Objective Sex discrepancies have been reported in chronic rhinosinusitis (CRS), but limited data exist exploring sex-specific biological processes and sinonasal quality of life. Study Design Prospective cohort. Setting Academic medical center. Methods Demographics, clinical data, and sinonasal mucus were collected from patients with CRS presenting for surgical consideration over a 5-year period. A random forest model and linear regression were used to assess predictor variables for the 22-item Sino-Nasal Outcome Test (SNOT-22) and subdomains. Enzyme-linked immunosorbent assays were used to measure substance P and tryptase in a subset of mucus samples to explore biological differences by sex. Results In total, 520 patients were studied (mean age 48.3 years, 50.9% female). Males were older (50.1 vs 46.6 years, P = .008), had more polyp disease (48.2% vs 35.5%, P = .004), and had higher mean Lund-Mackay CT score (11.3 vs 9.5, P = .004). Females had a higher overall mean SNOT-22 (40.9 vs 46.9, P = .001) and higher scores in ear/facial, psychological, and sleep domains ( P < .01). Age, objective disease measures, and sex were top predictors for total SNOT-22. Neither mucus substance P or tryptase, alone or paired with sex, correlated with total SNOT-22. Analysis of mucus biomarkers by sex revealed correlation between mucus tryptase in females with the extranasal subdomain ( P = .01). Conclusion Sex differences exist in CRS disease manifestations and presentation for surgical consideration. Detection of mucus (substance P and tryptase) was reliable, but in this exploratory study, we were not able to establish neurogenic or allergic inflammatory processes as a large source of differential disease features between sexes.
BACKGROUND AND PURPOSE: Sinus CT is critically important for the diagnosis of chronic rhinosinusitis. While CT is sensitive for detecting mucosal disease, automated methods for objective quantification of sinus opacification are lacking. We describe new measurements and further clinical validation of automated CT analysis using a convolutional neural network in a chronic rhinosinusitis population. This technology produces volumetric segmentations that permit calculation of percentage sinus opacification, mean Hounsfield units of opacities, and percentage of osteitis.MATERIALS AND METHODS: Demographic and clinical data were collected retrospectively from adult patients with chronic rhinosinusitis, including serum eosinophil count, Lund-Kennedy endoscopic scores, and the SinoNasal Outcomes Test-22. CT scans were scored using the Lund-Mackay score and the Global Osteitis Scoring Scale. CT images were automatically segmented and analyzed for percentage opacification, mean Hounsfield unit of opacities, and percentage osteitis. These readouts were correlated with visual scoring systems and with disease parameters using the Spearman r .RESULTS: Eighty-eight subjects were included. The algorithm successfully segmented 100% of scans and calculated features in a diverse population with CT images obtained on different scanners. A strong correlation existed between percentage opacification and the Lund-Mackay score (r ¼ 0.85, P , .001). Both percentage opacification and the Lund-Mackay score exhibited moderate correlations with the Lund-Kennedy score (r ¼ 0.58, P , .001, and r ¼ 0.58, P , .001, respectively). The percentage osteitis correlated moderately with the Global Osteitis Scoring Scale (r ¼ 0.48, P , .001). CONCLUSIONS:Our quantitative processing of sinus CT images provides objective measures that correspond well to established visual scoring methods. While automation is a clear benefit here, validation may be needed in a prospective, multi-institutional setting.
Background: Despite the rapid growth in the use of hip arthroscopy, standardized data on postoperative pain scores and activity level are lacking. Purpose: To quantify narcotic consumption and use of the stationary bicycle in the early postoperative period after hip arthroscopy. Study Design: Case series; Level of evidence, 4. Methods: In this prospective case series, patients undergoing a primary hip arthroscopy procedure by a single surgeon were asked to fill out a daily survey for 9 days postoperatively. Patients were asked to report their pain level each day on a visual analog scale from 1 to 10, along with the amount of narcotic pain pills they used during those postoperative days (PODs). Narcotic usage was converted to a morphine-equivalent dosage (MED) for each patient. Patients were also instructed to cycle daily starting on the night of surgery for a minimum of 3 minutes twice per day and were asked to rate their pain as a percentage of their preoperative pain level and the number of minutes spent cycling on a stationary bicycle per day. Results: A total of 212 patients were enrolled in this study. Pain levels (POD1, 5.5; POD4, 3.8; POD9, 2.9; P < .0001) and the percentage of preoperative pain (POD1, 51.6%; POD4, 31.8%; POD9, 29.5%; P < .01) significantly decreased over the study period. The amount of narcotics used per day (reported in MED) also significantly decreased (POD1, 27.3; POD4, 22.3; POD9, 8.5; P < .0001). By POD4, 41% of patients had discontinued all narcotics, and by POD9, 65% of patients were completely off narcotic medication. Patients were able to significantly increase the number of minutes spent cycling each day (POD1, 7.6 minutes; POD4, 13.8 minutes; POD9, 19.0 minutes; P < .0001). Patients who received a preoperative narcotic prescription for the affected hip were significantly more likely to require an additional postoperative narcotic prescription ( P < .001). Conclusion: Patients can expect a rapid decrease in narcotic consumption along with a high degree of activity tolerance in the early postoperative period after hip arthroscopy.
Objective: As medical systems focus on patient satisfaction as an important care outcome, specialty clinics are tasked with continued improvement of patients’ experience. When patient expectations for a consultation differ from that of the specialty provider, dissatisfaction with the experience can occur. One source of differing expectations is discordance between the patient’s chief complaint and the clinical rationale for the consultation as requested by the referring provider. We sought to better understand when this discordance occurs, as well as factors contributing to this disorientation of patient and provider expectations in a safety net otolaryngology practice. Methods: A retrospective observational study was performed and records were examined from new patient consultations. Patient questionnaires, including self-reported chief concerns, were compared with the electronic referral documentation. A difference between the patient’s Chief Complaint (CC) and Referral Reason (RR) was defined as CC-RR Discordance. Medical records, pre-consultation patient communication, and scheduling data were also reviewed to evaluate contributing factors. Results: Of the 1155 consultations examined, 952 were included in the analysis. A CC-RR Discordance was found in 175 (18.4%) of new-patient encounters, including 117 (12.3%) that were unable to articulate a CC (unsure of the reason for the appointment), and 58 (6.1%) that stated a CC that was different than the RR. The rate of CC-RR Discordance was higher in patients with female sex ( P < .05), older age ( P < .001), and longer time intervals between referral and appointment ( P < .05). Lack of communication with the patient (instructions or referral notification) by the referring provider was not associated with CC-RR Discordance. Conclusions: Discordance between patient CC and the rationale for a consultation is common in this safety-net otolaryngology practice and may be an important source of patient dissatisfaction. Future opportunities for quality improvement include pre-consultation communication between the specialist and the patient and reducing time intervals between referral and appointment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.