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Record W4237694132 · doi:10.14740/jnr404w

A Study on Clinico-Biochemical Profile of Neonatal Seizure

2016· article· en· W4237694132 on OpenAlex
Dinesh Das, Sanjib Kumar Debbarma

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Neurology Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEtiologyPediatricsNeonatal seizureFull TermPresentation (obstetrics)EpilepsyPregnancyObstetricsInternal medicine

Abstract

fetched live from OpenAlex

Background: Seizure is the most frequent sign of neurologic dysfunction in the neonate. Biochemical disturbances occur frequently in neonatal seizures either as an underlying cause or as associated abnormalities. In their presence, it is difficult to control seizures and there is a risk of further brain damage. Early recognition and treatment of biochemical disturbances are essential for optimal management and satisfactory long-term outcome. The aims were to study the biochemical abnormalities in neonatal seizures and to describe the clinical presentation, time of onset and its relation to etiology of neonatal seizures. Methods: The present study included 115 neonates presenting with seizures admitted to neonatal unit, in a teaching institute, Agartala, Tripura, India during the period of 1.5 years from November 2013 to April 2015. Detailed antenatal, natal and postnatal history was taken and examination of baby was done. Then, relevant investigations including biochemical parameters were done and etiology of neonatal seizures and their associated biochemical abnormalities were diagnosed. Results: In the present study, out of 115 neonates studied, 105 were full-term, of which 94 (81.7%) were AGA and 11 (9.6%) were SGA, nine (7.8%) were preterm and one (0.9%) was post-term babies. One hundred and thirteen (98.3%) were hospital deliveries and 104 (90.4%) were spontaneous vaginal deliveries. Seventy-five (65.2%) were with birth weight > 2.5 kg. In our study, 82 (80%) cases had onset of seizures within first 3 days. The highest number is seen on first day of life (66, 57.4%). Birth asphyxia was the cause in 92.1% of neonates who developed seizures on first day of life. Subtle seizures were the most common type of seizures in our study (49, 42.6%). Birth asphyxia was the most common cause of neonatal seizures in our study (64, 56%), followed by neonatal meningitis (24, 21%) and metabolic disorders (13, 11%). The most common biochemical abnormality detected in neonatal seizures in our study was hyponatremia (26, 65%), of which 21 (72.4%) were due to hypoxic ischemic encephalopathy (HIE), and the rest were due to neonatal meningitis (5, 55.6%). In metabolic seizures, hypoglycemia (66.7%) was common, and more so in low birth weight babies (55%). Incidence of hypomagnesemia with hypocalcemia occurred in two (1.73%) cases. Conclusions: The most common etiology of neonatal seizures is HIE and onset is during first 3 days of life. Hyponatremia is the most common biochemical abnormality associated with non-metabolic seizures, mainly HIE. Hypoglycemia is a more common metabolic disorder, more so in low birth weight. Incidence of hypomagnesemia with hypocalcemia is low but recognition of such abnormality has important therapeutic implications. J Neurol Res. 2016;6(5-6):95-101 doi: https://doi.org/10.14740/jnr404w

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.402
Teacher spread0.341 · 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