MétaCan
Menu
← Back to cohort
Record W4205563677 · doi:10.18231/j.ijn.2021.058

A study of association of serum ferritin as a prognostic marker in acute cerebrovascular accident

2022· article· en· W4205563677 on OpenAlexaboutno aff
B S Mythreini, Uthayasankar M.K, Sumanbabu I.S.S

Bibliographic record

VenueIP Indian Journal of Neurosciences · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)FerritinInclusion and exclusion criteriaInternal medicineDiseaseVenous bloodAcute strokePediatricsPathology

Abstract

fetched live from OpenAlex

Cerebrovascular disease (CVD) is the third leading cause of death in developed countries and is now emerging as the commonest preventable life-threatening neurological problem worldwide. It makes an important contribution to morbidity and mortality in developed as well as developing countries. The prognosis of acute stroke is determined by a series of factors some of which may be used in the early stages of stroke to predict prognosis and mortality. However, the role of inflammatory markers in predicting functional outcome in stroke remains controversial, Iron and ferritin are known to have an important role in stroke as well as in other disorders. Serum ferritin which is considered as an acute phase reactant has also been used for assessing the severity and prognosis of stroke. Therefore, testing of serum ferritin is useful in identifying high risk patients. 1: To study the effect of level of serum ferritin with early neurological deterioration and the outcome in patients of acute stroke. 2: Association of serum ferritin in ischemic and haemorrhagic stroke. 50 patients with acute stroke were selected based on inclusion and exclusion criteria. Appropriate questionnaire was used to collect the data of patients. Diagnosis of stroke was confirmed by CT or MRI scan of brain and examination was done by Canadian stroke scale at the time of admission. About 5ml of venous blood Sample from cubital vein was collected for measuring serum ferritin levels, it was performed within 48hrs of onset of symptoms by using CLIA method. Neurological assessment was repeated on the day of discharge to assess the clinical improvement and prognosis of the stroke patients. Totally 50 patients of acute stroke were included in our study, majority of the patients are males 35 (70%), and females are 15(30%). Approximately 36% were in the age group of 51-60 years. In this study ischemic stroke was seen in 45 (90%) of the patients and 5 (10%) had hemorrhagic stroke. The serum ferritin levels are normal in 41(82%) and high in 9(18%) of the patients. Canadian stroke scale interpretation on the day of discharge showed 20% of the patient are deteriorated, 66% are in the same status and 14% of the patients are improved clinically. The patients with haemorrhagic stroke had high serum ferritin level 60.0% and ischemic stroke are 13.3%. Those patients with high serum ferritin levels had higher deterioration in Canadian stroke scale (p<0.001). The mean serum ferritin levels are higher in deteriorated patients 199.29% when compared to other status group in Canadian stroke scale. High levels of serum ferritin correlates well with early neurological deterioration of stroke patients. Based on this study finding, that high serum ferritin level within 48 hours after the onset of symptoms of stroke helps to predict the early prognosis. Therefore, testing of serum ferritin is useful in identifying high risk patients.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.275
Teacher spread0.262 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueIP Indian Journal of Neurosciences→Same topicAcute Ischemic Stroke Management→French-language works237,207→