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Record W4214701652 · doi:10.36106/ijsr/6111520

ASSOCIATION OF LIPID PROFILE AMONG THE HYPERTENSIVE IN COMPARISON TO NORMOTENSIVE PATIENTS IN OUR INSTITUTION

2022· article· en· W4214701652 on OpenAlexaff
Anand Shanker Singh, G. Radhika

Bibliographic record

VenueINTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH · 2022
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsMedicineBlood pressureDyslipidemiaInternal medicineTriglycerideCardiologyStroke (engine)Risk factorDiseaseCholesterolEndocrinology

Abstract

fetched live from OpenAlex

Introduction: Hypertension and dyslipidemia are associated with oxidative stress and are major causes of cardiovascular disease amounting to 30% of global death rate. It is widely accepted that cardiovascular disease is associated with hypertension and increased blood levels of low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides. In contrast, a low level of high density lipoprotein (HDL) is a risk factor for mortality from cardiovascular disease. Hypertension is a major public health problem in developed and developing countries. Methods: This study was a cross sectional study in which 159 diagnosed hypertensive patient and 75 with normal blood pressure (normotensive) were enrolled. These patients sought a through health cheek up including blood pressure assessment between May 2020 to April 2021 Results: The mean of Systolic blood pressure and Diastolic blood pressure of hypertensive were higher than normotensive (p<0.001). The serum levels of total cholesterol, triglyceride and LDL-C in hypertensive subject were higher than normotensive and statistically signicant (p<0.001). Serum HDL-C was signicantly lower (p<0.001) in hypertensive patients than in normotensive. Conclusion: Hypertensive patients have been found to have close association with dyslipidemia. Hypertensive patients need measurement of blood pressure and lipid prole at regular interval to prevent heart diseases and stroke

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.097
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
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 integrity0.0000.001
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 head0.080
GPT teacher head0.386
Teacher spread0.306 · 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 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 venueINTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCHSame topicBlood Pressure and Hypertension StudiesFrench-language works237,207