Is white-coat hypertension a risk factor for carotid atherosclerosis? A review and meta-analysis
Bibliographic record
Abstract
The association of white-coat hypertension (WCH) with target organ damage is still debated; in particular, the relationship of this blood pressure phenotype with subclinical vascular damage remains controversial. Thus, we carried out a systematic review and meta-analysis to provide updated information on carotid structural changes in WCH. Studies were identified using the following search terms: 'white coat hypertension', 'isolated clinic hypertension', 'carotid artery', 'carotid atherosclerosis', 'carotid intima-media thickness', 'carotid damage', 'carotid thickening'. Full articles published in the English language in the last two decades reporting studies on adults were considered. A total of 3478 untreated patients, 940 normotensive (48% men), 666 WCH (48% men), and 1872 hypertensive individuals (57% men) included in 10 studies, were analyzed. Common carotid intima-media thickness (IMT) showed a progressive increase from normotensive (718±36 μm) to WCH (763±47 μm, standardized mean difference 0.54±0.13, P<0.01) and to hypertensive patients IMT (817±47 μm, standardized mean difference 0.45±0.14, P<0.01). After assessing data for publication bias, only the difference between normotensive and WCH patients remained significant. Our meta-analysis documents that common carotid IMT, a prognostically validated marker of vascular damage, is greater in WCH patients than in true normotensive individuals and is not different from sustained hypertensives. This finding supports the concept that WCH is not an entirely benign condition.
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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".