Objectives. The aim of this study was to evaluate the differences in clinical and laboratory features between eosinophilic chronic rhinosinusitis (ECRS) and non-ECRS and to compare diagnostic criteria for ECRS.Methods. We compared clinical features and/or laboratory findings classified as ECRS and non-ECRS according to various diagnostic criteria (histological and clinical). We also analyzed studies to compare endoscopic findings, symptom scores, laboratory findings, and computed tomography (CT) findings between ECRS and non-ECRS.Results. Our search included 55 studies with 6,143 patients. A comparison of clinical features and/or laboratory criteria with histological criteria showed no significant differences in nasal symptom scores and CT scores according to criteria. Serum eosinophil levels showed differences across the criteria, with ECRS consistently characterized by higher serum eosinophil levels than non-ECRS. Among the four criteria, the Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis (JESREC) criteria and tissue eosinophilia (≥70) were associated with decreased olfactory function. In laboratory findings, the eosinophil percentage (standardized mean difference [SMD], 1.561; 95% confidence interval [CI], 1.329–1.794; P<0.001) and eosinophil count (SMD, 1.493; 95% CI, 1.134–1.852; P<0.001) of eosinophils were higher in ECRS than non-ECRS. In clinical findings, nasal symptom scores (SMD, 0.382; 95% CI, 0.156–0.608; P<0.001), endoscopic nasal polyp scores (SMD, 0.581; 95% CI, 0.314–0.848; P<0.001), and olfactory dysfunction (SMD, 0.416; 95% CI, 0.037–0.794; P=0.031) were higher in ECRS than in non-ECRS. With regard to CT findings, the whole-sinus opacification score (SMD, 0.824; 95% CI, 0.588–1.059; P<0.001) was higher in ECRS than in non-ECRS. In particular, there were significant differences in anterior ethmoid sinus and sphenoid sinus opacification.Conclusion. ECRS and non-ECRS differ in their clinical and laboratory features. When histological confirmation is difficult on an outpatient basis, ECRS could be diagnosed using clinical features and/or laboratory findings.

This study presents an up-to-date survey of the use of artificial intelligence (AI) in the field of otorhinolaryngology, considering opportunities, research challenges, and research directions. We searched PubMed, the Cochrane Central Register of Controlled Trials, Embase, and the Web of Science. We initially retrieved 458 articles. The exclusion of non-English publications and duplicates yielded a total of 90 remaining studies. These 90 studies were divided into those analyzing medical images, voice, medical devices, and clinical diagnoses and treatments. Most studies (42.2%, 38/90) used AI for image-based analysis, followed by clinical diagnoses and treatments (24 studies). Each of the remaining two subcategories included 14 studies. Machine learning and deep learning have been extensively applied in the field of otorhinolaryngology. However, the performance of AI models varies and research challenges remain.

Background: There have been reports investigating the use of olfactory training in olfactory dysfunction after COVID-19. Objective: We evaluated the effect of olfactory training on the olfactory dysfunction of patients infected with COVID-19. Methods: We searched PubMed, EMBASE, the Web of Science, the Cochrane database, SCOPUS, and Google Scholar up to May 2022. We retrieved studies that compared the extents of olfactory dysfunction before and after olfactory training. We performed a subgroup analysis by the duration of olfactory dysfunction. Results: The olfactory score after olfactory training (standard mean difference [SMD] = 1.0830, 95% confidence interval [CI] [0.6416; 1.5245], P < .0001, I ² = 90.4%) was higher than that before training. The olfactory dysfunction rate differed significantly (OR = 0.0232, 95% CI [0.0052; 0.1044], P < .0001, I ² = 63.1%) before and after olfactory training. On subgroup analysis, although patients with both acute (onset < 30 days prior) and chronic (onset > 30 days prior) olfactory dysfunction evidenced clinically significant improvements, training during acute dysfunction (compared to acute dysfunction) increased the olfactory score to a greater extent (SMD = 1.7779, 95% CI [1.0077; 2.5481] vs 0.6928 [0.2143; 1.1712], P = 0.0190). Moreover, as a result of subgroup analysis by dividing the included studies into2 using 2-month training period as standard, there was no statistically significant difference in the effect of the training period in the included study. Conclusion: Olfactory training improved olfactory disorders caused by COVID-19. Such training was effective in both the acute and chronic phases.

Objectives. A systematic review of the literature was conducted to evaluate hypotensive agents in terms of their adverse effects and associations with perioperative morbidity in patients undergoing nasal surgery.Methods. Two authors independently searched databases (Medline, Scopus, and Cochrane databases) up to February 2020 for randomized controlled trials comparing the perioperative administration of a hypotensive agent with a placebo or other agent. The outcomes of interest for this analysis were intraoperative morbidity, operative time, intraoperative bleeding, hypotension, postoperative nausea/vomiting, and postoperative pain. Both a standard pairwise meta-analysis and network meta-analysis were conducted.Results. Our analysis was based on 37 trials. Treatment networks consisting of six interventions (placebo, clonidine, dexmedetomidine, beta-blockers, opioids, and nitroglycerine) were defined for the network meta-analysis. Dexmedetomidine resulted in the greatest differences in intraoperative bleeding (−0.971; 95% confidence interval [CI], −1.161 to −0.781), intraoperative fentanyl administration (−3.683; 95% CI, −4.848 to −2.518), and postoperative pain (−2.065; 95% CI, −3.170 to −0.960) compared with placebo. The greatest difference in operative time compared with placebo was achieved with clonidine (−0.699; 95% CI, −0.977 to −0.421). All other agents also had beneficial effects on the measured outcomes. Dexmedetomidine was less likely than other agents to cause adverse effects.Conclusion. This study demonstrated the superiority of the systemic use of dexmedetomidine as a perioperative hypotensive agent compared with the other five tested agents. However, the other agents were also superior to placebo in improving operative time, intraoperative bleeding, and postoperative pain.

Mesenchymal stem cells (MSCs) are increasingly used as regenerative therapies for patients in the preclinical and clinical phases of various diseases. However, the main limitations of such therapies include functional heterogeneity and the lack of appropriate quality control (QC) methods for functional screening of MSC lines; thus, clinical outcomes are inconsistent. Recently, machine learning (ML)-based methods, in conjunction with single-cell morphological profiling, have been proposed as alternatives to conventional in vitro/vivo assays that evaluate MSC functions. Such methods perform in silico analyses of MSC functions by training ML algorithms to find highly nonlinear connections between MSC functions and morphology. Although such approaches are promising, they are limited in that extensive, high-content single-cell imaging is required; moreover, manually identified morphological features cannot be generalized to other experimental settings. To address these limitations, we propose an end-to-end deep learning (DL) framework for functional screening of MSC lines using live-cell microscopic images of MSC populations. We quantitatively evaluate various convolutional neural network (CNN) models and demonstrate that our method accurately classifies in vitro MSC lines to high/low multilineage differentiating stress-enduring (MUSE) cells markers from multiple donors. A total of 6,120 cell images were obtained from 8 MSC lines, and they were classified into two groups according to MUSE cell markers analyzed by immunofluorescence staining and FACS. The optimized DenseNet121 model showed area under the curve (AUC) 0.975, accuracy 0.922, F1 0.922, sensitivity 0.905, specificity 0.942, positive predictive value 0.940, and negative predictive value 0.908. Therefore, our DL-based framework is a convenient high-throughput method that could serve as an effective QC strategy in future clinical biomanufacturing processes.

Objectives. The aim of this study was to compare the effect of steroid-impregnated spacers to that of conventional management after endoscopic sinus surgery (ESS) in patients with chronic rhinosinusitis (CRS).Methods. Six databases were searched from inception until November 2022. Sixteen studies were found that compared the improvement of chronic sinusitis-related symptoms and postoperative outcomes between a steroid-impregnated spacer group and a control group (non-steroid-impregnated spacers). The Cochrane risk of bias tool (for randomized controlled studies) and the Newcastle-Ottawa Scale (for non-randomized controlled studies) were used to assess the quality of the works included.Results. Regarding the endoscopic findings, the degree of mucosal edema, ethmoid inflammation, crust formation at 2–3 months postoperatively, nasal discharge, polyposis, and scarring/synechia were significantly lower in the steroid-impregnated spacer group. The steroid-impregnated spacer group also showed significantly lower Lund–Kennedy scores and perioperative sinus endoscopy scores than the control group at 2–3 weeks postoperatively. Furthermore, the steroid-impregnated spacer group had lower rates of adhesions, middle turbinate lateralization, polypoid changes, the need for oral steroid use, the need for postoperative therapeutic interventions, and lysis of adhesions than controls. However, no significant between-group differences were found in short-term (2–3 weeks postoperatively) endoscopic findings regarding nasal discharge, postoperative crusting, polyposis, or scarring/synechia.Conclusion. Steroid-impregnated nasal packing reduced the rates of postoperative intervention and recurrent polyposis and inflammation in CRS patients undergoing ESS.