COVID‐19 Pandemic and Periodontal Practice: The Immunological, Clinical, and Economic Points of View
Bibliographic record
Abstract
The recent global health problem, COVID-19, has had far-reaching impacts on lifestyles. Although many effective WHO-approved vaccines have been produced that have reduced the spread and severity of the disease, it appears to persist in humans for a long time and possibly forever as everyday it turns out to have new mutations. COVID-19 involves the lungs and other organs primarily through cytokine storms, which have been implicated in many other inflammatory disorders, including periodontal diseases. COVID-19 is in a close association with dental and periodontal practice from two respects: first, repeated mandatory lockdowns have reduced patient referrals to dentists and limited the dental and periodontal procedures to emergency treatments, whereas it is important to recognize the oral manifestations of COVID-19 as well as the influence of oral and periodontal disease on the severity of COVID-19. Second, dentistry is one of the high-risk professions in terms of close contact with unmasked individuals, necessitating redefining the principles of infection control. The pressures of the economic recession on patients as well as dentists add to the difficulty of resuming elective dental services. Therefore, this study is divided into two parts corresponding to what mentioned above: the first part examines the clinical and immunological associations between COVID-19 and periodontal and oral diseases, and the second part delineates the measures needed to control the disease transmission in dental clinics as well as the economic impact of the pandemic era on dental services.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".