Risk of heart failure and edema associated with the use of pregabalin: a systematic review
Bibliographic record
Abstract
BACKGROUND: Pregabalin is used in the treatment of postherpetic neuralgia, diabetic neuropathic pain, partial seizures, anxiety disorders and fibromyalgia. Recognized adverse effects associated with its use include cognitive impairment, somnolence and dizziness. Heart failure associated with pregabalin has been described, however the strength of this association has not been well characterized. To examine this further, we will conduct a systematic review of the risk of heart failure and edema associated with use of pregabalin. METHODS/DESIGN: We will include all studies (experimental, quasi-experimental, observational, case series/reports, drug regulatory reports) that examine the use of pregabalin compared to placebo, gabapentin or conventional care. Our primary outcome is heart failure and the secondary outcomes include edema and weight gain. We will search electronic databases (MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials), and grey literature sources (trial registries, conference abstracts) to identify relevant studies. To ensure literature saturation, we will contact drug manufacturers, conduct forward citation searching, and scan the reference lists of key articles and included studies. We will not restrict inclusion by language or publication status.Two reviewers will screen citations (titles and abstracts) and full-text articles, conduct data abstraction, and appraise risk of bias. Random-effects meta-analysis will be conducted if the studies are deemed heterogeneous in terms of clinical, statistical and methodological factors but still suitable for meta-analysis. CONCLUSIONS: The results of this review will assist physicians to better appreciate pregabalin's risk for edema or congestive heart failure and will be pertinent to the thousands of patients worldwide who are administered this medication.Our protocol was registered in the PROSPERO database (CRD42012002948).
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 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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.020 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".