Cinacalcet versus standard treatment for chronic kidney disease: a protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease-mineral and bone disorders (CKD-MBD) have been associated with poor health outcomes, including diminished quality and length of life. Standard management for CKD-MBD includes phosphate-restricted diet, active vitamin D, vitamin D analogs, and phosphate binders. Persistently elevated parathyroid hormone (PTH) levels may require the addition of Cinacalcet hydrochloride (cinacalcet) which sensitizes calcium receptors on the parathyroid glands. The objective of this systematic review is to compare the effect of cinacalcet versus standard treatment in patients with CKD-MBD. METHODS/DESIGN: Data sources will include MEDLINE, EMBASE, the Cochrane Register of Controlled Trials, and Web of Science from 1996 to June 2015. Teams of two reviewers will, independently and in duplicate, screen titles and abstracts and potentially eligible full text reports to determine eligibility, and subsequently abstract data and assess risk of bias in eligible trials. We will calculate the effect estimates (risk ratios or mean differences) and 95 % confidence intervals, as well as statistical measures of variability in results across studies using random effect models for patient-important and intermediate outcomes. We will use the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach to rate the quality of evidence about estimates of effect on an outcome-by-outcome basis. We will present our results with a GRADE summary table. DISCUSSION: Our review will explore the effect of cinacalcet versus standard treatment in patients with CKD-MBD. The results of this systematic review will help guide management of this patient population, and identify targets for future research. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015020318 http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42015020318.
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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 | 0.071 | 0.119 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.024 | 0.033 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.040 | 0.004 |
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".