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Record W1573887796

Investigation of cardiac dysfunction and hypoxaemia during epileptic seizures

2012· dissertation· en· W1573887796 on OpenAlexfundno aff
Ruth Brotherstone

Bibliographic record

VenueERA · 2012
Typedissertation
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsEpilepsyMedicineCardiac dysfunctionPsychologyCardiologyAnesthesiaPsychiatryHeart failure
DOInot available

Abstract

fetched live from OpenAlex

Epileptic seizures are often un-witnessed and can result in hypoxic brain damage or can be fatal due to injuries, status epilepticus or sudden unexpected death in epilepsy (SUDEP). The first aim of this thesis was to investigate some of the physiological parameters that accompany an epileptic seizure and may be useful in a seizure alarm system. The second aim was to investigate aspects of cardiac dysfunction during clinical and sub-clinical seizures that may be potential contributing factors in SUDEP. Percentage heart rate change and oxygen saturation were studied prospectively during 527 epileptic seizures in 50 patients aged from one-day full term neonate to 60 years with a variety of seizure types (absences, generalised tonic clonic seizures, myoclonic seizures, tonic seizures and focal seizures) and in normal physiological events (e.g. coughing, turning in bed). Higher percentage heart rate change occurred during epileptic seizures (21.8%) than during normal physiological events (16.4%) p<0.001. Diagnostic testing of clinically significant seizures i.e seizures that could potentially lead to serious consequences if left undetected (n=61) had a sensitivity of 91% and specificity of 75% when percentage heart rate change and hypoxaemia parameters were combined. Percentage heart rate change and oxygen saturation could be used as reliable indicators of a seizure when set at specific levels and distinguish clinically significant seizures from normal physiological events. These parameters can now be used to develop a reliable alarm system to detect epileptic seizures at night. Prolongation of QTc and increased vagal tone may be possible mechanisms underlying SUDEP. Corrected Q-T cardiac repolarisation time 5 minutes before and throughout 156 epileptic seizures were analysed using four corrective formulae (Bazett, Hodge, Fridericia and Framingham). All formulae indicated statistically significant lengthening of the corrected Q-T during epileptic seizures (p<0.001) compared to pre-seizure values. All formulae agreed that the greatest lengthening of the corrected QT beyond normal limits occurred during right temporal lobe seizures in two patients. Reflex and tonic vagal activity utilising R-R intervals was assessed in 33 sub-clinical seizures occurring during stages 3 or 4 sleep and was compared to matched counts of R-R interval non-ictal baseline studies from the same stage of sleep in each patient. Altered vagal activity occurred during total sub-clinical seizures compared to baseline studies (p<0.001). Lengthening of the corrected Q-T and changes in cardiac vagal tone during epileptic seizures may have a role in the patho-physiology of SUDEP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.273
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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