Abstract：
OBJECTIVE: Critical components of the nasal endoscopic examination have not been definitively established for either the normal examination or for clinical disorders. This study aimed to identify concordance among rhinologists regarding the importance of examination findings for various nasal pathologies.
METHODS: A consortium of 19 expert rhinologists across the United States was asked to rank the importance of findings on nasal endoscopy for 5 different sinonasal symptom presentations.
METHODS: An online questionnaire was distributed in July 2023.
METHODS: The questionnaire utilized JotForm® software and featured 5 cases with a set of 4 identical questions per case, each covering a common indication for nasal endoscopy. Rankings were synthesized into Normalized Attention Scores (NASs) and Weighted Normalized Attention Scores (W-NASs) to represent the perceived importance of each feature, scaled from 0 to 1.
RESULTS: General concordance was found for examination findings on nasal endoscopy within each case. The perceived features of importance differed between cases based on clinical presentation. For instance, in evaluating postnasal drip, the middle meatus was selected as the most important structure to examine (NAS, 0.73), with mucus selected as the most important abnormal finding (W-NAS, 0.66). The primary feature of interest for mucus was whether it was purulent or not (W-NAS, 0.67). Similar analyses were performed for features in each case.
CONCLUSIONS: The implicit framework existing among rhinologists may help standardize examinations and improve diagnostic accuracy, augment the instruction of trainees, and inform the development of artificially intelligent algorithms to enhance clinical decision-making during nasal endoscopy.
METHODS: A consortium of 19 expert rhinologists across the United States was asked to rank the importance of findings on nasal endoscopy for 5 different sinonasal symptom presentations.
METHODS: An online questionnaire was distributed in July 2023.
METHODS: The questionnaire utilized JotForm® software and featured 5 cases with a set of 4 identical questions per case, each covering a common indication for nasal endoscopy. Rankings were synthesized into Normalized Attention Scores (NASs) and Weighted Normalized Attention Scores (W-NASs) to represent the perceived importance of each feature, scaled from 0 to 1.
RESULTS: General concordance was found for examination findings on nasal endoscopy within each case. The perceived features of importance differed between cases based on clinical presentation. For instance, in evaluating postnasal drip, the middle meatus was selected as the most important structure to examine (NAS, 0.73), with mucus selected as the most important abnormal finding (W-NAS, 0.66). The primary feature of interest for mucus was whether it was purulent or not (W-NAS, 0.67). Similar analyses were performed for features in each case.
CONCLUSIONS: The implicit framework existing among rhinologists may help standardize examinations and improve diagnostic accuracy, augment the instruction of trainees, and inform the development of artificially intelligent algorithms to enhance clinical decision-making during nasal endoscopy.
摘要：
目的：对于正常检查或临床疾病，鼻内镜检查的关键组成部分尚未明确确定。这项研究旨在确定鼻学家之间关于检查结果对各种鼻部病变的重要性的一致性。
方法：美国19位专家鼻学家组成的联盟被要求对5种不同的鼻窦症状表现的鼻内镜检查结果的重要性进行排名。
方法：2023年7月发放了一份在线问卷。
方法：问卷使用JotForm®软件，包含5个案例，每个案例有4个相同的问题，每个都涵盖了鼻内窥镜检查的常见适应症。排名被合成为归一化注意力得分（NASs）和加权归一化注意力得分（W-NASs），以代表每个特征的感知重要性。从0扩展到1。
结果：每个病例的鼻内镜检查结果均具有总体一致性。根据临床表现，病例之间的重要性感知特征有所不同。例如,在评估鼻后滴漏时，中鼻道被选为最重要的检查结构(NAS，0.73),粘液被选为最重要的异常发现(W-NAS，0.66)。粘液的主要特征是它是否化脓(W-NAS，0.67)。在每种情况下对特征进行类似的分析。
结论：鼻学家中存在的隐含框架可能有助于标准化检查并提高诊断准确性，加强学员的指导，并告知人工智能算法的发展，以提高鼻内窥镜检查期间的临床决策。
方法：美国19位专家鼻学家组成的联盟被要求对5种不同的鼻窦症状表现的鼻内镜检查结果的重要性进行排名。
方法：2023年7月发放了一份在线问卷。
方法：问卷使用JotForm®软件，包含5个案例，每个案例有4个相同的问题，每个都涵盖了鼻内窥镜检查的常见适应症。排名被合成为归一化注意力得分（NASs）和加权归一化注意力得分（W-NASs），以代表每个特征的感知重要性。从0扩展到1。
结果：每个病例的鼻内镜检查结果均具有总体一致性。根据临床表现，病例之间的重要性感知特征有所不同。例如,在评估鼻后滴漏时，中鼻道被选为最重要的检查结构(NAS，0.73),粘液被选为最重要的异常发现(W-NAS，0.66)。粘液的主要特征是它是否化脓(W-NAS，0.67)。在每种情况下对特征进行类似的分析。
结论：鼻学家中存在的隐含框架可能有助于标准化检查并提高诊断准确性，加强学员的指导，并告知人工智能算法的发展，以提高鼻内窥镜检查期间的临床决策。
