Prevalence of Malnutrition Among Elderly People in Iran: Protocol for a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Malnutrition occurs following a decrease or an imbalance in the absorption of energy, protein, vitamins, and minerals because of numerous factors. Thus, it has serious and life-threatening consequences. To plan for this issue, we need information on the burden of this problem. OBJECTIVE: The aim of this study is to determine the prevalence of malnutrition among elderly people in Iran. METHODS: For the purpose of this study, papers, including original articles, theses, and conference proceedings on the prevalence of malnutrition among people aged 60 years and above, and have been published in national and international journals until September 2018 will be included without any language limitation. The following keywords along with their synonyms in Persian will be used in the literature search: malnutrition, elderly, and Iran. At first, the screening process will be conducted based on our inclusion and exclusion criteria. Then, the full text of the remaining articles will be read carefully, and eligible articles will be selected according to the objectives of the study. Next, the methodological quality of the selected papers will be reviewed, and the required information will be extracted from those with acceptable quality. Finally, a meta-analysis will be performed using the Stata software (version 14) when optimum criteria are met. It should be noted that all stages of screening, selection, quality assessment of primary studies, and data extraction will be performed by two reviewers independently. RESULTS: This review is ongoing and will be completed at the end of 2019. CONCLUSIONS: This review aims to provide comprehensive evidence about the prevalence of malnutrition among elderly people in Iran. This can help Iranian health managers and policy makers make informed decisions for preventing malnutrition and promoting the health status of elderly people. TRIAL REGISTRATION: PROSPERO CRD42018115358; https://tinyurl.com/y28su47m. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15334.
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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 | 0.063 | 0.087 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.024 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.063 | 0.006 |
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".