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Record W2938229115 · doi:10.30576/2414-2050.2019.05.1

Assessment of C-Reactive Protein Levels in Periodontal Patients Using a Standard Laboratory Procedure

2019· article· en· W2938229115 on OpenAlexvenueno aff
Vittorio Checchi

Bibliographic record

VenueGlobal Journal of Oral Science · 2019
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsnot available
FundersUniversità di Bologna
KeywordsC-reactive proteinDentistryMedicineInternal medicineInflammation

Abstract

fetched live from OpenAlex

Background: the aims of the randomized clinical trial were (i) to verify the association between periodontal disease and C-reactive protein (CRP) and (ii) to evaluate a possible reduction of serum CRP levels after non-surgical periodontal treatment.Methods: Thirty-two subjects, 18 affected by chronic periodontitis, and 14 periodontally healthy patients, aged between 21 and 65 (41± 13) were included.Clinical and radiographic examinations were used for each patient to obtain three dental indices that were used to evaluate severity of periodontal disease and changes after treatment.Periodontal patients were randomly assigned to one of two groups for different treatments: special oral hygiene instructions alone or in combination with scaling and root planing.Blood samples were taken for measurement of CRP levels and eritrosedimentation rate before and after treatment Results: a reduction of clinical index CPSS was observed for both groups of periodontal patients after treatment but there were no statistically significant differences for CRP and ESR at baseline and between baseline and reexamination.Non statistically significant differences of CRP values between periodontal patients and healthy controls were found Conclusions: CRP values don't seem to change after non-surgical treatment of periodontitis, even in presence of a reduction of clinical indices.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.019
GPT teacher head0.360
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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