Postoperative in dental surgery: development of an application for postoperative monitoring and randomized clinical trial of the effect of pre-emptive analgesia in dental implant surgeries
Bibliographic record
Abstract
This study was conducted to evaluate the clinical efficacy of ibuprofen in pain prevention after unit implant surgeries and to develop an operative monitoring application. For the triple-blind, parallel, placebo-controlled and randomized clinical trial, 54 singles implant insertion surgeries were performed. Two groups received two different protocols 1 hour before the surgery: group (1) Ibuprofen (IBU) 600 mg ibuprofen; and (2) placebo group (corn starch). Pain intensity was assessed by means of the visual analogue scale (EVA) printed on paper in 6 strokes (1,6,12,24,48 and 72 hours after surgery). Patients were instructed to take 750 mg paracetamol as rescue medication, if necessary. The occurrence and intensity of the pain was analyzed using an ANOVA variance analysis with repeated measurements using the general linear model procedure. The IBU group had lower EVA scores overall (IBU=0.30, ±0.57, placebo=1.14, ±1.07) and at all times in the intra, intergroup and time/group comparisons than the placebo group (p<0.001). The use of rescue medication was significantly lower and the longer postoperative time in the IBU group was compared to placebo (p=0.002). It was concluded that the single use of ibuprofen was significantly superior in reducing pain after unit implant surgery compared to placebo. In this dissertation, the development of a mobile application, operationalized in the Android® and iOS® systems, called Operational Monitoring Application (AMO), is also presented. The AMO is a means of evaluation that aims the operative monitoring without the need for the user to be physically and/or geographically linked to a professional. In addition, the analysis of the data obtained by the AMO can contribute significantly to research on the subject. The version presented here used the following validated scales: Dental Fear Survey (DFS), Dental Anxiety Scale (DAS), Pain [short version of McGill Pain (QDM)], Visual Analog Scale VAS), Verbal Dental Scale (VDS) and Numerical Rating Scale (NRS) and alerts for medication use and urgencies.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".