Validation of the Quality Analysis of Medical Artificial Intelligence (QAMAI) tool: a new tool to assess the quality of health information provided by AI platforms.

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.

Past, Present, and Future Diagnostic Methods for the Early Noninvasive Detection of Oral Premalignant Lesions: A State of the Art and Systematic Review.

Objectives: To provide an in-depth analysis of noninvasive methods for the early diagnosis of oral premalignant lesions, focusing on novel biomarkers and optical technologies, and to discuss their potential in improving the prognosis of patients with oral oncological diseases. Methods: This state-of-the-art review examines various noninvasive diagnostic techniques, including the utilization of salivary microRNAs and optical technologies such as Raman spectroscopy, elastic scattering spectroscopy, diffuse reflectance spectroscopy, narrow-band imaging, autofluorescence imaging, toluidine blue staining, and microendoscopy. Results: Several noninvasive techniques have shown varying degrees of effectiveness in detecting oral cancer. Autofluorescence imaging exhibited sensitivities up to 100% but had variable specificity. toluidine blue staining reported sensitivity between 77% and 100% for high-risk lesions or cancer, with specificity around 45% to 67%. Spectroscopy techniques achieved 72% to 100% sensitivities and specificities of 75% to 98%. Microendoscopy presented a sensitivity of 84% to 95% and a specificity of 91% to 95%. Conclusion: The review highlights the strengths and limitations of each noninvasive diagnostic method and their recent advancements. Although promising results have been demonstrated, there is a need for further development of reliable strategies for early detection and intervention in oral oncology.

Performance and Consistency of ChatGPT-4 Versus Otolaryngologists: A Clinical Case Series.

OBJECTIVE: To study the performance of Chatbot Generative Pretrained Transformer-4 (ChatGPT-4) in the management of cases in otolaryngology-head and neck surgery. STUDY DESIGN: Prospective case series. SETTING: Multicenter University Hospitals. METHODS: History, clinical, physical, and additional examinations of adult outpatients consulting in otolaryngology departments of CHU Saint-Pierre and Dour Medical Center were presented to ChatGPT-4, which was interrogated for differential diagnoses, management, and treatment(s). According to specialty, the ChatGPT-4 responses were assessed by 2 distinct, blinded board-certified otolaryngologists with the Artificial Intelligence Performance Instrument. RESULTS: One hundred cases were presented to ChatGPT-4. ChaGPT-4 indicated a mean of 3.34 (95% confidence interval [CI]: 3.09, 3.59) additional examinations per patient versus 2.10 (95% CI: 1.76, 2.34; P = .001) for the practitioners. There was strong consistency (k > 0.600) between otolaryngologists and ChatGPT-4 for the indication of upper aerodigestive tract endoscopy, positron emission tomography and computed tomography, audiometry, tympanometry, and psychophysical evaluations. Primary diagnosis was correctly performed by ChatGPT-4 in 38% to 86% of cases depending on subspecialty. Additional examinations indicated by ChatGPT-4 were pertinent and necessary in 8% to 31% of cases, while the treatment regimen was pertinent in 12% to 44% of cases. The performance of ChatGPT-4 was not influenced by the human-reported level of difficulty of clinical cases. CONCLUSION: ChatGPT-4 may be a promising adjunctive tool in otolaryngology, providing extensive documentation about additional examinations, primary and differential diagnoses, and treatments. The ChatGPT-4 is more effective in providing a primary diagnosis, and less effective in the selection of additional examinations and treatments.

Molecularly defined sinonasal malignancies: an overview with focus on the current WHO classification and recently described provisional entities.

Classification of tumors of the head and neck has evolved in recent decades including a widespread application of molecular testing in tumors of the sinonasal tract, salivary glands, and soft tissues with a predilection for the head and neck. The availability of new molecular techniques has allowed for the definition of multiple novel tumor types unique to head and neck sites. Moreover, an expanding spectrum of immunohistochemical markers specific to genetic alterations facilitates rapid identification of diagnostic molecular abnormalities. As such, it is currently possible for head and neck pathologists to benefit from a molecularly defined tumor classification while making diagnoses that are still based largely on histopathology and immunohistochemistry. This review covers the principal molecular alterations in sinonasal malignancies, such as alterations in DEK, AFF2, NUTM1, IDH1-2, and SWI/SNF genes in particular, that are important from a practical standpoint for diagnosis, prognosis, and prediction of response to treatment.

Is generative pre-trained transformer artificial intelligence (Chat-GPT) a reliable tool for guidelines synthesis? A preliminary evaluation for biologic CRSwNP therapy.

INTRODUCTION: Biologic therapies for Chronic Rhinosinusitis with Nasal Polyps (CRSwNP) have emerged as an auspicious treatment alternative. However, the ideal patient population, dosage, and treatment duration are yet to be well-defined. Moreover, biologic therapy has disadvantages, such as high costs and limited access. The proposal of a novel Artificial Intelligence (AI) algorithm offers an intriguing solution for optimizing decision-making protocols. METHODS: The AI algorithm was initially programmed to conduct a systematic literature review searching for the current primary guidelines on biologics' clinical efficacy and safety in treating CRSwNP. The review included a total of 12 studies: 6 systematic reviews, 4 expert consensus guidelines, and 2 surveys. Simultaneously, two independent human researchers conducted a literature search to compare the results. Subsequently, the AI was tasked to critically analyze the identified papers, highlighting strengths and weaknesses, thereby creating a decision-making algorithm and pyramid flow chart. RESULTS: The studies evaluated various biologics, including monoclonal antibodies targeting Interleukin-5 (IL-5), IL-4, IL-13, and Immunoglobulin E (IgE), assessing their effectiveness in different patient populations, such as those with comorbid asthma or refractory CRSwNP. Dupilumab, a monoclonal antibody targeting the IL-4 receptor alpha subunit, demonstrated significant improvement in nasal symptoms and quality of life in patients with CRSwNP in several randomized controlled trials and systematic reviews. Similarly, mepolizumab and reslizumab, which target IL-5, have also shown efficacy in reducing nasal polyp burden and improving symptoms in patients with CRSwNP, particularly those with comorbid asthma. However, additional studies are required to confirm the long-term efficacy and safety of these biologics in treating CRSwNP. CONCLUSIONS: Biologic therapies have surfaced as a promising treatment option for patients with severe or refractory CRSwNP; however, the optimal patient population, dosage, and treatment duration are yet to be defined. The application of AI in decision-making protocols and the creation of therapeutic algorithms for biologic drug selection, could offer fascinating future prospects in the management of CRSwNP.

Is there a role for voice therapy in the treatment of laryngopharyngeal reflux? A pilot study.

Objective: The aim of this study was to compare the efficacy of voice therapy combined with standard anti-reflux therapy in reducing symptoms and signs of laryngopharyngeal reflux (LPR). Methods: A randomised clinical trial was conducted. Fifty-two patients with LPR diagnosed by 24 h multichannel intraluminal impedance-pH monitoring were randomly allocated in two groups: medical treatment (MT) and medical plus voice therapy (VT). Clinical symptoms and laryngeal signs were assessed at baseline and after 3 months of treatment with the Reflux Symptom Index (RSI), Reflux Finding Score (RFS), Voice Handicap Index (VHI) and GRBAS scales. Results: Groups had similar scores at baseline. At 3-month follow-up, a significant decrease in RSI and RFS total scores were found in both groups although it appeared to be more robust in the VT group. G and R scores of the GRBAS scale significantly improved after treatment in both groups, with better results in the VT group. The VHI total score at 3 months improved more in the VT group (VHI delta 9.54) than in the MT group (VHI delta 5.38) (p < 0.001). Conclusions: The addition of voice therapy to medications and diet appears to be more effective in improving treatment outcomes in subjects with LPR. Voice therapy warrants consideration in addition to medication and diet when treating patients with LPR.

Malignant carotid body tumors: What we know, what we do, and what we need to achieve. A systematic review of the literature.

Malignant carotid body tumors (MCBT) are rare and diagnosed after detection of nodal or distant metastases. This systematic review (SR) focuses on MCBT initially approached by surgery. Preferred Reporting Items for SR and Meta-Analysis (MA) guided the articles search from 2000 to 2023 on PubMed, Scopus, and Web of Science. Among 3548 papers, 132 (337 patients) were considered for SR; of these, 20 (158 patients) for MA. Malignancy rate was 7.3%, succinate dehydrogenase (SDH) mutation 17%, age at diagnosis between 4th and 6th decades, with a higher prevalence of females. MCBTs were mostly Shamblin III, with nodal and distant metastasis in 79.7% and 44.7%, respectively. Malignancy should be suspected if CBT >4 cm, Shamblin III, painful or otherwise symptomatic, at the extremes of age, bilateral, with multifocal disease, and SDHx mutations. Levels II-III clearance should be performed to exclude nodal metastases and adjuvant treatments considered on a case-by-case basis.

Exploring the potential of Chat-GPT as a supportive tool for sialendoscopy clinical decision making and patient information support.

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.

Validity and reliability of an instrument evaluating the performance of intelligent chatbot: the Artificial Intelligence Performance Instrument (AIPI).

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.

Accuracy of ChatGPT in head and neck oncological board decisions: preliminary findings.

OBJECTIVES: To evaluate the ChatGPT-4 performance in oncological board decisions. METHODS: Twenty medical records of patients with head and neck cancer were evaluated by ChatGPT-4 for additional examinations, management, and therapeutic approaches. The ChatGPT-4 propositions were assessed with the Artificial Intelligence Performance Instrument. The stability of ChatGPT-4 was evaluated through regenerated answers at 1-day interval. RESULTS: ChatGPT-4 provided adequate explanations for cTNM staging in 19 cases (95%). ChatGPT-4 proposed a significant higher number of additional examinations than practitioners (72 versus 103; p = 0.001). ChatGPT-4 indications of endoscopy-biopsy, HPV research, ultrasonography, and PET-CT were consistent with the oncological board decisions. The therapeutic propositions of ChatGPT-4 were accurate in 13 cases (65%). Most additional examination and primary treatment propositions were consistent throughout regenerated response process. CONCLUSIONS: ChatGPT-4 may be an adjunctive theoretical tool in oncological board simple decisions.

Chat GPT for the management of obstructive sleep apnea: do we have a polar star?

PURPOSE: This study explores the potential of the Chat-Generative Pre-Trained Transformer (Chat-GPT), a Large Language Model (LLM), in assisting healthcare professionals in the diagnosis of obstructive sleep apnea (OSA). It aims to assess the agreement between Chat-GPT's responses and those of expert otolaryngologists, shedding light on the role of AI-generated content in medical decision-making. METHODS: A prospective, cross-sectional study was conducted, involving 350 otolaryngologists from 25 countries who responded to a specialized OSA survey. Chat-GPT was tasked with providing answers to the same survey questions. Responses were assessed by both super-experts and statistically analyzed for agreement. RESULTS: The study revealed that Chat-GPT and expert responses shared a common answer in over 75% of cases for individual questions. However, the overall consensus was achieved in only four questions. Super-expert assessments showed a moderate agreement level, with Chat-GPT scoring slightly lower than experts. Statistically, Chat-GPT's responses differed significantly from experts' opinions (p = 0.0009). Sub-analysis revealed areas of improvement for Chat-GPT, particularly in questions where super-experts rated its responses lower than expert consensus. CONCLUSIONS: Chat-GPT demonstrates potential as a valuable resource for OSA diagnosis, especially where access to specialists is limited. The study emphasizes the importance of AI-human collaboration, with Chat-GPT serving as a complementary tool rather than a replacement for medical professionals. This research contributes to the discourse in otolaryngology and encourages further exploration of AI-driven healthcare applications. While Chat-GPT exhibits a commendable level of consensus with expert responses, ongoing refinements in AI-based healthcare tools hold significant promise for the future of medicine, addressing the underdiagnosis and undertreatment of OSA and improving patient outcomes.

ChatGPT performance in laryngology and head and neck surgery: a clinical case-series.

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.

Laryngeal verrucous cell carcinoma.

PURPOSE OF REVIEW: To summarize the recent literature on epidemiology, clinical findings, treatment, and survival of laryngeal verrucous cell carcinoma (LVC). RECENT FINDINGS: Epidemiological studies report that LVC accounts for 1-3% of all laryngeal cancers. The incidence is decreasing, while most patients are male individuals and smokers. LVC are commonly detected in early stages because they are more frequently located in the glottic region. Tobacco, alcohol overuse, and, possibly, human papilloma virus are the main contributing factors. Recent studies confirm that surgery is the primary therapeutic approach with better prognosis when compared with other treatment modalities. Surgery alone is associated with 86.8% disease-free and 80.3% overall survival rates, while metastases are anecdotal. SUMMARY: LVC presents different clinical, pathological, and survival outcomes when compared with the classic laryngeal squamous cell carcinoma. Biopsies need often to be repeated before getting the most appropriate diagnosis; this supports the need of large-sample biopsy during the tumor diagnosis and staging. The glottic location of most LVC leads to detection of this lesion in its early stages, with ensuing better survival and outcomes after surgery compared with the classic form of squamous cell carcinoma. Future studies are needed to understand the biology of LVC and its related better prognostic outcomes when compared to other laryngeal malignancies.

The Dubai Definition and Diagnostic Criteria of Laryngopharyngeal Reflux: The IFOS Consensus.

OBJECTIVE: The objective of this work was to gather an international consensus group to propose a global definition and diagnostic approach of laryngopharyngeal reflux (LPR) to guide primary care and specialist physicians in the management of LPR. METHODS: Forty-eight international experts (otolaryngologists, gastroenterologists, surgeons, and physiologists) were included in a modified Delphi process to revise 48 statements about definition, clinical presentation, and diagnostic approaches to LPR. Three voting rounds determined a consensus statement to be acceptable when 80% of experts agreed with a rating of at least 8/10. Votes were anonymous and the analyses of voting rounds were performed by an independent statistician. RESULTS: After the third round, 79.2% of statements (N = 38/48) were approved. LPR was defined as a disease of the upper aerodigestive tract resulting from the direct and/or indirect effects of gastroduodenal content reflux, inducing morphological and/or neurological changes in the upper aerodigestive tract. LPR is associated with recognized non-specific laryngeal and extra-laryngeal symptoms and signs that can be evaluated with validated patient-reported outcome questionnaires and clinical instruments. The hypopharyngeal-esophageal multichannel intraluminal impedance-pH testing can suggest the diagnosis of LPR when there is >1 acid, weakly acid or nonacid hypopharyngeal reflux event in 24 h. CONCLUSION: A global consensus definition for LPR is presented to improve detection and diagnosis of the disease for otolaryngologists, pulmonologists, gastroenterologists, surgeons, and primary care practitioners. The approved statements are offered to improve collaborative research by adopting common and validated diagnostic approaches to LPR. LEVEL OF EVIDENCE: 5 Laryngoscope, 134:1614-1624, 2024.