DESIGN: Retrospective assessment using the Peer Assessment Rating (PAR) index.

SETTING: Consecutive patients treated by one consultant orthodontist at a tertiary care cleft center.

PARTICIPANTS: One hundred twenty-seven patients with either complete unilateral cleft lip and palate (UCLP) or bilateral cleft lip and palate (BCLP) consecutively treated with fixed appliances.

INTERVENTION: Fixed orthodontic appliance treatment and orthognathic surgery when required.

OUTCOMES: The PAR index assessment was carried out by a calibrated-independent assessor. Treatment duration, the number of patient visits, and data on dental anomalies were drawn from patient records and radiographs.

RESULTS: One hundred two patients' study models were assessed after exclusions. Mean start PAR score for UCLP (n = 71) was 43.9 (95% CI, 41.2-46.6, SD 11.5), with a mean score reduction of 84.3% (95% CI, 81.9-86.7, SD 10.1). The UCLP mean treatment time was 23.7 months with 20.1 appointments. Mean start PAR score for BCLP (n = 31) was 43.4 (95% CI, 39.2-47.6, SD 11.4), with a mean score reduction of 80.9% (95% CI, 76.3-85.5, SD 12.5). The BCLP mean treatment time was 27.8 months with 20.5 appointments.

Methods: We collected 3794 corneal images from 542 eyes of 280 subjects and developed seven deep learning models based on anterior and posterior eccentricity, anterior and posterior elevation, anterior and posterior sagittal curvature, and corneal thickness maps to extract deep corneal features. An independent subset with 1050 images collected from 150 eyes of 85 subjects from a separate center was used to validate models. We developed a hybrid deep learning model to detect KCN. We visualized deep features of corneal parameters to assess the quality of learning subjectively and computed area under the receiver operating characteristic curve (AUC), confusion matrices, accuracy, and F1 score to evaluate models objectively.

Results: In the development dataset, 204 eyes were normal, 123 eyes were suspected KCN, and 215 eyes had KCN. In the independent validation dataset, 50 eyes were normal, 50 eyes were suspected KCN, and 50 eyes were KCN. Images were annotated by three corneal specialists. The AUC of the models for the two-class and three-class problems based on the development set were 0.99 and 0.93, respectively.

Conclusions: The hybrid deep learning model achieved high accuracy in identifying KCN based on corneal maps and provided a time-efficient framework with low computational complexity.

SOURCE OF FUNDING: The study was funded by International Islamic University Malaysia (P-RIGS18-036-0036).

OBJECTIVE: The systematic review is aimed at evaluating the value of PRF in different areas of surgery.

DATA SOURCES: A systematic review of articles sourced from MEDLINE-pubmed (2008-2017(July)) was done. Additional articles were searched through GOOGLE SCHOLAR and SCIENCE DIRECT. Search terms such as Platelet rich fibrin; Platelet rich fibrin, surgery; Platelet concentrate; second generation concentrate; Applications of PRF in surgery were used.

STUDY SELECTION: Systematic reviews, Randomized control trials, Pilot studies and Case reports were included. Non English articles, in-vitro and animal studies were excluded.

DATA EXTRACTION: Independent sourcing of articles by 3 authors using a set of predefined criteria.

DATA SYNTHESIS: Out of the 25 articles covering various surgical procedures that met the inclusion criteria, positive outcomes were noted in most. Although categorization into one specific type of study was not done, the overall success rate with PRF usage was 78%.No differences between test and control groups were observed in 2 studies and 3 studies showed no significant improvements with the usage of PRF.

LIMITATIONS: The systematic review did not categorize the study designs while evaluating success rates which might be considered as a shortcoming as case reports were also included.