METHODS: This retrospective study was conducted at the Department of Medicine, Aga Khan University Hospital, Karachi, and comprised records of dengue patients with severe hepatitis who received paracetamol for control of fever between June 2007 and December 2014. Alanine aminotransferase at baseline and following paracetamol administration was noted, as well as dosage and duration of paracetamol, along with participants' demographic details. Frequency of patients who developed worsening or improvement of alanine aminotransferase was also noted. SPSS 19 was used for data analysis. RESULTS: Of the 113 subjects, 73(64.6%) were male and 40(35.4%) were female. Overall improvement was observed in subsequent alanine aminotransferase levels (491 units per litre, IQR 356.5 TO 775 vs 151 units per litre, IQR 49.5 to 299.5). Most commonly prescribed dose of paracetamol was 2g (IQR 1 to 5 grams), which was taken for a median duration of 1 day (IQR 1 to 3 days). Moreover, 100(88.5 %) patients showed improvement in alanine aminotransferase. Only 13(11.5 %) patients developed worsening of alanine aminotransferase. Of those with worsening liver function, 8(61.5 %) were discharged home with no clinical deterioration and 5(38.5 %) deaths were observed. However, causes of deaths were unrelated to liver dysfunction. CONCLUSIONS: The frequency of worsening liver function following paracetamol administration in patients with severe dengue hepatitis was relatively low.

Pure motor axonal neuropathy triggered by antituberculous therapy in an undiagnosed case of acute intermittent porphyria.

A man aged 22 years misdiagnosed as suffering from recurrent abdominal tuberculosis, in view of recurrent abdominal pain was treated for abdominal tuberculosis in the past. The patient was prescribed antituberculous therapy. 2 months after starting treatment, he developed progressive weakness of all 4 limbs. Electrodiagnostic examination revealed an acute severe motor axonal neuropathy. Further workup revealed elevated porphyrin precursors in urine.

Hypoparathyroidism: A rare mimic of amyotrophic lateral sclerosis.

INTRODUCTION: Amyotrophic lateral sclerosis (ALS) carries a grim prognosis. Various ALS mimics have been reported and should be excluded before confirming this diagnosis. METHODS: We report the case of a 61-year-old man who presented with progressively worsening limb weakness and dysphagia. His examination showed mixed upper and lower motor neuron signs without sensory impairment. ALS was suspected, however, atypical diffuse pain prompted diagnostic work-up to exclude other causes. RESULTS: Electrodiagnostic testing was suggestive of a sensorimotor polyneuropathy with superimposed diffuse active denervation suspicious for anterior horn cell degeneration. Brain MRI showed bilateral basal ganglia and thalamic calcifications. Laboratory studies confirmed the diagnosis of hypoparathyroidism. Treatment with calcium and vitamin D resulted in significant improvement at 6 months follow-up. CONCLUSIONS: Hypoparathyroidism, a treatable endocrinopathy, can rarely present clinically as ALS. In atypical cases, this should be ruled out before making a final diagnosis. Muscle Nerve, 2016 Muscle Nerve 55: 437-439, 2017.