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PURPOSE: Atelectasis otitis media (AtOM) is a chronic condition where the tympanic membrane (TM) becomes retracted towards the middle ear and the ossicular chain. Surgical treatment for this condition could be indicated based on stage of atelectasis, patient's clinical condition and hearing loss. Over the years, AtOM has been treated with various types of tympanoplasty under microscopic view. The aim of this study is to present the results of endoscopic ear surgery in AtOM. METHODS: Forty-five patients who underwent endoscopic trans-canal tympanoplasty were included in the study. Preoperative features, intraoperative findings and postoperative outcomes were collected. RESULTS: Preoperatively, none of the study's patients were classified with a Sadè Grade I, whereas grades II, III and IV were 3 (6.6%), 23 (32.1%) and 19 (67.8%) respectively. The 3 patients with Sadè grade II showed a conductive hearing loss higher than 20 dB and a continuous ear fullness, therefore they were surgically treated. The postoperative graft success rate was estimated at 95.5%. During follow-up, 2 patients showed a TM perforation (at 6 and 12 months after surgery) whereas 1 patient experienced a recurrence of atelectasis in the TM (16 months after surgery). The overall success rate at the final follow-up was calculated at 88.8%. The average preoperative air-conduction threshold was 51.1 ± 21.5, which reduced to 34.6 ± 22.1 (p = 0.04) at follow-up. The preoperative air-bone gap decreased from 28 ± 7.2 to 11.8 ± 10 (p = 0.002) after surgery. CONCLUSION: Atelectasis otitis media might be suitable for exclusive endoscopic surgical treatment, as it appears to exhibit a low recurrence rate and promising audiological outcomes.
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To evaluate the response capabilities, in a public healthcare system otolaryngology job competition examination, of ChatGPT 3.5 and an internet-connected GPT-4 engine (Microsoft Copilot) with the real scores of otolaryngology specialists as the control group. In September 2023, 135 questions divided into theoretical and practical parts were input into ChatGPT 3.5 and an internet-connected GPT-4. The accuracy of AI responses was compared with the official results from otolaryngologists who took the exam, and statistical analysis was conducted using Stata 14.2. Copilot (GPT-4) outperformed ChatGPT 3.5. Copilot achieved a score of 88.5 points, while ChatGPT scored 60 points. Both AIs had discrepancies in their incorrect answers. Despite ChatGPT's proficiency, Copilot displayed superior performance, ranking as the second-best score among the 108 otolaryngologists who took the exam, while ChatGPT was placed 83rd. A chat powered by GPT-4 with internet access (Copilot) demonstrates superior performance in responding to multiple-choice medical questions compared to ChatGPT 3.5.
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OBJECTIVE: Antibiotics have been prescribed routinely in sialendoscopy procedures to reduce the risk of postoperative infection, despite the limited evidence supporting this practice. Being necessary to assess the need for antibiotics in Sialendoscopy, aiming to provide evidence-based guidance to clinicians regarding antibiotic administration in this procedure. MATERIALS & METHOD: A prospective, randomized, double-blind, controlled clinical trial to evaluate the of prophylactic antibiotics in Sialendoscopy was designed. RESULTS: A total of 80 patients were included in this study, including 57 females (71.8%) and 23 males (28.8%). In terms of prophylaxis, 36 patients (45%) received prophylactic treatment, and 44 patients (55%) did not. The occurrence of infectious events was observed in 2 patients (5.6%) with prophylaxis and 4 patients (9.1%) without prophylaxis. However, this difference was not statistically significant (p = 0.556). CONCLUSION: In conclusion, our prospective, randomized clinical trial aimed to address the debate regarding the use of prophylactic antibiotics in sialendoscopy. Our study's findings suggest that the routine use antibiotics may not be necessary to prevent postoperative infections in sialendoscopy procedures. These results have important implications for clinical practice, potentially reducing the unnecessary use of antibiotics and addressing concerns related to antibiotic resistance and adverse drug reactions.
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OBJECTIVE: To investigate the consistency of Chatbot Generative Pretrained Transformer (ChatGPT)-4 in the analysis of clinical pictures of common laryngological conditions. STUDY DESIGN: Prospective uncontrolled study. SETTING: Multicenter study. METHODS: Patient history and clinical videolaryngostroboscopic images were presented to ChatGPT-4 for differential diagnoses, management, and treatment(s). ChatGPT-4 responses were assessed by 3 blinded laryngologists with the artificial intelligence performance instrument (AIPI). The complexity of cases and the consistency between practitioners and ChatGPT-4 for interpreting clinical images were evaluated with a 5-point Likert Scale. The intraclass correlation coefficient (ICC) was used to measure the strength of interrater agreement. RESULTS: Forty patients with a mean complexity score of 2.60 ± 1.15. were included. The mean consistency score for ChatGPT-4 image interpretation was 2.46 ± 1.42. ChatGPT-4 perfectly analyzed the clinical images in 6 cases (15%; 5/5), while the consistency between GPT-4 and judges was high in 5 cases (12.5%; 4/5). Judges reported an ICC of 0.965 for the consistency score (P = .001). ChatGPT-4 erroneously documented vocal fold irregularity (mass or lesion), glottic insufficiency, and vocal cord paralysis in 21 (52.5%), 2 (0.05%), and 5 (12.5%) cases, respectively. ChatGPT-4 and practitioners indicated 153 and 63 additional examinations, respectively (P = .001). The ChatGPT-4 primary diagnosis was correct in 20.0% to 25.0% of cases. The clinical image consistency score was significantly associated with the AIPI score (rs = 0.830; P = .001). CONCLUSION: The ChatGPT-4 is more efficient in primary diagnosis, rather than in the image analysis, selecting the most adequate additional examinations and treatments.
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OBJECTIVE: To investigate the platelet-rich plasma (PRP) effectiveness in patients with a long-lasting postviral olfactory dysfunction (LPOD). METHODS: Forty-three consecutive patients with a long-lasting postviral OD were prospectively recruited. The injection of 1 mL of PRP was carried out in both olfactory clefts. The pre- to 6-month post-PRP injection change in olfaction was assessed with the olfactory disorder questionnaire (ODQ) and the threshold, discrimination, and identification (TDI) tests. RESULTS: Forty-three patients received bilateral PRP injections (24 females). The mean age of patients was 58.9 ± 16.8 years. The mean duration of LPOD was 8.7 years. The pre to 6-month post-injection mean TDI significantly improved from 10.3 ± 10.2 to 20.12 ± 12.07 (p = 0.001). The mean ODQ significantly decreased from 29.8 ± 13.0 to 23.4 ± 11.3 (p = 0.013). The average change of the TDI and the ODQ were 9.8 and 6.4, respectively. Age was inversely associated with the 6-month threshold score. CONCLUSION: PRP appears to be a promising therapeutic strategy for long-lasting postviral OD. Our findings support the conduction of controlled randomized trial in this population of patients.
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OBJECTIVE: To investigate the minimum therapeutic duration for patients with primary laryngopharyngeal reflux disease (LPRD) through the evaluation of symptom changes at multiple time points. STUDY DESIGN: Prospective uncontrolled. SETTING: University medical center. METHODS: Patients with LPRD at the 24-hour hypopharyngeal-esophageal multichannel intraluminal impedance-pH monitoring were recruited from the European Reflux Clinic. Depending on the type of LPRD, patients were treated with a combination of proton-pump inhibitors, alginate, or magaldrate. Symptoms were evaluated with the reflux symptom score (RSS) at baseline and throughout treatment (1-, 3-, 6-, and 9-month posttreatment). The most appropriate therapeutic duration was determined using the RSS changes. Signs were evaluated with the reflux sign assessment. RESULTS: A total of 159 patients completed the study. The mean age was 49.9 ± 15.7 years. At 1-month posttreatment, 97 patients (61.0%) were considered as early responders to treatment, and the treatment was stopped for 52 patients (32.7%). Of the 62 early nonresponders, 34 patients (21.4%) reached responded to treatment after 3 to 9 months. The cumulative therapeutic success rate at 1-month posttreatment (61.0%) progressively increased to reach a range of 82.4% to 99.3% at 9-month posttreatment. The RSS mainly decreased in the first month of treatment in early responders. In early nonresponders, RSS progressively decreased throughout the 9-month treatment period. The baseline severity of RSS is a strong predictor of therapeutic response. CONCLUSION: A therapeutic regimen of 1 month can be sufficient to treat one third of LPRD patients. The early nonresponders may require 3 to 9 months of treatment.
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Background: To investigate the perception of young European otolaryngologists (OTOs), i.e., head and neck surgeons, toward transoral robotic surgery (TORS). Methods: Members of the Young Confederation of European Otorhinolaryngology-Head and Neck Surgery and Young Otolaryngologists of International Federation of Otorhinolaryngological Societies were surveyed about TORS perception and practice. Results: The survey was completed by 120 young OTOS (26%). The most important barriers to TORS were robot availability (73%), cost (69%), and lack of training (37%). The participants believed that the main benefits include better surgical filed view (64%), shorter hospital stay (62%), and better postoperative outcomes (61%) than the conventional approach. Head and neck surgeons considered cT1-T2 oropharyngeal cancers (94%), resection of base of tongue for sleep apnea (86%), or primary unknown cancer (76%) as the most appropriate indications. A total of 67% of TORS surgeons assessed themselves as adequately trained in TORS. Conclusions: Young European OTOs report positive perception, adoption, and knowledge of TORS. The cost-related unavailability and the lack of training or access are reported to be the most important barriers for the spread of TORS.
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Implant-prosthetic rehabilitations of severely atrophic posterior maxillary sectors currently is challenging, often requiring multiple surgeries and long rehabilitation times. Recently, graftless techniques (e.g. zygomatic, pterygoid and nasal implants) have gained popularity as they offer a reduction in rehabilitation time, aligning more closely with patient preferences but may not be feasible for sectorial rehabilitations. Subperiosteal implants, suggested for full-arch rehabilitations of atrophic maxilla, haven't been explored for sectorial rehabilitations. In this report we present the case of a patient with maxillary molar edentulism, rehabilitated with a subperiosteal implant.
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The aim of this retrospective study was to analyze a series of patients who underwent full-arch rehabilitation of the atrophic maxilla using additively manufactured subperiosteal implants, between August 2018 and January 2023, at the Universities of Sassari and Poznan. In total, 36 patients and 72 implants were included, with no implants lost during follow-up, and a success rate of 90.3%. Seven (9.7%) of the implants showed class 1 exposure. Bleeding on probing was detected in 10.4% of the abutments at 6 months, 7.9% at 1 year, 10% at 2 years, 7% at 3 years, and 11.4% at 4 years. No significant bone resorption under the abutments was detected during the whole observation period. Based on the findings from this study, additively manufactured subperiosteal implants could represent a safe and reliable technique for full-arch rehabilitation in patients with severe maxillary atrophy.
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The increasing development of artificial intelligence (AI) generative models in otolaryngology-head and neck surgery will progressively change our practice. Practitioners and patients have access to AI resources, improving information, knowledge, and practice of patient care. This article summarizes the currently investigated applications of AI generative models, particularly Chatbot Generative Pre-trained Transformer, in otolaryngology-head and neck surgery.
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The inaugural total laryngectomy in history was conducted by Billroth in 1873. Nevertheless, significant enhancements to the technique were achieved through the contributions of Gluck, Sorensen, and various other surgeons. Throughout the twentieth century, advancements in anesthesia, infectious disease, hospital hygiene, antibiotic therapy, resuscitation, and the expertise of numerous laryngologists elevated total laryngectomy to a pivotal surgical intervention in head and neck surgery. The latter half of the twentieth century witnessed a paradigm shift with the emergence of organ preservation protocols. Total laryngectomy became the preferred choice for patients experiencing radiotherapy failure. However, the widespread use of laryngeal conservative treatments appears to be correlated with a decline in overall survival rates in the United States and Europe. The evolution of new minimally invasive surgical approaches in the twenty-first century may usher in a revolutionary era in the management of laryngeal carcinoma, offering the potential for improved survival and functional outcomes.
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PURPOSE: This study evaluates the efficacy of two advanced Large Language Models (LLMs), OpenAI's ChatGPT 4 and Google's Gemini Advanced, in providing treatment recommendations for head and neck oncology cases. The aim is to assess their utility in supporting multidisciplinary oncological evaluations and decision-making processes. METHODS: This comparative analysis examined the responses of ChatGPT 4 and Gemini Advanced to five hypothetical cases of head and neck cancer, each representing a different anatomical subsite. The responses were evaluated against the latest National Comprehensive Cancer Network (NCCN) guidelines by two blinded panels using the total disagreement score (TDS) and the artificial intelligence performance instrument (AIPI). Statistical assessments were performed using the Wilcoxon signed-rank test and the Friedman test. RESULTS: Both LLMs produced relevant treatment recommendations with ChatGPT 4 generally outperforming Gemini Advanced regarding adherence to guidelines and comprehensive treatment planning. ChatGPT 4 showed higher AIPI scores (median 3 [2-4]) compared to Gemini Advanced (median 2 [2-3]), indicating better overall performance. Notably, inconsistencies were observed in the management of induction chemotherapy and surgical decisions, such as neck dissection. CONCLUSIONS: While both LLMs demonstrated the potential to aid in the multidisciplinary management of head and neck oncology, discrepancies in certain critical areas highlight the need for further refinement. The study supports the growing role of AI in enhancing clinical decision-making but also emphasizes the necessity for continuous updates and validation against current clinical standards to integrate AI into healthcare practices fully.
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OBJECTIVE: To review the current literature on the application, accuracy, and performance of Chatbot Generative Pre-Trained Transformer (ChatGPT) in Otolaryngology-Head and Neck Surgery. DATA SOURCES: PubMED, Cochrane Library, and Scopus. REVIEW METHODS: A comprehensive review of the literature on the applications of ChatGPT in otolaryngology was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. CONCLUSIONS: ChatGPT provides imperfect patient information or general knowledge related to diseases found in Otolaryngology-Head and Neck Surgery. In clinical practice, despite suboptimal performance, studies reported that the model is more accurate in providing diagnoses, than in suggesting the most adequate additional examinations and treatments related to clinical vignettes or real clinical cases. ChatGPT has been used as an adjunct tool to improve scientific reports (referencing, spelling correction), to elaborate study protocols, or to take student or resident exams reporting several levels of accuracy. The stability of ChatGPT responses throughout repeated questions appeared high but many studies reported some hallucination events, particularly in providing scientific references. IMPLICATIONS FOR PRACTICE: To date, most applications of ChatGPT are limited in generating disease or treatment information, and in the improvement of the management of clinical cases. The lack of comparison of ChatGPT performance with other large language models is the main limitation of the current research. Its ability to analyze clinical images has not yet been investigated in otolaryngology although upper airway tract or ear images are an important step in the diagnosis of most common ear, nose, and throat conditions. This review may help otolaryngologists to conceive new applications in further research.
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BACKGROUND: The widespread diffusion of Artificial Intelligence (AI) platforms is revolutionizing how health-related information is disseminated, thereby highlighting the need for tools to evaluate the quality of such information. This study aimed to propose and validate the Quality Assessment of Medical Artificial Intelligence (QAMAI), a tool specifically designed to assess the quality of health information provided by AI platforms. METHODS: The QAMAI tool has been developed by a panel of experts following guidelines for the development of new questionnaires. A total of 30 responses from ChatGPT4, addressing patient queries, theoretical questions, and clinical head and neck surgery scenarios were assessed by 27 reviewers from 25 academic centers worldwide. Construct validity, internal consistency, inter-rater and test-retest reliability were assessed to validate the tool. RESULTS: The validation was conducted on the basis of 792 assessments for the 30 responses given by ChatGPT4. The results of the exploratory factor analysis revealed a unidimensional structure of the QAMAI with a single factor comprising all the items that explained 51.1% of the variance with factor loadings ranging from 0.449 to 0.856. Overall internal consistency was high (Cronbach's alpha = 0.837). The Interclass Correlation Coefficient was 0.983 (95% CI 0.973-0.991; F (29,542) = 68.3; p < 0.001), indicating excellent reliability. Test-retest reliability analysis revealed a moderate-to-strong correlation with a Pearson's coefficient of 0.876 (95% CI 0.859-0.891; p < 0.001). CONCLUSIONS: The QAMAI tool demonstrated significant reliability and validity in assessing the quality of health information provided by AI platforms. Such a tool might become particularly important/useful for physicians as patients increasingly seek medical information on AI platforms.
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OBJECTIVES: The development of artificial intelligence-powered language models, such as Chatbot Generative Pre-trained Transformer (ChatGPT) or Large Language Model Meta AI (Llama), is emerging in medicine. Patients and practitioners have full access to chatbots that may provide medical information. The aim of this study was to explore the performance and accuracy of ChatGPT and Llama in treatment decision-making for bilateral vocal fold paralysis (BVFP). METHODS: Data of 20 clinical cases, treated between 2018 and 2023, were retrospectively collected from four tertiary laryngology centers in Europe. The cases were defined as the most common or most challenging scenarios regarding BVFP treatment. The treatment proposals were discussed in their local multidisciplinary teams (MDT). Each case was presented to ChatGPT-4.0 and Llama Chat-2.0, and potential treatment strategies were requested. The Artificial Intelligence Performance Instrument (AIPI) treatment subscore was used to compare both Chatbots' performances to MDT treatment proposal. RESULTS: Most common etiology of BVFP was thyroid surgery. A form of partial arytenoidectomy with or without posterior transverse cordotomy was the MDT proposal for most cases. The accuracy of both Chatbots was very low regarding their treatment proposals, with a maximum AIPI treatment score in 5% of the cases. In most cases even harmful assertions were made, including the suggestion of vocal fold medialisation to treat patients with stridor and dyspnea. ChatGPT-4.0 performed significantly better in suggesting the correct treatment as part of the treatment proposal (50%) compared to Llama Chat-2.0 (15%). CONCLUSION: ChatGPT and Llama are judged as inaccurate in proposing correct treatment for BVFP. ChatGPT significantly outperformed Llama. Treatment decision-making for a complex condition such as BVFP is clearly beyond the Chatbot's knowledge expertise. This study highlights the complexity and heterogeneity of BVFP treatment, and the need for further guidelines dedicated to the management of BVFP.