Acute dental infections and cardiac arrhythmias: a systematic literature review and case report
Bibliographic record
Abstract
Objectives: In this paper we outline how inflammation related to oral disease such as periodontitis, bacteraemia and pulpal lesions have been linked to cardiovascular disease and undertake a systematic review of the literature focused on acute dental infection and cardiac arrhythmia. We also describe an illustrative case where an acute oral infection was associated with occurrence of new onset atrial fibrillation (AF). Methods: An electronic search was undertaken using MEDLINE and SCOPUS from 01 Jan 1970 until 30 June 2020. We also undertook manual searches using forward and backward citation chasing. Inclusion criteria were any primary research studies investigating symptomatic apical infections or dental abscess with outcomes of arrythmia. Results Over the last fifty years, only two low quality studies have been investigated this area. Our illustrative case involved a 58-year-old who was diagnosed with an acute dental infection from an upper canine tooth. The patient later developed tachycardia and new-onset AF. Conclusions: Based on the biological plausibility of a link between acute dental infection and arrythmia, together with the case report presented, it is evident that further study in this area is needed. If there are possible cardiovascular consequences for patients suffering acute dental infections, this has future implications for healthcare staff as they can integrate professional advice related to oral health and cardiovascular disease. Screening programmes situated in dental settings can also facilitate early intervention and prevention producing benefits not just for patients, but in savings to the health system.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".