Is Cerebral Microembolism in Mechanical Prosthetic Heart Valves Clinically Relevant?
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: High-intensity transient signals (HITS) are frequently detected by transcranial Doppler (TCD) ultrasound in patients with mechanical prosthetic heart valves (PHVs), but published data about their clinical relevance are controversial. This study was undertaken to determine the clinical relevance of HITS in patients with mechanical PHVs. METHODS: The authors prospectively studied patients with mechanical PHVs using TCD monitoring for microemboli detection with and without O2 inhalation. The cognitive testing of patients included the Mini-Mental State Examination, the Dementia Rating Scale, and MicroCog. RESULTS: The authors studied 36 patients (20 women, aged 58 +/- 13 years). HITS were detected in 72% of patients, with a nonsignificant increase of HITS rate in the aortic valve group (P = .07). There was no significant difference in HITS rate between asymptomatic and symptomatic patients. In a multiple linear regression model, HITS rate was predicted only by younger age (P = .024). No correlation was found between HITS rate and the cognitive performance of patients. There was a significant decrease in HITS rate after 100% O2 inhalation compared to baseline levels (32.8 +/- 40.2 vs 6.1 +/- 11.3, P = .011). Subgroup analysis in asymptomatic patients confirmed this finding (P = .017), but in symptomatic patients, decreased HITS rate was not statistically significant (P = .18). CONCLUSION: Only age was a significant predictor of HITS in patients with mechanical PHVs. The lack of association between HITS, clinical symptoms, and cognitive functioning suggests that most of these signals represent harmless epiphenomena, and only HITS detected after O2 inhalation have any clinical relevance.
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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".