The Role of Leukocyte Telomere Length in Cognitive Function, Symptom Severity, and Sdg-Related Health Goals Among Batak Schizophrenia Patients
Bibliographic record
Abstract
Objective: To assess the relationship between leukocyte telomere length, cognitive function, and symptom severity in Batak tribe schizophrenia patients, with a focus on telomere length as a potential biomarker for disease progression and its relevance to Sustainable Development Goal (SDG) 3: Good Health and Well-being. Theoretical Framework: This study builds on findings linking leukocyte telomere shortening to accelerated aging, cognitive decline, and increased risks of neurodegenerative diseases and cancer. These connections underscore the importance of telomere length as a marker of symptom severity in schizophrenia and its alignment with global health objectives under the SDGs. Method: A 6-month cross-sectional study design with numerical correlation tests was used from January to June 2023. Eighty-five patients from the Batak tribe diagnosed with schizophrenia were recruited from Regional Mental Hospital Prof. Dr. M. Ildrem Medan, and telomere length analysis was conducted at Prodia Private Clinical Laboratory in Medan. Results and Discussion: The sample included 85 patients, mostly male (80%) with a mean age of 30.38 years (SD: 3.2). Cognitive function showed a mean MoCA-Ina score of 17.33 (SD: 5.4), and symptom severity showed a mean PANSS score of 48.87 (SD: 9.73). Leukocyte telomere length ratios were 0.92 (SD: 0.04) for β-globin T/S and 0.99 (SD: 0.05) for B4AU T/S. No significant link was found between telomere length and cognitive function (p>0.05), but shorter telomeres correlated with more severe symptoms (β-globin T/S: p=0.034, r=-0.23; B4AU T/S: p=0.037, r=-0.227). Research Implications: Findings indicate that leukocyte telomere length could serve as a biomarker for schizophrenia symptom severity, offering valuable insights for disease progression and contributing to health monitoring strategies aligned with SDG 3. Originality/Value: By focusing on the Batak tribe, this study highlights telomere length as a biomarker for prognosis and underscores the importance of diverse population studies to achieve SDG-related health outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".