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Record W2510638501 · doi:10.3329/bsmmuj.v7i2.29443

Serum zinc status of neonates with seizure

2016· article· en· W2510638501 on OpenAlexaff
Olia Sharmeen, Md Abid Hossain Mollah, Md. Hasanur Rasbid, Shamshad B. Quaraishi

Bibliographic record

VenueBangabandhu Sheikh Mujib Medical University Journal · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsConvulsionMedicineZincHypoglycemiaInternal medicineZinc deficiency (plant disorder)EndocrinologyGastroenterologyEpilepsyPathologyPsychiatryInsulinChemistry

Abstract

fetched live from OpenAlex

Background: Seizure is a common neurological disorder in neonatal age group!. Primary metabolic derangement is one of the important reason behind this convulsion during this period. Among primary metabolic derangement hypoglycemia, is most common followed by bypocalcaemia, hypomagnesaemia, low zinc status etc. As causes of many cases of convul­sion remain unknown in neonate. Objectives: To see the zinc status in the sera of neonate with convulsion. So that if needed early intervention can be taken up and thereby prevent complications. Method: A total of 50 neonates (1-28 days) who had convulsion with no apparent reasons of convulsion were enrolled as cases and 50 healthy age and sex matched neonates were enrolled as controls. After a quick clinical evaluation serum zinc status was estimated from venous blood by atomic absorption method in Chemistry Division, Atomic Energy Centre. Low zinc was considered if serum value was <0.7mg/L. Results: Among a total of 50 cases 6% had low zinc value & 2% of controls also had low zinc level. The mean serwu zinc level of cases and controls were 1.57±0.95 and 2.37±1.06 mmol/1 respectively (p<0.01). Conclusion: From the study it is seen that low zinc value is an important cause of neonatal seizure due to primary metabolic abnormalities. So early recognition and treatment could save these babies from long term neurological sequelies.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.004
GPT teacher head0.189
Teacher spread0.185 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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