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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: The purpose of this study was to assess how well ChatGPT, an AI-powered chatbot, performed in helping to manage pediatric sialadenitis and identify when sialendoscopy was necessary. METHODS: 49 clinical cases of pediatric sialadenitis were retrospectively reviewed. ChatGPT was given patient data, and it offered differential diagnoses, proposed further tests, and suggested treatments. The decisions made by the treating otolaryngologists were contrasted with the answers provided by ChatGPT. Analysis was done on ChatGPT response consistency and interrater reliability. RESULTS: ChatGPT showed 78.57% accuracy in primary diagnosis, and 17.35% of cases were considered likely. On the other hand, otolaryngologists recommended fewer further examinations than ChatGPT (111 vs. 60, p < 0.001). For additional exams, poor agreement was found between ChatGPT and otolaryngologists. Only 28.57% of cases received a pertinent and essential treatment plan via ChatGPT, indicating that the platform's treatment recommendations were frequently lacking. For treatment ratings, judges' interrater reliability was greatest (Kendall's tau = 0.824, p < 0.001). For the most part, ChatGPT's response constancy was high. CONCLUSIONS: Although ChatGPT has the potential to correctly diagnose pediatric sialadenitis, there are a number of noteworthy limitations with regard to its ability to suggest further testing and treatment regimens. Before widespread clinical use, more research and confirmation are required. To guarantee that chatbots are utilized properly and effectively to supplement human expertise rather than to replace it, a critical viewpoint is required.
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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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Background: Previous studies have assessed the capability of PRAAT for acoustic voice analysis in total laryngectomized (TL) patients, although this software was designed for acoustic analysis of laryngeal voice. Recently, we have witnessed the development of specialized acoustic analysis software, Tracheoesophageal Voice Analysis (TEVA). This study aims to compare the analysis with both programs in TL patients. Methods: Observational analytical study of 34 TL patients where a quantitative acoustic analysis was performed for stable phonation with vowels [a] and [i] as well as spectrographic characterization using the TEVA and PRAAT software. Results: The Voice Handicap Index (VHI-10) showed a mean score of 11.29 ± 11.16 points, categorized as a moderate handicap. TEVA analysis found lower values in the fundamental frequency vs. PRAAT (p < 0.05). A significant increase in shimmer values was observed with TEVA (>20%). No significant differences were found between spectrographic analysis with TEVA and PRAAT. Conclusions: Tracheoesophageal speech is an alaryngeal voice, characterized by a higher degree of irregularity and noise compared to laryngeal speech. Consequently, it necessitates a more tailored approach using objective assessment tools adapted to these distinct features, like TEVA, that are designed specifically for TL patients. This study provides statistical evidence supporting its reliability and suitability for the evaluation and tracking of tracheoesophageal speakers.
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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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INTRODUCTION: Juvenile recurrent parotitis is a rare disease characterized by repeated episodes of inflammation affecting, unilaterally or bilaterally, the parotid glands during childhood. MATERIAL AND METHODS: Retrospective study including patients diagnosed with juvenile recurrent parotitis between January 2010 and September 2020 at a tertiary level hospital, with the aim of evaluating the results of medical treatment and sialendoscopy. RESULTS: A total of 48 patients met the inclusion criteria and had a mean follow-up of 4 years (SDâ¯=â¯3; Min: 2/Max: 12). Regarding treatment, 34 (70.8%) patients received conservative treatment and had a mean of 5 episodes (SDâ¯=â¯3; Min: 2/Max: 13) until symptom resolution. Meanwhile, 14 (29.2%) patients underwent sialendoscopy, of which two (12%) required reintervention. In 100% (14) of the patients treated with sialendoscopy, the findings were consistent with JRP and, after sialendoscopy, a statistically significant reduction in episodes was observed, with a mean of 1 post-intervention episode (SDâ¯=â¯1.5; Min:0/Max: 6) (Pâ¯<â¯.001). CONCLUSIONS: The results obtained in this study suggest that sialendoscopy is a useful tool in the treatment of juvenile recurrent parotitis. However, new studies comparing the results of sialendoscopy with other therapeutic alternatives are necessary.
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Stereotactic body radiotherapy (SBRT) is characterized by a high dose per fraction, well-defined small targets, superior dose conformity, and a steep off-target dose gradient. A literature search was conducted to examine the experience with SBRT as a curative treatment for newly diagnosed mucosal carcinoma of the head and neck (MCHN). Four retrospective case series and one prospective phase I clinical trial published between 2012 and 2020 described 124 patients. SBRT was mainly performed in older patients with different tumor sites. The median size of the planning target volumes ranged from 5.3 to 41 cm3. Different approaches were used to create margins. In two studies, limited elective nodal irradiation was performed. The equivalent doses used were 60-83.33 Gy delivered in five fractions. Considerable heterogeneity was observed in the radiation dose specification. The incidence of grade ≥3 late toxicity was 0-8.3%, with local and regional control ranging from 73% to 100%. Improved or stable quality of life after SBRT was reported in two studies. Curative-intent SBRT for de novo MCHN appears to be an effective and relatively safe treatment for small tumor targets, preferably without concomitant elective tissue irradiation. Standardization of SBRT practice and well-designed prospective clinical trials are needed to better define the role of SBRT in this setting.
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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: 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.
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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.
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Otolaringologia , Humanos , Estudos Prospectivos , Masculino , Feminino , Adulto , Otorrinolaringologistas , Pessoa de Meia-Idade , Otorrinolaringopatias/terapia , Otorrinolaringopatias/diagnóstico , Diagnóstico DiferencialRESUMO
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.
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Biomarcadores Tumorais , Neoplasias dos Seios Paranasais , Humanos , Neoplasias dos Seios Paranasais/patologia , Neoplasias dos Seios Paranasais/genética , Neoplasias dos Seios Paranasais/classificação , Neoplasias dos Seios Paranasais/diagnóstico , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/análise , Organização Mundial da SaúdeRESUMO
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.
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Refluxo Laringofaríngeo , Voz , Humanos , Refluxo Laringofaríngeo/diagnóstico , Refluxo Laringofaríngeo/tratamento farmacológico , Projetos Piloto , Inibidores da Bomba de Prótons/uso terapêutico , Qualidade da VozRESUMO
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.
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Asma , Produtos Biológicos , Pólipos Nasais , Rinite , Sinusite , Humanos , Interleucina-5 , Rinite/complicações , Rinite/tratamento farmacológico , Inteligência Artificial , Qualidade de Vida , Asma/epidemiologia , Pólipos Nasais/complicações , Pólipos Nasais/tratamento farmacológico , Pólipos Nasais/epidemiologia , Doença Crônica , Sinusite/complicações , Sinusite/tratamento farmacológico , Sinusite/epidemiologia , Produtos Biológicos/uso terapêutico , Terapia BiológicaRESUMO
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.