Evidence map›Paper›PMID 38800162›Full record

ArticleCureus2024

Glycemic Profile and Lipid Profile in Chronic Obstructive Pulmonary Disease (COPD) Patients With and Without Metabolic Syndrome.

Binod Mahato, Shreya Nigoskar, Lingidi Jhansi Lakshmi, Doddigarla Zephy

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Binod MahatoDepartment of Biochemistry, Index Medical College & Research Center, Malwanchal University, Indore, IND.
Shreya NigoskarDepartment of Biochemistry, Index Medical College & Research Center, Malwanchal University, Indore, IND.
Lingidi Jhansi LakshmiDepartment of Biochemistry, Hi-Tech Medical College & Hospital, Bhubaneswar, IND.
Doddigarla ZephyDepartment of Biochemistry, Hi-Tech Medical College & Hospital, Rourkela, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThere is a lack of Indian data regarding the frequency of metabolic syndrome (MetS) or its components in chronic obstructive pulmonary disease (COPD). As a result, the present study aimed to determine the prevalence of MetS in COPD cases and investigate its association with COPD severity. MATERIAL: After receiving ethical approval from Index Medical College and Hospital, we conducted this cross-sectional study in Indore. We recruited 100 participants with a history of COPD and divided them into two groups: those with MetS and those without. Researchers examined the subjects' fasting blood glucose, serum high-density lipoprotein, triglyceride (TG), systolic and diastolic blood pressure (SBP/DBP), waist circumference, and fasting blood glucose levels.

resultsWe discovered that 59% of patients with COPD and 52% of individuals with impaired fasting glucose (IFG) had MetS (mean ± SD = 110.8 ± 32.8). In comparison, 48% (mean ± SD = 98.2 ± 24.8) of individuals with normal fasting glucose do not experience this. The incidence of MetS was higher in both groups, those with IFG and those without, but the difference was not statistically significant (t = 1.7088, df = 98; p = 0.0907). We observed X2 = 1.336, df = 1, and p = 0.2476 when we tested the association between IFG and COPD with the Chi-square test.

conclusionIndividuals with MetS were more likely to have high BP, raised TG levels, low HDL cholesterol, abdominal obesity, and other risk factors.

Indexed as

chronic obstructive pulmonary diseaseemphysemahigh-density lipoproteinsimpaired fasting glucosemean blood glucosetriglycerides

Identifiers

PMID38800162
PMCPMC11116744

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.