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Introduction: Sialendoscopy has emerged in the last decades as a groundbreaking technique, offering a minimally invasive approach for exploring and managing salivary gland disorders. More recently, the advent of chatbots, powered by advanced natural processing language and artificial intelligence algorithms, has revolutionized the way healthcare professionals and patients access and analyze medical information and potentially will support soon the clinical decision-making process. Materials and methods: A prospective, cross-sectional study was designed to assess the level of agreement between Chat-GPT and 10 expert sialendoscopists aiming the capabilities of Chat-GPT to further improve the management of salivary gland disorders. Results: The mean level of agreement was 3.4 (SD: 0.69; Min: 2, Max: 4) for Chat-GPT's answers while it was 4.1 (SD: 0.56; Min: 3, Max: 5) for the group of EESS (p < 0.015). The overall Wilcoxon signed-rank test yielded a significance level of p < 0.026 when comparing the level of agreement between Chat-GPT and EESS. The mean number of therapeutic alternatives suggested by Chat-GPT was 3.33 (SD: 1.2; Min: 2, Max: 5), while it was 2.6 (SD: 0.51; Min: 2, Max: 3) for the group of EESS; p = 0.286 (95% CI − 0.385 to 1.320). Conclusion: Chat-GPT represents a promising tool in the clinical decision-making process within the salivary gland clinic, particularly for patients who are candidates for sialendoscopy treatment. Additionally, it serves as a valuable source of information for patients. However, further development is necessary to enhance the reliability of these tools and ensure their safety and optimal use in the clinical setting. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the reliability and validity of the Artificial Intelligence Performance Instrument (AIPI). Methods: Medical records of patients consulting in otolaryngology were evaluated by physicians and ChatGPT for differential diagnosis, management, and treatment. The ChatGPT performance was rated twice using AIPI within a 7-day period to assess test–retest reliability. Internal consistency was evaluated using Cronbach's α. Internal validity was evaluated by comparing the AIPI scores of the clinical cases rated by ChatGPT and 2 blinded practitioners. Convergent validity was measured by comparing the AIPI score with a modified version of the Ottawa Clinical Assessment Tool (OCAT). Interrater reliability was assessed using Kendall's tau. Results: Forty-five patients completed the evaluations (28 females). The AIPI Cronbach's alpha analysis suggested an adequate internal consistency (α = 0.754). The test–retest reliability was moderate-to-strong for items and the total score of AIPI (rs = 0.486, p = 0.001). The mean AIPI score of the senior otolaryngologist was significantly higher compared to the score of ChatGPT, supporting adequate internal validity (p = 0.001). Convergent validity reported a moderate and significant correlation between AIPI and modified OCAT (rs = 0.319; p = 0.044). The interrater reliability reported significant positive concordance between both otolaryngologists for the patient feature, diagnostic, additional examination, and treatment subscores as well as for the AIPI total score. Conclusions: AIPI is a valid and reliable instrument in assessing the performance of ChatGPT in ear, nose and throat conditions. Future studies are needed to investigate the usefulness of AIPI in medicine and surgery, and to evaluate the psychometric properties in these fields. [ABSTRACT FROM AUTHOR]

Objectives: To study the performance of ChatGPT in the management of laryngology and head and neck (LHN) cases. Methods: History and clinical examination of patients consulting at the Otolaryngology-Head and Neck Surgery department were presented to ChatGPT, which was interrogated for differential diagnosis, management, and treatment. The ChatGPT performance was assessed by two blinded board-certified otolaryngologists using the following items of a composite score and the Ottawa Clinic Assessment Tool: differential diagnosis; additional examination; and treatment options. The complexity of clinical cases was evaluated with the Amsterdam Clinical Challenge Scale test. Results: Forty clinical cases were submitted to ChatGPT, accounting for 14 (35%), 12 (30%), and 14 (35%) easy, moderate and difficult cases, respectively. ChatGPT indicated a significant higher number of additional examinations compared to practitioners (p = 0.001). There was a significant agreement between practitioners and ChatGPT for the indication of some common examinations (audiometry, ultrasonography, biopsy, gastrointestinal endoscopy or videofluoroscopy). ChatGPT never indicated some important additional examinations (PET–CT, voice quality assessment, or impedance-pH monitoring). ChatGPT reported highest performance in the proposition of the primary (90%) or the most plausible differential diagnoses (65%), and the therapeutic options (60–68%). The ChatGPT performance in the indication of additional examinations was lowest. Conclusions: ChatGPT is a promising adjunctive tool in LHN practice, providing extensive documentation about disease-related additional examinations, differential diagnoses, and treatments. The ChatGPT is more efficient in diagnosis and treatment, rather than in the selection of the most adequate additional examination. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the consistency between the international guidelines recommendations and worldwide standard practices regarding diagnostic work-up and follow-up strategies for managing patients with Chronic Rhinosinusitis with Nasal Polyps (CRSwNP) in the era of monoclonal antibodies. Methods: A questionnaire developed by the Rhinology section of the Young Otolaryngologists of the International Federation of Oto-rhino-laryngological Societies (Yo-IFOS) included items regarding the management of CRSwNP patients, monoclonal prescription, surgical and follow-up procedures, awareness of biologicals availability, and other relevant clinical practices. The online survey was directed to otolaryngologists and distributed in Europe, North America, South America, and the Middle East through otolaryngological and/or rhinological societies. Results: A total of 202 responses were analyzed; the mean participants' age was 45 ± 11 (73% men and 27% women), and 31% were from the United States, Canada 19%, Europe 45%, Middle East and South America 5%. Only 60% of the respondents declared using validated symptoms and endoscopic score systems in their clinical practice. Several practice discrepancies emerged in our cohort, including preferred surgical approach, prescription of preoperative oral steroids, and perioperative antibiotics (59% and 58%, respectively), as well as divergent awareness levels of available biologics for CRSwNP worldwide. Conclusions: CRSwNP needs a complex and time-consuming assessment, according to the latest guidelines. There seems to be a gap between these recommendations and the real-world data, which should draw more attention to bringing them into uniform clinical practice in the near future. [ABSTRACT FROM AUTHOR]

Purpose: Vascular perfusion research has been dedicated to identify inexpensive, effective, and easy to use methods to assess free flap perfusion for both buried and non-buried flaps. Methods: Systematic review of complications in patients underwent Head and Neck microsurgical reconstruction and vascular implantable Doppler monitoring. Results: Sixteen articles were included for qualitative analysis. 2535 (92.2%) patients received IDP monitorization. Venous thrombosis was the most common vascular complication effecting 28 (1.1%). Regarding complications potentially related to the use of the IDP, just one study described the presence of granuloma formation along the suture line in 2 (0.07%) patients. Conclusions: Our findings indicated that Cook–Swartz IDP will represents a safe and effective device for FF monitoring in HN reconstructive micro-surgery. A detailed prospective registration of the results and complications related to the use of IDP remains mandatory to precisely estimate results, cost, and complications. [ABSTRACT FROM AUTHOR]

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.A prospective, randomized, double-blind, controlled clinical trial to evaluate the of prophylactic antibiotics in Sialendoscopy was designed.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).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.Materials & method: 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.A prospective, randomized, double-blind, controlled clinical trial to evaluate the of prophylactic antibiotics in Sialendoscopy was designed.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).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.Results: 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.A prospective, randomized, double-blind, controlled clinical trial to evaluate the of prophylactic antibiotics in Sialendoscopy was designed.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).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.Conclusion: 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.A prospective, randomized, double-blind, controlled clinical trial to evaluate the of prophylactic antibiotics in Sialendoscopy was designed.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).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. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Exploring the potential of Chat-GPT as a supportive tool for sialendoscopy clinical decision making and patient information support" published in the European Archives of Oto-Rhino-Laryngology. The correction states that the ethics declaration statement was missing from the original article and should have included information about the author Jerome R. Lechien's involvement as a guest editor of a special issue on 'ChatGPT and Artificial Intelligence in Otolaryngology-Head and Neck Surgery'. The original article has been updated to include this information. The publisher, Springer Nature, remains neutral regarding jurisdictional claims and institutional affiliations. The authors of the article are Carlos M. Chiesa-Estomba, Jerome R. Lechien, Luigi A. Vaira, Aina Brunet, Giovanni Cammaroto, Miguel Mayo-Yanez, Alvaro Sanchez-Barrueco, and Carlos Saga-Gutierrez. [Extracted from the article]

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.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.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).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.Methods: 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.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.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).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.Results: 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.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.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).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.Conclusions: 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.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.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).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. [ABSTRACT FROM AUTHOR]