Kharameh cohort study (KHCS) on non-communicable diseases and preliminary findings of 3-year follow-up
Bibliographic record
Abstract
PURPOSE: The Kharameh cohort study (KHCS) is one branch of the 'Prospective Epidemiological Research Studies in Iran', located in the south of Iran. The enrolment phase of KHCS spanned from April 2015 to March 2017, during which urban and rural residents of Kharameh were enrolled in the study. KHCS aims to investigate the incidence of non-communicable diseases (NCDs) such as hypertension, diabetes mellitus, cardiovascular diseases and cancer, and its related risk factors in a 15-year follow-up. PARTICIPANTS: KHCS was designed to recruit 10 000 individuals aged 40-70 years old from both urban and rural areas of Kharameh. Thus, a total of 10 800 individuals aged 40-70 years of age were invited and, finally, 10 663 subjects were accepted to participate, with a participation rate of 98.7%. FINDINGS TO DATE: Of the 10 663 participants, 5944 (55.7%) were women, and 6801 (63.7%) were rural residents. The mean age of the participants was 51.9±8.2 years. 41.8% of the participants were aged 40-49, 35.2% were aged 50-59 and the remaining 23% were 60-70 years old. Until March 2020 (first 3 years of follow-up), the total number of patients diagnosed with NCDs was 1565. Hypertension, type 2 diabetes and acute ischaemic heart disease were the most common NCDs. Furthermore, the total number of deaths during the first 3 years of follow-up was 312, with cardiovascular diseases (38.7%) as the most common cause of death, followed by cerebrovascular diseases (11.8%) and cancer (16.2%). FUTURE PLANS: The remaining 12 years of follow-up will inevitably shed light on the genetic, lifestyle/socioeconomic status, and environmental risk and protective factors of NCDs.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".