Evidence map›Paper›PMID 37469231›Full record

ArticleEpilepsia open2024

Ex-SPECTing success: Predictors of successful SPECT radiotracer injection during presurgical video-EEG admissions.

Carmela Cosentino, Said Al Maawali, Thanomporn Wittayacharoenpong, Tracie Tan, Hue Mun Au Yong, Lubna Shakhatreh, Zhibin Chen, Paul Beech, Emma Foster, Terence J O'Brien and 2 more

Open access · goldAbstract read
In one paragraph

Article in Epilepsia open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 2 countries.

Carmela CosentinoDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-7939-4887
Said Al MaawaliDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.
Thanomporn WittayacharoenpongDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.
Tracie TanDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-1638-7129
Hue Mun Au YongDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0001-9420-0641
Lubna ShakhatrehDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0003-2262-0377
Zhibin ChenDepartment of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-1888-6917
Paul BeechDepartment of Radiology, Alfred Health, Melbourne, Victoria, Australia.
Emma FosterDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0001-8958-3844
Terence J O'BrienDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.
Patrick KwanDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0001-7310-276X
Andrew NealDepartment of Neurology, Alfred Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0001-9251-5471
Alfred Health · AUHealth First · USMonash University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine predictors of successful ictal single photon emission computed tomography (SPECT) injections during Epilepsy Monitoring Unit (EMU) admissions for patients undergoing presurgical evaluation for drug-resistant focal epilepsy.

methodsIn this retrospective study, consecutive EMU admissions were analyzed at a single center between 2019 and 2021. All seizures that occurred during the admission were reviewed. "Injectable seizures" occurred during hours when the radiotracer was available. EMU-level data were analyzed to identify factors predictive of an EMU admission with a successful SPECT injection (successful admission). Seizure-level data were analyzed to identify factors predictive of an injectable seizure receiving a SPECT injection during the ictal phase (successful injection). A multivariate generalized linear model was used to identify predictive variables.

results125 EMU admissions involving 103 patients (median 37 years, IQR 27.0-45.5) were analyzed. 38.8% of seizures that were eligible for SPECT (n = 134) were successfully injected; this represented 17.4% of all seizures (n = 298) that occurred during admission. Unsuccessful admissions were most commonly due to a lack of seizures during EMU-SPECT (19.3%) or no injectable seizures (62.3%). Successful EMU-SPECT was associated with baseline seizure frequency >1 per week (95% CI 2.1-3.0, P < 0.001) and focal PET hypometabolism (95% CI 2.0-3.7, P < 0.001). On multivariate analysis, the only factor associated with successful injection was patients being able to indicate they were having a seizure to staff (95% CI 1.0-4.4, P = 0.038). SIGNIFICANCE: Completing a successful ictal SPECT study remains challenging. A baseline seizure frequency of >1 per week, a PET hypometabolic focus, and a patient's ability to indicate seizure onset were identified as predictors of success. These findings may assist EMUs in optimizing their SPECT protocols, patient selection, and resource allocation.

Indexed as

Drug Resistant EpilepsyElectroencephalographyTomography, Emission-Computed, Single-PhotonAdultFemaleHumansMaleMiddle AgedPreoperative CareRetrospective StudiesSeizuresVideo Recordingepilepsy monitoring unitepilepsy surgeryfocal epilepsyrefractory epilepsysingle photon emission computed tomography

Identifiers

PMID37469231
PMCPMC11450587
OpenAlexW4384819831

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.