Healthcare Utilization of Oral and Oropharyngeal Cancer Patients in Emergency Department and Outpatient Settings: An 8-year Population-Based Study.

INTRODUCTION: This study aimed to determine trends in the healthcare utilization by Oral Cavity and Oropharyngeal cancer patients across emergency department (ED) and outpatient settings in Alberta and examine the predictors of ED visits. METHODS: This is a retrospective, population-based, cohort study using administrative data collected by all healthcare facilities between 2010 and 2019 in Alberta, Canada. Trend of visits to different facilities, patients' primary diagnosis, and predictors of ED visits were analyzed. RESULTS: In total, 34% of patients had at least one cancer-related ED visit. With a rise of 31% in cancer incidence, there was a notable upswing in visits to outpatient clinics and community offices, while ED visits decreased. Cancer stage, rural residence, high material deprivation score, and treatments were found as predictors of ED visits. CONCLUSION: Improved symptom management and better care access for disadvantaged and rural oral cancer patients may decrease avoidable ED visits.

Trends and predictors of unplanned hospitalization among oral and oropharyngeal cancer patients; an 8-year population-based study.

PURPOSE: The incidence of oral cancers, particularly HPV-related oropharyngeal cancer, is steadily increasing worldwide, presenting a significant healthcare challenge. This study investigates trends and predictors of unplanned hospitalizations for oral cavity cancer (OCC) and oropharyngeal cancer (OPC) patients in the province of Alberta, Canada. METHODS: This retrospective, population-based, cohort study used administrative data collected from all hospitals in the province. Using the Alberta Cancer Registry (ACR), a cohort of adult patients diagnosed with a single primary OCC or OPC between January 2010 and December 2017 was identified. Linking this cohort with the Discharge Abstract Database (DAD), trends in hospitalizations, primary diagnoses, and predictors of unplanned hospitalization (UH) and 30-day unplanned readmission were analyzed. RESULTS: Of 1,721 patients included, 1,244 experienced 2,228 hospitalizations, with 48 % being categorized as UH. The UHs were significantly associated with a higher mortality rate, 18.5 % as compared to 4.6 % for planned, and influenced by sex, age groups, comorbidities, cancer types, stages, and treatment modalities. The rate of UH per patient decreased from 0.69 to 0.54 visits during the study period (P = 0.02). Common diagnoses for UH were palliative care and post-surgical convalescence, while surgery-related complications such as infection and hemorrhage were frequent in 30-day unplanned readmissions. Predictors of UH included cancer stage, material deprivation, and treatment, while cancer type and comorbidity predicted readmissions. CONCLUSION: The rate of UHs showed a noteworthy decline in this study, which could be a result of enhanced care coordination. Furthermore, identified primary diagnosis and predictors associated with UHs and readmissions, provide valuable insights for enhancing the quality of care for cancer patients.

Safety and efficacy of target controlled infusion administration of propofol and remifentanil for moderate sedation in non-hospital dental practice.

Background: Fearful and anxious patients who find dental treatment intolerable without sedative and analgesic support may benefit from moderate sedation. Target controlled infusion (TCI) pumps are superior to bolus injection in maintaining low plasma and effect-site concentration variability, resulting in stable, steady-state drug concentrations. We evaluated the safety and efficacy of moderate sedation with remifentanil and propofol using TCI pumps in non-hospital dental settings. Methods: A prospective chart review was conducted on 101 patients sedated with propofol and remifentanil using TCI pumps. The charts were completed at two oral surgeons and one general dentist's office over 6 months. Hypoxia, hypotension, bradycardia, and over-sedation were considered adverse events and were collected using Tracking and Reporting Outcomes of Procedural Sedation (TROOPS). Furthermore, patient recovery time, sedation length, drug dose, and patient satisfaction questionnaires were used to measure sedation effectiveness. Results: Of the 101 reviewed sedation charts, 54 were of men, and 47 were of women. The mean age of the patients was 40.5 ±18.7 years, and their mean BMI was 25.6 ± 4.4. The patients did not experience hypoxia, bradycardia, and hypotension during the 4694 min of sedation. The average minimum Mean Arterial Pressure (MAP) and heartbeats were 75.1 mmHg and 60.4 bpm, respectively. 98% of patients agreed that the sedation technique met their needs in reducing their anxiety, and 99% agreed that they were satisfied with the sedation 24 hours later. The average sedation time was 46.9 ± 55.6 min, and the average recovery time was 12.4 ± 4.4 min. Remifentanil and propofol had mean initial effect-site concentration doses of 0.96 µ/ml and 1.0 ng/ml respectively. The overall total amount of drug administered was significantly higher in longer sedation procedures compared to shorter ones, while the infusion rate decreased as the procedural stimulus decreased. Conclusion: According to the results of this study, no patients experienced adverse events during sedation, and all patients were kept at a moderate sedation level for a wide range of sedation times and differing procedures. The results showed that TCI pumps are safe and effective for administering propofol and remifentanil for moderate sedation in dentistry.

CHAC1 as a novel biomarker for distinguishing alopecia from other dermatological diseases and determining its severity.

Alopecia Areata (AA) is characterised by an autoimmune response to hair follicles (HFs) and its exact pathobiology remains unclear. The current study aims to look into the molecular changes in the skin of AA patients as well as the potential underlying molecular mechanisms of AA in order to identify potential candidates for early detection and treatment of AA. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to identify key modules, hub genes, and mRNA-miRNA regulatory networks associated with AA. Furthermore, Chi2 as a machine-learning algorithm was used to compute the gene importance in AA. Finally, drug-target construction revealed the potential of repositioning drugs for the treatment of AA. Our analysis using four AA data sets established a network strongly correlated to AA pathogenicity based on GZMA, OXCT2, HOXC13, KRT40, COMP, CHAC1, and KRT83 hub genes. Interestingly, machine learning introduced these genes as important in AA pathogenicity. Besides that, using another ten data sets, we showed that CHAC1 could clearly distinguish AA from similar clinical phenotypes, such as scarring alopecia due to psoriasis. Also, two FDA-approved drug candidates and 30 experimentally validated miRNAs were identified that affected the co-expression network. Using transcriptome analysis, suggested CHAC1 as a potential diagnostic predictor to diagnose AA.