Febrile seizure

Febrile seizure

Definition

-Age + T°C + no CNS infection

1st) Age: 6 mo - 5 yo

*>6y→GEFS+

2nd) T ≥ 38°C

3rd) No CNS infection

Epidemiology

-MC szs of childhood

-Peak 1y

-Viral, mainly

>can occur after DTP (1d) or MMR (8d)

-Genetic, 25% FH of szs (FS or Epi)

Classificaiton

-Simple (90%)→ generalized < 15 min, no recur 24h

-Complex→ everything else

a) focal

b) > 15 min (some 10 min)

c) recur 24h

d) postictal neuro-deficit

Evaluation

-Based on classification, find T°C source

>Simple→ nothing specific

TTx

-Usually, self-limited (< 3 min)

-Otherwise, BZD, manage as SE

-Prophylaxis

>No ASM

>Antipyretics do not prevent FS

*Okay rescue BZD, if hs of febrile SE

Prognosis

-FS recurr→30%

-Epi, based on classification

>Simple, as general population

Amplitude-integrated EEG (aEEG)

Amplitude-integrated EEG (aEEG)

Applicability

-Mainly, new born

-No pattern for adults, except by 2 settings

a. post-cardiac arrest

b. NICU szs detection

Classifications

-Hellström-Westas→ 5 categories, term & preterm

-al Naqeeb→ 3 categories, only term

Explanation

1. CNV: LM 5–10 µV, UM 10–50 µV

2. DNV: LM < 5 µV, UM > 10 µV

3. BS: LM 0–2 µV, and bursts exceed 25 µV.

BS+: > 100 bursts per hour.

BS−: < 100 bursts per hour.

4. CLV: < 5 µV, with everything < 10 µV.

5. FT/isoelectric: no activity, < 5 µV.

Approach of preterm 

Adults

a. post–cardiac arrest

-CNV recovery time→ best predictor

>CNV within about 24 h predicted good outcome

>At least Fp1-Fp2

b. NICU szs detection

>recommended 1h windows, miss 30s szs

253. Accepted

252. Accepted

251. Accepted

Intermittent photic stimulation (IPS)

Intermittent photic stimulation (IPS)

Ancient Greece & Rome, 

Slave traders used a rotating potter's wheel as a provocative medical screening

❶Documentation

-If normal:

 >Symmetric posterior driving

 >No epileptiform discharges

 >No clinical correlate

-If abnormal:

 >Type of photoparoxysmal response (PPR)

 >Triggering frequency (range)

 >Clinical correlate: absent/ present (semiology)

 >Persistent beyond stimulation

❷Setup

-Informed consent

-Stop IPS, if discahrges

-Caution in genetic and photosensitive generalized epilepsies, especially JME

-Circular-reflector stimulator, at 30 cm from nasion and 0.7 intensity

❸Protocol

*IPS should be performed 3 min after HV, or before HV

1)Hz: 1→2→8→10→15→18→20→25→40→50→60

2)Eye: closure→closed→open

*Eye closure is the most provocative

3)If PRR occurs, stop ascending sequence

4)Restart from 60 Hz descending to determine range

❹Photic driving

-Occipital/post leads (MC)

-Usually: symmetric, post predominant, and non-epileptiform

-Components: harmonic (2x) and subharmonic (1/2)

E.g.: if 10 Hz stimuli, harmonic is 20 Hz response, and subharmonic 5 Hz

❺Photomyogenic response (PMR)

-Ocular artifact: frontal blinked related deflection

-PMR: 

>Time-locked frontotemporal muscle resposne

>Stops when stimulation ends

❻PPR

-Spike-wave or polyspike-wave discharges, often generalized; can persitent beyond stimulation

-PPRs range from post discharges to generalized responses

❼Considerations

ⓐ Does absent photic driving indicate abnormal brain function?→No

-Normal physiological occipital response

-Influenced by: retinal illumination and drowsiness

ⓑWhy IPS w/ eyes open, closure, and closed?→ ≠conditions

-Open→ preserved visual fixation

-Closure→ detect eye-closure sensitivity (ECS) in eyelid myoclonia (Jeavons syndrome)

>brief epileptiform discharges immediately after closing, within 1–3 seconds

-Closed→ fixation-off sensitivity (FOS), mainly in occipital epilepsies

Levetiracetam Versus Phenobarbital as First‑Line Therapy for Neonatal Seizures: A Meta‑analysis of Randomized Controlled Trials

Title: Levetiracetam Versus Phenobarbital as First‑Line Therapy for Neonatal Seizures: A Meta‑analysis of Randomized Controlled Trials

Authors: Ana Leticia Fornari Caprara, Jamir Pitton Rissardo

Conference: 2026 ANA Annual Meeting, San Diego, CA

OBJECTIVE

Phenobarbital remains the standard first‑line treatment (1LT) for neonatal seizures (NS) despite concerns regarding efficacy and safety. Levetiracetam has gained widespread use as an alternative, but randomized evidence is conflicting. We performed a meta‑analysis of randomized controlled trials (RCTs) comparing levetiracetam with phenobarbital as 1LT for NS.

METHODS

We systematically identified RCTs PubMed-indexed enrolling neonates treated with levetiracetam or phenobarbital as initial antiseizure medication (ASM). The primary outcome was seizure freedom (SF) within 24 hours. Secondary outcomes included 1LT failure, requirement for rescue ASM, adverse events (AEs), and mortality. Risk ratios (RRs) were pooled using a Mantel–Haenszel random‑effects model with REML. Heterogeneity was quantified using the I2 statistic. Numbers needed to treat (NNT) and harm (NNH) were estimated from absolute risk differences.

RESULTS

Six RCTs (levetiracetam=245; phenobarbital=216) were included. Levetiracetam did not significantly increase SF compared with phenobarbital (RR 1.23, 95% CI 0.86–1.76; I2=72%). On meta‑regression, trials using clinical seizure diagnosis demonstrated higher SF rates with levetiracetam (RR  1.38, 95% CI 1.01–1.88), whereas the single trial using continuous EEG‑confirmed seizures showed superior efficacy of phenobarbital (RR 0.30, 95% CI 0.17–0.54). 1LT failure (RR  0.87, 95% CI 0.52–1.44) and need for rescue ASM (RR 0.73, 95% CI 0.46–1.17) did not differ significantly between groups. Levetiracetam was associated with fewer AEs overall (RR 0.33, 95% CI 0.15–0.71), particularly hypotension (RR 0.30, 95% CI 0.13–0.68). No differences were observed between groups for respiratory depression (RR 0.63, 95% CI 0.32–1.25), bradycardia (RR 0.44, 95% CI 0.13–1.53), or mortality rates (RR 1.17, 95% CI 0.46–2.95). Levetiracetam increased SF by 3.3% (NNT ≈ 30), whereas phenobarbital increased hypotension by 9.1% (NNH ≈ 11).

CONCLUSIONS

Levetiracetam does not demonstrate consistent superiority over phenobarbital as 1LT for NS control. However, levetiracetam shows a more favorable short‑term safety profile. RCTs assessing different NS diagnoses are needed to confirm results.

Citation

Caprara AL, Rissardo JP. Levetiracetam Versus Phenobarbital as First‑Line Therapy for Neonatal Seizures: A Meta‑analysis of Randomized Controlled Trials. Ann Neurol 2026;100(Suppl 37):S160.

Deferiprone in Parkinson’s Disease: Motor, Imaging, and Safety Outcomes Across Randomized Trials

Title: Deferiprone in Parkinson’s Disease: Motor, Imaging, and Safety Outcomes Across Randomized Trials

Authors: Jamir Pitton Rissardo, Ana Leticia Fornari Caprara

Conference: 2026 ANA Annual Meeting, San Diego, CA

BACKGROUND/OBJECTIVE

Iron accumulation in the substantia nigra (SN) contributes to oxidative injury and neurodegeneration in Parkinson’s disease (PD). Deferiprone (DFP), a brain‑penetrant iron chelator, has been evaluated as a potential disease‑modifying therapy, with inconsistent trial‑level results. We conducted a systematic review and meta‑analysis of randomized controlled trials (RCTs) to quantify the effects of DFP on motor outcomes, neuroimaging biomarkers, and safety in PD.

DESIGN/METHODS

Pubmed and ClinicalTrials.gov were searched for RCTs comparing DFP versus placebo in PD. Random‑effects meta‑analyses (REML estimator) were performed. Outcomes assessed were motor (MDS‑UPDRS Part III), MRI iron measures (SN, caudate, and putamen), serum ferritin, cognition, (MoCA/MMSE), quality-of-life (PDQ‑39), and adverse events. Effect sizes were expressed as standardized mean differences (SMD) or mean differences (MD). Heterogeneity was quantified using I2.

RESULTS

Four RCTs (n = 474 participants) were included. Pooled analysis demonstrated no significant improvement in motor symptoms with DFP versus placebo (SMD −0.11, 95% CI −0.43 to 0.21; p = 0.51; I2 = 0%). Dose‑stratified 9‑month analyses showed no significant effect across 300–1200 mg/day (MD 0.30, 95% CI −1.93 to 2.52; I2 = 64%). MRI iron outcomes showed no significant pooled effect in the SN (SMD 0.20, 95% CI −0.78 to 1.19; I2 = 79%), caudate (SMD −0.05, 95% CI −1.20 to 1.11), or putamen (SMD 0.01, 95% CI −0.95 to 0.96). DFP significantly reduced serum ferritin (MD −45.4 ng/mL, 95% CI −78.0 to −12.9; p = 0.006; I2 = 0%). No significant between‑group difference were observed for quality-of-life (MD 1.04, 95% CI −3.26 to 5.33) and cognition (SMD −0.10, 95% CI −0.48 to 0.28; p = 0.62). Risk of any adverse event was higher with DFP (RR 1.49, 95% CI 1.23–1.81; p < 0.001), with a non‑significant increase in serious adverse events and hematologic toxicity.

CONCLUSIONS

Across randomized evidence, deferiprone does not improve motor, cognitive, or quality‑of‑life outcomes in PD despite demonstrable iron chelation. Increased adverse events and lack of clinical efficacy do not support routine use of DFP as symptomatic or disease‑modifying therapy in PD.

Citation

Rissardo JP, Caprara AL. Deferiprone in Parkinson’s Disease: Motor, Imaging, and Safety Outcomes Across Randomized Trials. Ann Neurol 2026;100(Suppl 37):S311.

Escitalopram for Depression and Motor Symptoms in Parkinson’s Disease: A Systematic Review and Meta‑analysis

Title: Escitalopram for Depression and Motor Symptoms in Parkinson’s Disease: A Systematic Review and Meta‑analysis

Authors: Vishnu V. Byroju, Jamir Pitton Rissardo, Jorge Patino, Ana Leticia Fornari Caprara, Andrew McGarry, Ian Walker

Conference: 2026 International Congress of Parkinson's Disease, Seoul, Korea

Objective

To evaluate the efficacy of escitalopram versus placebo for depressive symptoms, motor severity, and quality of life (QoL) in Parkinson’s disease (PD).

Background

Depression is highly prevalent in PD and contributes to disability and reduced QoL. Although selective serotonin reuptake inhibitors are frequently prescribed, evidence regarding the impact of escitalopram on mood and motor outcomes in PD remains inconsistent.

Design/Methods

A PRISMA‑compliant systematic search of PubMed, Embase, Cochrane Library, Scopus, Web of Science, PsycINFO, and CNKI identified randomized controlled trials (RCTs) comparing escitalopram with placebo in adults with PD. Outcomes included depressive symptoms [Hamilton Depression Rating Scale (HAM‑D), Beck’s Depression Inventory (BDI‑II), and Patient Health Questionnaire-9 (PHQ‑9)], motor severity [Unified Parkinson’s Disease Rating Scale III (UPDRS‑III)], and quality of life [Parkinson’s Disease Questionnaire-39 (PDQ‑39)]. Standardized mean differences (SMDs) or mean differences (MDs) were synthesized using random‑effects models (REML). Heterogeneity was assessed using I².

Results

Four RCTs (escitalopram n=124; placebo n=126) met inclusion criteria. Escitalopram improved depressive symptoms compared with placebo (SMD −1.25; 95% CI −2.33 to −0.16), but with very high heterogeneity (I²=92.1%). No significant effect was observed for UPDRS‑III (MD −2.18; 95% CI −11.11 to 6.76; I²=98%). QoL modestly improved with escitalopram (PDQ‑39 MD −6.47; 95% CI −10.83 to −2.11). Rates of adverse events, including constipation (RR 3.50, 95% CI 0.18–69.24), dyspepsia (RR 0.70, 95% CI 0.01–33.90), falls (RR 3.50, 95% CI 0.18–69.24), fatigue (RR 1.38, 95% CI 0.13–14.20), dizziness (RR 0.70, 95% CI 0.01–33.90), and insomnia (RR 0.23, 95% CI 0.01–5.45), did not differ meaningfully between groups.

Conclusions

Escitalopram may reduce depressive symptoms and improve QoL in PD, although the evidence is limited by small sample sizes, substantial heterogeneity, and imprecise estimates. Motor outcomes show no consistent effect. Larger, methodologically uniform RCTs are needed to clarify escitalopram’s efficacy and safety in PD.

Citation

Byroju V, Rissardo JP, Patino J, Caprara AL, McGarry A, Walker I. Escitalopram for Depression and Motor Symptoms in Parkinson’s Disease: A Systematic Review and Meta‑analysis. Mov Disord 2026;41(Suppl_1):S689.

Bidirectional Association Between Gout and Parkinson’s Disease: A Systematic Review and Meta-Analysis

Title: Bidirectional Association Between Gout and Parkinson’s Disease: A Systematic Review and Meta-Analysis

Authors: Vishnu V. Byroju, Jamir Pitton Rissardo, Jorge Patino, Ana Leticia Fornari Caprara, Andrew McGarry, Ian Walker

Conference: 2026 International Congress of Parkinson's Disease, Seoul, Korea

Objective

To evaluate whether gout influences the risk of Parkinson’s disease (PD) and whether PD influences the subsequent risk of gout.

Background

Gout and PD share potential mechanistic pathways involving urate metabolism, oxidative stress, and neuroinflammation. However, epidemiologic studies examining their association have produced inconsistent findings.

Design/Methods

A PubMed search identified studies reporting hazard ratios (HRs) for gout preceding PD (Gout→PD) and PD preceding gout (PD→Gout). Random‑effects models with inverse‑variance weighting were applied. Sex‑stratified analyses were performed when available. Heterogeneity was quantified using I², and publication bias was evaluated using trim‑and‑fill and multiple fail‑safe N methods.

Results

Five studies provided thirteen study‑level estimates of gout to PD risk [Figure 1]. The pooled HR was 2.86 (95% CI 2.76–2.96; I² = 74.5%). Female‑specific analyses showed HR 3.21 (95% CI 2.91–3.55), and male‑specific analyses showed HR 2.61 (95% CI 2.45–2.79). Trim‑and‑fill identified no missing studies, and Rosenthal’s fail‑safe N was 831. Two studies evaluated PD to gout risk [Figure 2], yielding a pooled HR of 1.65 (95% CI 1.42–1.90; I² = 0%). Females had HR 1.75 (95% CI 1.36–2.26), and males HR 1.60 (95% CI 1.34–1.91). The fail‑safe N was 1, reflecting the limited available evidence.

Conclusions

Gout was associated with a higher risk of PD, and PD was associated with a higher risk of subsequent gout. These findings suggest shared pathways involving systemic inflammation, purine metabolism, and urate regulation. Further mechanistic and longitudinal studies are needed to clarify how these biological processes link gout and PD.

Citation

Byroju V, Rissardo JP, Patino J, Caprara AL, McGarry A, Walker I. Bidirectional Association Between Gout and Parkinson’s Disease: A Systematic Review and Meta-Analysis. Mov Disord 2026;41(Suppl_1):S757-S758.

Figure 1. Gout to PD risk.

Figure 2. PD to gout risk.