The application of leukocyte- and platelet-rich fibrin (L-PRF) in maxillary sinus augmentation

BACKGROUND

Since the introduction of sinus augmentation in the 1970s the procedure has been performed with or without biomaterials. Autologous blood products (ABPs) for use in sinus augmentation was first introduced in the 2000s, to aid potentially in bone and soft tissue healing.

METHODS

Three different applications of leukocyte- and platelet-rich fibrin (L-PRF) in maxillary sinus augmentation are presented in this case series. In case 1, L-PRF is used in bilateral sinus augmentation to support placement of implants to support a maxillary hybrid denture. Case 2 highlights the use of L-PRF in a complication associate with Schneiderian membrane elevation. Case 3 provides histology taken at the time of implant placement 6 months following L-PRF/xenograft sinus augmentation.

RESULTS

All cases resulted in the successful placement of dental implants. In case 2, an osseodensification procedure was performed with freeze-dried bone allograft, which provided an approximate 4 mm of additional vertical height for implant placement. Histology from case 3 at 6 months post sinus augmentation demonstrated the presence of new vital bone in contact with the xenograft.

CONCLUSION

To date, there is only a limited amount of evidence reporting on platelet-rich fibrin (PRF) or L-PRF use in maxillary sinus augmentation. Bone gain from either product has ranged from 3.2 to 11.8 mm, with the percentage of newly formed bone reported in case series as 33% ± 5%. Despite the lack of strong evidence, L-PRF appears to have beneficial effects on bone regeneration when used in sinus augmentation.

Evaluation of the need to prescribe opioid medication to control post-surgical pain of different periodontal/oral surgeries

BACKGROUND

To determine the level of perceived pain after different types of periodontal/oral surgical procedures, and the differences in patients' selection of pain management, over the counter (OTC) versus opioid, based on procedure type.

METHODS

Patients undergoing surgical procedures were asked to complete a pain questionnaire at four time points: 1) before surgery 2) first dose of analgesic at home, 3) 24 hours postoperatively, and 4) 72 hours postoperatively. The questionnaire consisted of numerical and descriptive scales to describe the perceived pain.

RESULTS

A total of 198 patients completed the questionnaire. All surgical procedures were grouped into five major categories: bone augmentation procedures (11% BAP), teeth extractions (26% EXT), surgical implant placement (25% IP), mucogingival surgeries (21% MGS), and pocket elimination procedures (17%). IP surgery was associated with significantly less pain compared with MGS and EXT (P <0.05). There was a statistically significant difference for taking any medication based on type of surgical procedure at 24 hours (P <0.05).

CONCLUSIONS

IP is associated with significantly lower perceived pain compared with EXT and MGS surgery. Analgesic consumption was generally parallel to pain perception. A considerable number of patients elected to control the post-surgical pain using OTC medication up to 72 hours. Periodontal/oral surgery procedures vary in the amount of perceived postoperative pain. Tailoring postoperative medications to the type of periodontal/oral surgery performed will help prevent overprescribing of opioids.

Typing and Characterization of Bacteria Using Bottom-up Tandem Mass Spectrometry Proteomics

Methods for rapid and reliable microbial identification are essential in modern healthcare. The ability to detect and correctly identify pathogenic species and their resistance phenotype is necessary for accurate diagnosis and efficient treatment of infectious diseases. Bottom-up tandem mass spectrometry (MS) proteomics enables rapid characterization of large parts of the expressed genes of microorganisms. However, the generated data are highly fragmented, making downstream analyses complex. Here we present TCUP, a new computational method for typing and characterizing bacteria using proteomics data from bottom-up tandem MS. TCUP compares the generated protein sequence data to reference databases and automatically finds peptides suitable for characterization of taxonomic composition and identification of expressed antimicrobial resistance genes. TCUP was evaluated using several clinically relevant bacterial species (Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus pneumoniae, Moraxella catarrhalis, and Haemophilus influenzae), using both simulated data generated by in silico peptide digestion and experimental proteomics data generated by liquid chromatography-tandem mass spectrometry (MS/MS). The results showed that TCUP performs correct peptide classifications at rates between 90.3 and 98.5% at the species level. The method was also able to estimate the relative abundances of individual species in mixed cultures. Furthermore, TCUP could identify expressed β-lactamases in an extended spectrum β-lactamase-producing (ESBL) E. coli strain, even when the strain was cultivated in the absence of antibiotics. Finally, TCUP is computationally efficient, easy to integrate in existing bioinformatics workflows, and freely available under an open source license for both Windows and Linux environments.