AimThis study aimed to assess the quality and reliability of the information in YouTube videos regarding pilonidal sinus disease (PSD).MethodsA total of 100 most-viewed videos on PSD were included in the analysis by two general surgeons. Video duration and content, date of upload, qualification of the video uploaders, and number of daily and total view, like, and comment counts were analyzed. We grouped the videos as those uploaded by healthcare professionals and non-professionals. The quality of the video contents was assessed with the Global Quality Scale (GQS) and the reliability of the video content with the DISCERN scoring system.ResultsEighty-five (85%) videos were uploaded by professionals and 15 (15%) videos by laypersons. The average DISCERN score of the reviewed video contents was 3.18 ± 1.23, and the average GQS score was 3.39 ± 1.24. In the overall subjective evaluation, the mean DISCERN value was found as 4.01 ± 1.24 and the mean GQS value as 4.25 ± 1.25 in the useful videos. The mean DISCERN value was found as 2.32 ± 1.22 and the mean GQS value as 2.48 ± 1.25 in the misleading videos.ConclusionOur results showed that most of the YouTube videos on PSD were loaded by healthcare professionals. However, the mean quality and reliability scores were lower in videos uploaded by laypersons. Given the prevalence of PSD, physicians should be promoted for uploading accurate and professional video contents to direct patients to the right solutions for their problems. Pilonidal sinus disease (PSD) is an acquired, benign disease of the natal cleft. PSD usually affects young males aged 15-30 years with a reported incidence of 6/100,000 and a prevalence of 8.3% .Pain, local sepsis, and discharge caused by PSD have a significant negative impact on patients’ quality of life, although it can be easily treated with minimally invasive surgery. Many patients with PSD hesitate to seek medical help for the disease because it is located in a private region of the body. Therefore, patients with PSD may often search for a remedy before seeing a doctor. In fact, increasingly more people seek a solution for their health-related problems on the Internet rather than presenting to a healthcare center.https://backlinko.com/youtube-users).Today, 80% of Internet users search for medical information using online platforms on the Internet . ParticuGiven that digital health literacy is increasing day by day, YouTube can provide an opportunity to offer the public health-related information and direct people with health problems to accurate medical sources. A recent study showed that hashtags of some specific diseases on Twitter, another social media platform, often referenced YouTube, highlighting that online traffic is largely driven to YouTube . HoweverSearch strategy on YouTubeThis study was conducted by two experienced general surgeons as a reliability and quality analysis of information on YouTube videos concerning pilonidal sinus disease at 07-09/10/2022. The search terms were decided by the consensus of the researchers as “pilonidal sinus,” “pilonidal sinus disease,” “pilonidal cysts,” and “ingrown hair” based on the most common trends on Google search engine. From filtering options of the YouTube platform, the video contents were sorted by relevance option. It has been reported in previous studies that 90% of YouTube users view the first results ,16. AccoData retrievalThe data used in this study included video content, video duration, qualification of the uploaders, time of upload, the number of daily views, and the total view, like, and comment counts. Since YouTube removed the number of dislikes, this was not included in the analysis. We further grouped the videos as the videos uploaded by healthcare professionals and those uploaded by non-professionals. Accordingly, the videos that had been directly uploaded by hospital channels and health channels were considered uploaded by professionals because the narrators of these videos were physicians. The other uploaders were considered non-healthcare professionals. The contents of the videos reviewed included general information about PSD, surgical technique, alternative medicine, patient experience, narration, and differential diagnosis. Narrative videos included a narrator (mostly doctors) without displaying any procedure or other images.Evaluation of the videosAfter separate scoring of the videos, subjective assessment was made by the consensus of the two researchers, and all videos were classified as useful and misleading, independently from the scores given. The quality of the video contents was assessed with the Global Quality Scale (GQS) and the reliability of the video content with the DISCERN scoring system. These two online content assessment scales have been commonly utilized in numerous studies investigating YouTube videos on different diseases -13. The DISCERN scaleDISCERN is a scoring scale for evaluating the reliability of consumers’ health-related information on treatment options. In the present study, we used the shortened version of the DISCERN tool adapted by Singh et al. from the original form . The modGQSGQS is a tool developed by Bernard et al. in order to evaluate the quality of a video content based on the utility of the healthcare information offered in the video . GQS conStatistical analysisThe results obtained in this study were analyzed using Statistical Package for Social Sciences (SPSS) version 24.0  software package. The distribution of the data was evaluated using the Kolmogorov-Smirnov test. Since the variables were non-normally distributed, the Mann-Whitney U test was used in the comparison of the continuous variables, and the chi-square test was used in the comparison of the categorical variables between the groups. The Kruskal-Wallis test was used in the comparison of the DISCERN and GQS scores based on the video sources. Continuous variables were given as mean ± standard deviation, while categorical variables were expressed as frequency and percentage (n and %). The calculation of the agreement between the two observers was made using Cronbach’s alpha coefficients. A p < 0.05 was considered statistically significant.In this study, we evaluated a total of 100 YouTube videos on PSD in terms of the reliability and quality of the information they offer. The total view count of these 100 videos was approximately 40 million with about a 10-hour duration. Video content analysis revealed that 63 (63%) videos included surgical technique, 14 (14%) videos included patient experience, 10 (10%) videos included general information about PSD, 10 (10%) videos included only narration without displaying images, two (2%) videos included alternative medicine for the treatment of PSD, and one (1%) video contained differential diagnosis  videos, while patients and laypersons uploaded 15 (15%) videos, hospital channels uploaded 14 (14%) videos, and health channels uploaded 14 (14%) videos. We further divided all videos in two groups as the videos uploaded by healthcare professionals and laypersons. Accordingly, 85 (85%) videos were uploaded by professionals and 15 (15%) videos by laypersons.The average length of the videos was found as 5.63 ± 4.86 minutes. The mean video duration was measured as 5.64 ± 4.86 minutes in the videos uploaded by the professionals and 5.59 ± 4.31 minutes in those uploaded by laypersons. There was no statistically significant difference in video duration between the two groups (p > 0.05). The oldest video was uploaded on 30/12/2007 and the last newest video on 30/10/2021. The mean duration since the upload was found as 1,554.23 ± 1,080.74 days. The average daily views and comment and like counts of the videos are presented in Table The 100 videos enrolled in this study were subjected to an overall evaluation following the scoring process by the two researchers. In the case of disagreement, the view of a third general surgeon was requested, and the decision was made on the consensus of the three surgeons. Accordingly, 49 (49%) videos were evaluated as misleading and 51 (51%) as useful regardless of the uploaders.The quality of the video contents was assessed with the Global Quality Scale and the reliability of the video content with the DISCERN scoring system. The average DISCERN score of the videos was found as 3.18 ± 1.23, and the average GQS score as 3.39 ± 1.24. In the overall subjective evaluation, the mean DISCERN value was found as 4.01 ± 1.24 and the mean GQS value as 4.25 ± 1.25 in the useful videos. The mean DISCERN value was found as 2.32 ± 1.22 and the mean GQS value as 2.48 ± 1.25 in the misleading videos. Table According to the DISCERN results, 41 (41%) videos were of poor quality, nine (9%) were of medium quality, and 50 (50%) were of good quality. Based on the GQS results, eight (8%) videos were of very poor quality, and 20 (20%) videos were excellent. Cronbach’s alpha coefficient was used to evaluate the agreement between the two raters. As a result, there was an excellent agreement between the two surgeons in terms of the GQS and DISCERN scores Table .The DISCERN and GQS scores given by the two researchers are shown in Figures Today, patients and their relatives are increasingly using the Internet  as a source of information to seek help for their health problems, to share experiences, and even to buy treatment . In a suIn this study, we assessed the reliability and quality of the 100 most-viewed YouTube video contents regarding pilonidal sinus disease. The 100 most-viewed video contents were evaluated by two experienced general surgeons independently. The total view count of the videos was about 40 million with approximately 10-hour duration, suggesting a public interest on the issue. The most-viewed video was uploaded by an Indian doctor. The video (four minutes and 56 seconds) was viewed 10,569,264 times with 11,000 likes.In this study, the video contents were uploaded by doctors, hospital channels, health channels, patients, and laypersons. However, because the narrators of the videos were again doctors, in those uploaded by hospital and health channels, we divided the uploaders into two wider groups as professionals and laypersons. Accordingly, in our study, 85% of the video contents were uploaded by healthcare professionals and 15% by non-professionals. In a study from Spain investigating YouTube as a source of influenza vaccine information, Hernández-García and Giménez-Júlvez reported that only 23% of the video contents were uploaded by health professionals . DiffereIn our study, the majority (63%) of videos contained information about surgical technique. We think the reason for this is that surgery is the only definitive solution in PSD. Other studies have reported different rates about the video content. In a study evaluating YouTube videos pertaining to rotator cuff tears, Kuru et al. reported that 14% of video contents were about surgical methods. Again, these rates differ among the studies according to the topic of search .We intend to analyze our DISCERN and GQS scores between professionals and laypersons and to compare our results with the most recent studies in the literature. In the present study, the mean DISCERN score was 3.47 ± 1.23 for the videos uploaded by healthcare professionals and 1.53 ± 1.34 for the videos uploaded by laypersons. The mean GQS score was calculated as 3.70 ± 1.24 for the videos uploaded by healthcare professionals and 1.60 ± 1.38 for the videos uploaded by laypersons. When we analyzed the high difference between the professional and layperson videos, we found out some striking points. In almost all videos uploaded by patients or laypersons, alternative but not scientific methods were mentioned for the treatment of PSD. Even in some videos, there were only images with music in the background without any explanation. People in these videos were discouraging PSD patients from seeking medical help for their problem.Similar results have been reported in the most recent studies. In a study of YouTube videos on contact dermatitis, the mean GQS score was reported as 4.5% in the video contents uploaded by medical sources and 2% in those uploaded by non-medical sources . Chang aStudy limitationsFirst, the focus was only on English-language videos. Video contents in other languages might change the results. Second, the video evaluation was a subjective process, but the inter-observer agreement was excellent. Finally, further studies could include more observers of varying backgrounds such as patients and different age groups in order to minimize subjective bias in the video scoring process.Our results showed that most of the YouTube videos on PSD were uploaded by healthcare professionals. However, the average quality and reliability scores were low even for some video contents uploaded by physicians. Given the prevalence of PSD worldwide, doctors should be promoted to upload accurate and more professional video contents to direct patients to the right solutions for their problems. Finally, YouTube should improve its privacy and community guidelines to include supervision of healthcare-related videos before they can be published.


This paper introduces a transformer encoding linker network (TELNet) for automatically identifying scene boundaries in videos without prior knowledge of their structure. Videos consist of sequences of semantically related shots or chapters, and recognizing scene boundaries is crucial for various video processing tasks, including video summarization. TELNet utilizes a rolling window to scan through video shots, encoding their features extracted from a fine-tuned 3D CNN model (transformer encoder). By establishing links between video shots based on these encoded features (linker), TELNet efficiently identifies scene boundaries where consecutive shots lack links. TELNet was trained on multiple video scene detection datasets and demonstrated results comparable to other state-of-the-art models in standard settings. Notably, in cross-dataset evaluations, TELNet demonstrated significantly improved results (F-score). Furthermore, TELNet’s computational complexity grows linearly with the number of shots, making it highly efficient in processing long videos. Video scene boundary detection or video chaptering is a fundamental task in video structure analysis that facilitates extracting information from videos and enhances the user experience while browsing videos ,2. It haVideos can be divided into shots, which are uninterrupted sequences of visually similar consecutive frames captured by a single camera. However, when it comes to semantically meaningful storylines, scenes, or chapters that are valuable for information retrieval or video summarization, they often comprise a collection of consecutive video shots that are visually dissimilar. These shots may be recorded from different cameras or various angles, forming a cohesive narrative or thematic unit within the video content .Various researchers have studied shot detection algorithms and established methods for identifying shot boundaries using a variety of features ,6,7. GivIn contrast to shot detection, understanding videos at a higher level and distinguishing video scenes as a combination of semantically related shots poses a significant challenge. This task necessitates the integration of diverse information modalities through feature fusion . TherefoHaving video shots and focusing on visual features, we propose a transformer encoding linker network (TELNet) that learns associations among shot representations, establishes links among correlated shots, and identifies scene boundaries based on the established links without knowing the number of scenes in a video see . The ideTELNet relies on a pre-trained and fine-tuned 3D CNN model for extracting video shot features and a stack of multi-head self-attention networks for learning associations among the extracted shot features—transformer encoder. The linker network establishes links among shots based on the encoded shot features and creates a graph of shots (nodes) and their edges (links). Scene boundaries are declared where no overhead links exist between consecutive shots. Assuming that each scene can be represented by a key-shot which is the shot closest to the mean of shot features within each scene, video graphs are created and used as a label for the linker network. TELNet scans the video shots in batches (within a rolling window) and aggregates results when reaching the end of the video.We proposed a transformer encoding linker network (TELNet) that models video shot correlations and identifies video scene boundaries without prior knowledge of video structure, such as the number of video scenes. TELNet’s results demonstrate an increase of 50% in the F-score in half of the transfer settings while maintaining a performance on par with the other SOTA models in the rest of the evaluation settings.The transformer encoder and linker were trained jointly in contrast to the other SOTA models, which were trained in increments. TELNet was trained using novel generated graphs in which nodes are the shot representations, and edges are the links among key-shot and other shots within a scene.Given that TELNet scans video shots in batches and aggregates the results, the model’s computational complexity grows linearly as the number of shots increases, in contrast to other models whose complexity grows linearly to the square of the number of shots , or the TELNet was trained and evaluated on multiple publicly available datasets and compared to other state-of-the-art models ,13,14,15A video shot is the basic video unit comprising a sequence of visually similar frames taken from a single camera, usually at a fixed angle. Given the similarity of frames within a shot, multiple established shot detection algorithms have been proposed for video processing tasks . Chu et A video shot can be represented either by a set of frames or a single frame, known as the key-frame. The key-frame, as defined by Rui et al., captures the shot’s salient information, making it a representative sample of the entire shot . ConvoluIt has been shown that 3D convolutional neural networks (3D CNNs) can effectively represent transitions in a sequence of consecutive frames ,30. As aRecent studies on shot representation focus on self-supervised representation learning, aiming to enhance network robustness against various variations by modeling representation consistency. Chen et al. introduced a shot encoder incorporating video and audio features . Their aFinding similarities among shot representations can help us identify video scene boundaries . ChasaniPei et al. considered scene boundary detection a graph-linking problem in which a graph convolutional network (GCN) was trained to link shots based on the pivot graph generated using cosine similarity among shots . Trojahn2)  to deter2) . Selecte2) . Baraldi2) . Baraldi2) . Protaso2) . Bouyahi2) . Rotman 2) ,20. HaviThe introduction of the transformer architecture by Vaswani et al. in their seminal paper  revolutiAs shown in The authors utilized an updated version of the C3D model , which wN shots and with each shot represented by d features, X is denoted as the shots feature matrix where X ∈Z is the weighted sum of the concatenated outputs of the attention heads  are linked through weighted edges. The linker estimates the edge weights using two fully connected layers, denoted by the L function. The L function takes F, model parameters F (edge weight).With the encoded shot features TELNet analyzes a fixed number of video shots using a rolling window, and the linker establishes links among video shots within the rolling window. Through the link merging, the established links among overlapping rolling windows are compared and merged; the link with the highest edge weight will be preserved and used for detecting scene boundaries see . An ablaSelecting the key-shot as the closest shot to the mean of the shot features within a scene (refer to Algorithm 1). In contrast to the maximum variance method, which aims to select the most diverse shot within a scene, we have proposed the key-shot selection based on its proximity to the mean of the shot features. The rationale behind our approach is to identify a shot that can effectively represent the storyline of the scene, encapsulating the most common visual content. By choosing the key-shot as the one closest to the mean, we prioritize shots that align with the overall visual theme of the scene, leading to a more cohesive and representative graph. While the maximum variance method may emphasize shots with diverse characteristics, it may include outliers that do not accurately depict the primary content of the scene. In contrast, our proposed method seeks to find a shot that best encapsulates the central theme, ensuring that the key-shot serves as a reliable anchor for connecting other intra-scene shots. This approach enhances the interpretability and coherence of the video graph, enabling more accurate analysis and understanding of the video content.Establishing links among intra-scene shots to the key-shot refer to . This stTELNet generates a video graph in which shots (nodes) are linked based on their relationships, quantified by edge weights. We transform raw shot features into encoded representations through the training process, wherein intra-scene shot features are brought closer together than out-of-scene shot features. In simpler terms, the encoded features capture the semantic relationships among intra-scene shots learned from the ground truth label. Having access to labeled datasets that provide scene boundaries, we have devised the graph label generation procedure, which involves two steps:Algorithm 1 Key-shot selection, graph label generationInput: Raw shot features within a sceneOutput: Y  1:k-th shot in a videoConsider j-th scene containing n shots starting from   2:Mean shot feature   3:∞minDist =   4:fori = k to k + n − 1 do  5:    Dist = EuclideanDistance  dataset, proposed by Rotman et al., comprises 21 movies and animations . HoweverThe Movie SceneClip (MSC) dataset, introduced by Liu et al., consists of 500+ videos . Unlike Video scene boundary detection can be treated as a binary classification task, where the model’s performance can be assessed using average precision. TELNet achieved an average precision of 18.5 on the BBC dataset and 18.1 on the OVSD dataset. However, a limitation arises as precision and recall can only evaluate the model’s ability to precisely identify the exact scene boundaries rather than the representation of each segmentation. Due to this limitation, relying solely on average precision as the evaluation metric for scene boundary detection may lead to underestimating the model’s actual performance. An alternative evaluation metric that addresses this issue is the F-score, calculated as the harmonic mean of coverage, n models :(6)Ct=Zii-th scene. TELNet achieved an F-score of 0.74 on the BBC dataset and 0.72 on the OVSD dataset.The predicted scenes are denoted as To maintain consistency with prior studies, the evaluation was conducted using the leave-one-out training approach. Notably, TELNet demonstrates outstanding performance, surpassing all other models, in several cases by a significant margin. Furthermore, it achieves results on par with ACRNet, which is a more complex model .In the canonical setting, the F-score results on the BBC and OVSD datasets are obtained by averaging the leave-one-out results. For the MSC dataset, the F-score is calculated by splitting the dataset into 70% for training and 30% for testing.On the other hand, in the transfer setting, the F-score is calculated using a full dataset for training and a different dataset for testing. In this scenario, TELNet exhibits superior performance over ACRNet, indicating the effectiveness of the proposed encoder–linker in learning the essential video structure for scene boundary detection, independent of the specific video subjects.These findings suggest that TELNet’s architecture enables it to generalize well across different datasets, making it a robust and versatile model for video scene boundary detection tasks. The results highlight the advantages of TELNet over ACRNet, particularly in scenarios where a model’s ability to adapt to new video content is crucial.As videos become longer and contain more shots, the computational demands of scene boundary detection algorithms can escalate significantly. Therefore, it is essential to analyze and compare different models’ time and space complexities to ensure their feasibility and efficiency for real-world use.The optical scene graph (OSG) algorithm, as described in the work of Rotman et al. ,20, has ACRNet, proposed by Liu et al. , utilizeWs. For a video with N shots, TELNet’s time complexity is TELNet adopts a different approach. It establishes links among shots by calculating pairwise linking probabilities using a rolling window size of The x-axis represents the shot indexes, the vertical orange dashed lines indicate the ground truth scene boundaries in the video, and the red vertical solid lines, on the other hand, represent the predicted scene boundaries generated by the TELNet model. The colored horizontal lines illustrate the links between shots (see the zoomed section of the plot).If there are no horizontal lines with the same color crossing two adjacent shots, it implies the presence of a scene boundary. For instance, the absence of a light blue horizontal line crossing shot no. 149 indicates that shot no. 149 is a scene boundary.This study aimed to design a simple video scene detection network that could be trained end-to-end and that relies solely on shot representations with no need for any information about video scenes, such as the number of scenes in a video.We have proposed a model integrating a transformer encoder and a linker to identify video scene boundaries. The proposed model was trained and evaluated on multiple datasets using a novel key-shots selection technique and corresponding video graph labels. The proposed model scans shot representations extracted from the pre-trained 3D CNN model in a sequence using a rolling window methodology, encodes representations using a transformer encoder, and generates an aggregated video link graph using a linker.TELNet achieved F-score results comparable to the other state-of-the-art models in the canonical setting and outperformed results in the transfer settings without prior knowledge of the video structure, such as the number of scenes in a video. State-of-the-art results in the transfer setting confirm that combining the selected shot representations and the transformer encoder can effectively learn the video structure of a wide range of subjects.An equally crucial aspect of TELNet is its linear growth in computational complexity as the number of shots increases. This makes TELNet the simplest and most suitable among the state-of-the-art models for handling long videos and ideal for real-time streaming applications.In conclusion, our study successfully introduces TELNet as an efficient and effective solution for video scene boundary detection. Its capacity to learn without prior knowledge of scene numbers and its scalability for handling longer videos highlights its applicability in various scenarios. By presenting a simple yet robust end-to-end trainable model, we aspire to pave the way for further advancements in video scene analysis.Future directions may involve the fusion of visual, textural, and audio features to achieve context-aware segmentation. These multimodal features can enhance the model’s understanding of video content, leading to more accurate and meaningful scene boundary predictions. One promising approach is constructing a video context graph that combines visual, textural, and audio information, enabling downstream tasks such as segment scoring and video summarization. This graph-based representation facilitates ranking and scoring segments based on their relevance and importance in the overall narrative, thereby capturing the essence of video content more effectively.


We used parent report data to investigate video game playing, aggression, and social impairment in adolescents with autism spectrum disorder. Parents of autistic adolescents were more likely to report that their child plays video games as a hobby compared to parents of adolescents with typical development and also reported that their children spent more time playing video games. For autistic participants, we found no differences in aggression levels or social impairment when comparing players versus non-players. However, playing video games “more than average,” as compared to “average” was associated with greater aggression and greater social impairment on “awareness” and “mannerisms” subscales. Future studies should focus on how type of video game(s) played is associated with these clinically important variables.The online version contains supplementary material available at 10.1007/s10803-022-05649-1. In the twenty-first century, and especially in the United States (US), video games are ubiquitous. There are nearly 227 million total video game players in the US, with 51% playing over 7 h per week  and aggression and violence. An early study  spend a large amount of time playing video games  and video game playing amount in adolescent participants with ASD and a non-autistic control group (TD) matched on FSIQ and sex. We also investigated video game playing status and amount in our ASD and TD groups while accounting for sex. Second, we examined the association between video game play and aggression within individuals with ASD. Finally, we investigated the association between video game playing and social impairment in adolescents with ASD. Based on previous research, we expected our cohort of autistic participants to spend more time playing video games than their TD peers. We anticipated that aggression would not be elevated in adolescents with ASD who are avid video game players due to recent research showing that aggression is not associated with video game playing in TD. Lastly, in light of research suggesting that video games can have a positive social benefit in those without ASD  study or the Autism Phenome Project (APP) study conducted at the University of California (UC) Davis MIND Institute. Both studies had protocols that included the same assessments for hobbies, aggressive symptoms, and social functioning (see below for a detailed description of measures). To qualify for either study, autistic participants had to have a clinical best estimate diagnosis of autism which included presenting with a community diagnosis of ASD, and meeting criteria for autism on the Autism Diagnostic Observation Schedule—Second Edition  Checklist  for ASD. The Social Communication Questionnaire—Lifetime Edition  and were based on the National Institutes of Health Collaborative Programs of Excellence in Autism diagnostic standards. They were then reassessed approximately one year after T1 (T2), two years after T2 (T3), and at ages 9–12 (T4). The current analyses use data from T4. Autistic participants were re-assessed with the ADOS-2 and SCQ  to identify a 1:1 matched sample. The algorithm allowed us to set a maximum difference on FSIQ (7 points) and require an exact match on sex and study when selecting a match. The final sample included 76 ASD-TD matched pairs. Participant characteristics are provided in Table A total of 151 ASD  and 114  TD participants met inclusion criteria. Two additional participants (ASD) were removed because their data was collected during the COVID-19 pandemic, which could affect video gaming habits. Data from all remaining participants was collected prior to the onset of the COVID-19 pandemic. These participants were submitted to an automated greedy matching algorithm (n = 36) had an FSIQ < 70, and FSIQ could not be computed for an additional two participants; one due to a lack of comprehension during the IQ assessment, and another due to behavioral difficulties during the testing session. Children with intellectual disability, which is diagnosed when there are deficits in intellectual functioning (FSIQ < 70) and adaptive behavior , play video games less compared to ASD and TD children without intellectual disability  were removed from the sample after case matching. Half of the removed TD participants had an FSIQ above 120, while the majority of the ASD participants removed had FSIQs below 90. About half of the ASD participants removed , or select none, based on an open-ended question as a prompt . Participants were divided into “Player” and “Non-player” groups based on the written responses to the “hobbies” prompt. Our accepted responses that indicate video game players include simple phrases such as “video games” and “computer games,” or more specific indicators such as “Xbox” or “Fortnite.” More general responses such as “computer” or “iPad” were also accepted. However, if further details provided indicated that video games were not being played on the electronic device (such as “watching movies on the iPad”) then the participant was categorized as a “Non-player.” To evaluate whether including the players with more general responses had an impact on our findings, we conducted a sensitivity analysis by rerunning the matching algorithm and the main analyses after removing those participants.Less Than Average, Average, More Than Average, and Don’t Know. From these data we created four video game playing categories that reflect the amount of time spent playing video games: Video game not listed as a hobby (“don’t play”), play video games less than average (“less than average”), play video games an average amount of time (“average”), and play video games more than an average amount of time (“more than average”). Due to the limited information gained from the “don’t know” category, individuals whose parents made this response  were excluded from analyses that investigated amount of video game playing, although they were included in analyses investigating players versus non-players.Once a hobby is written in, there are four options to select from to answer the question: “Compared to others of the same age, about how much time does he/she spend in each?” The options are M = 50, SD = 10): Social Awareness, Social Cognition, Social Communication, Social Motivation, and Restricted Interests and Repetitive Behavior . Elevated T-Scores (T-Scores ≥ 60) indicate more clinically significant social difficulties  within the chosen domain. Out of 69 autistic participants with SRS-2 Total T-scores available (from our case matched sample), 55 had clinically significant social impairment (80%). Social impairment within the TD group was not analyzed due to the lack of the presence of this core symptom of ASD in most TD youth. Table Social functioning was assessed using the Social Responsiveness Scale—Second Edition  were employed to test differences in these scores. Analyses of aggression and social impairment scores across playing status and amount of playing categories were restricted to ASD participants, given the limited range of these variables in TD. For each aggression and social impairment outcome, significant overall differences among amount of playing categories were followed up with the Dwass, Steel, Critchlow-Fligner post-hoc procedure, which corrects for multiple comparisons, to determine which pairs of playing categories differed. All analyses were implemented using SAS Version 9.4 . All tests were two-sided, and 2  = 6.80, p = 0.009], with parents of the autistic adolescents reporting video games as a hobby more frequently than those of TD adolescents. Similarly, significant diagnostic group (ASD/TD) differences in the amount of playing  were found   between diagnostic groups  and amount of playing  . Percentages for video game playing category, broken down by diagnostic group and sex, are shown in Supplemental Fig. To control for the potential difference in video game playing behavior between females and males, we redid our main analyses adjusting for sex. The results of the adjusted analyses confirmed the main results. After adjusting for sex, we found significant differences between ASD and TD in playing status (Player/Non-Player) . Parents of autistic individuals with FSIQ < 70 reported video games as a hobby less frequently than the parents of ASD participants with FSIQ of 70 or greater. There were also significant differences between the groups based on amount of playing ,   and video game playing status group (Player/Non-player)  (Table M = 59.0) and “average” group (M = 53.3) . No other comparisons were significant  = 7.87, p = 0.05], as were the SRS-2 Awareness  and Mannerisms  subscales (Table M = 73.7) and “play average” group (M = 62.8)   and “play average” group (M = 64.5)   and “average” (M = 65.2) had a trend-level p-value   and amount of time spent playing video games  in adolescents with ASD and TD, and also examined the association between video game playing and aggression and social impairment in adolescents with ASD. Parents of autistic participants reported their children as having video games as a hobby more often than parents of TD children. The analysis looking at amount of time spent playing video games also showed that ASD and TD differed significantly, with autistic adolescents more often falling into the “play more than average” category compared to TD Fig. . Both ofn = 16 per group) interpretation of our data on video game playing in girls is limited. However, it was surprising to see that ASD vs. TD differences in video game playing status appeared to be even more pronounced in girls than boys . This was driven by our finding that a large portion of our TD girls (75%) were not classified as video game players, which differs from recent reports showing that video game playing, while lower in girls than boys, is still highly prevalent in girls  subscale examines to what extent restricted, repetitive behaviors and interests are present. Video games often become a restricted interest in adolescents with ASD, as playing these games can morph from a leisurely hobby to an intense preoccupation. Thus, these findings agree with previous research showing that core symptoms of ASD, namely that the tendency to develop intense interests or encompassing preoccupations, plays a role in the extent of video game playing . However, when considering all four video game playing categories, the means for “play more than average” are not particularly high, but rather the means for “play average” appear low Fig. ; Table 4It is important to note that our sample includes autistic children who also may have Attention Deficit Hyperactivity Disorder (ADHD), thus the relationship between ADHD, video game play, aggression, and social functioning should also be considered in light of our results. While some studies show that children with ADHD do not play video games more or less in comparison to either TD or autistic children  was an exclusion. This created a group of participants where baseline levels of certain comorbid conditions  were less prevalent than would be expected in a population type sample. Should levels of these conditions in our sample have matched a population type sample, there may have been further/larger group differences, specifically when looking at aggression. Lastly, it is important to note that this study used an FSIQ-matched sample. While this eliminated the confounding effects of IQ differences, it also means conclusions from our main analyses cannot be extended across the entire range of autistic individuals. Supplemental analyses showed that parents of autistic adolescents with lower (< 70) FSIQ were less likely to report video games as a hobby in comparison to parents of autistic adolescents with higher IQs . If they did play video games, adolescents with lower IQs typically played on a tablet or phone as opposed to traditional video games played using a gaming console.In the future, further research using dedicated video game questionnaires is highly recommended. These questionnaires allow collection of in-depth information about when (weekday vs. weekend) and how often  games are being played. Secondly, these questionnaires also help in regard to determining what genres of games are being played, and with that information, more detailed conclusions about associations with aggression and social functioning can be made. Fortunately, a few popular video game questionnaires exist such as the Problem Video Game Playing Test , future research is needed to focus more on possible benefits of video gaming in ASD. What qualifies as a video game is largely open ended, and many games have a significant social component built into them . With the advent of the Internet and more sophisticated platforms to play video games that incorporate text or voice chat, it has never been easier to log on and play with others. One may assume that a child who is engaged in more communicative based video games is actively engaging in social skills through periods of increased communication with other peers in order to play the game, thus relationships between video game playing and social functioning may be highly dependent upon the type of game being played.2021 Essential Facts About the Video Game Industry, During the COVID-19 pandemic, video games have become a key outlet to avoid social isolation during long-haul stretches of lockdowns and quarantines. In a 2020 survey conducted by Google, 35% of American respondents said their decision to spend more time playing video games now than before the pandemic was to connect with friends and family Below is the link to the electronic supplementary material.


In 2021, 131 million adult Americans reported drinking alcohol in the last month, despite the well-known consequences of alcohol consumption. While alcohol use disorders (AUDs) are associated with both mood and chronic pain disorders, the relationship between alcohol drinking and affective and nociceptive behaviors remains unclear. Corticotropin releasing factor receptor-1 (CRF1) has been implicated in alcohol drinking, affective states, and pain sensitivity, often in a sex-dependent manner. In order to probe the effects of alcohol drinking on activity of CRF1+ cells and to also test the hypothesis that alcohol drinking is associated with both basal and subsequent affective and nociceptive readouts, we put male and female CRF1:cre:tdTomato rats through a battery of behavioral tests before and after intermittent access to alcohol. Following baseline testing, rats began alcohol (or water) drinking. Females consumed more alcohol in the first week, but there was no effect of sex on overall alcohol intake. Following three to four weeks of drinking, behavioral tests were repeated. Alcohol drinking decreased mechanical sensitivity, but no other effects of alcohol drinking were observed between experimental groups. Individual alcohol intake correlated with affective behavior in both sexes but only correlated with thermal sensitivity in males. There were no main effects of alcohol drinking or sex on CRF1+ neuronal activity in the medial prefrontal cortex (PFC) but final session alcohol intake correlated with activity in CRF1+ neurons in the infralimbic (IL) subregion. Together, our results suggest complex interplay between affective state, alcohol drinking, and the role of prefrontal CRF1+ neurons in mediating these behaviors. Despite alcohol use being extremely comorbid with mood and pain disorders, there is still a limited understanding of the interaction and directionality between the them. To investigate this problem, rats were tested for affective behavior before and after being allowed to drink alcohol for six weeks. While baseline behavior did not predict subsequent intake, alcohol intake predicted subsequent affective behavior on an individual subject basis. These findings were accompanied by increased activity of the corticotropin releasing factor receptor-1 (CRF1) containing neurons in the infralimbic (IL) region of the prefrontal cortex (PFC). Together, these findings reveal a new mechanism for understanding alcohol use.In 2021, 131 million adult Americans reported drinking alcohol (EtOH) in the last month, with almost 30 million adult Americans meeting the criteria for an alcohol use disorder AUD; . While AAffective behavior and EtOH use not only overlap in incidence, but also share similar neurobiological underpinnings. More specifically, both involve the stress-related corticotropin releasing factor (CRF) system. While hypothalamic release of CRF results in activation of the hypothalamic-pituitary-adrenal axis, extrahypothalamic CRF acts as an important neuromodulator in the brain through activity at two G-protein-coupled receptors, CRF1 and CRF2. In humans, polymorphisms in the gene encoding CRF1 are associated binge drinking, EtOH intake, and intoxication as well as with AUDs . PolymorIn rodents, systemically administered CRF1 antagonists decrease negative affect, EtOH intake, EtOH-induced negative affect and EtOH-induced hyperalgesia . CRF1 isThe present study uses behavioral testing and voluntary EtOH drinking in a CRF1 transgenic rat line to investigate the interaction between EtOH drinking and affective behavior in male and female rats. This study also examines the impact of chronic EtOH drinking on activity in the prefrontal cortex overall and specific to the CRF1 population. We specifically tested the hypothesis that basal affective and nociceptive behavior would predict subsequent drinking and that increased EtOH intake would further drive affective and nociceptive readouts. A period of three to four weeks of drinking was chosen as other papers found this time was sufficient to induce affective and nociceptive behaviors in both rats  and micen = 16/sex) CRF1:cre:tdTomato rats  on the dorsal coat of the torso, placed into a Plexiglas/textured flooring behavioral testing chamber [50 cm (length) × 50 cm (width) × 38 cm (height)] and recorded for 10 min in red light conditions. Latency to groom and total time spent grooming were scored by an experimenter blind to experimental group using the Behavioral Observation Research Interactive Software (BORIS) program . LatencyRats were brought into behavioral testing room 1 h before testing and were habituated for 15 min to a stainless-steel table (78 × 32 × 19.5 cm) with a perforated sheet containing staggered holes (0.28 cm diameter). Plastic filaments of increasing force (Bioseb EB2-VFF) were applied perpendicularly to hind paws until bending, and nocifensive responses defined as shaking, licking, or withdrawing the paw were recorded. Each paw was prodded three times/filament, beginning with the 2-g filament and increasing until the rat exhibited a nocifensive response during at least two trials. Withdrawal thresholds for each hind paw were then averaged for each animal to determine the paw withdrawal threshold.Rats were given 1 Froot Loop in the home-cage 48 h before testing to prevent neophobia. Twenty-four hours before testing, the food was removed from the cage. On test day, rats were habituated to behavioral testing room for 1 h before testing. During testing, rats were individually placed into a brightly lit (150 lux) behavioral testing chamber (50 × 76 × 40 cm) containing one Froot Loop on filter paper in the center. Latency to eat was recorded and used as a measure of affective behavior . After fRats were assessed for thermal sensitivity using the Plantar Analgesia Meter (IITC). Rats were brought into the testing room 1 h before testing and habituated to the heated glass (temperature: 32°C) apparatus for 20 min. Infrared light  was focused onto each hindpaw and withdrawal latency was recorded. A maximum cutoff of 20 s was used to prevent tissue damage. Each hindpaw was tested twice. If the latencies differed by more than 1 s, then the paw was tested one additional time. Withdrawal latencies were averaged per paw then per animal.After 4 d of acclimatization to drinking out of two water bottles, one bottle containing 20% EtOH and one bottle of water were placed on cages for 24 h. This occurred on alternating days (MWF) and bottles were introduced or removed at 10 A.M., 3 h after onset of the light cycle [zeitgeber time (ZT) 3]. Water drinking rats had their water bottles changed every 24 h (at the same time) to ensure comparable treatment. Bottle placement was alternated to eliminate side preference; 20% v/v EtOH was prepared by diluting 95% EtOH (Pharmco Products Inc) in tap water.Behavioral testing began 24 h after EtOH bottles were removed and lasted 2–3 h. IA2BC resumed the following day. The order of testing was randomized at baseline. During postconsumption testing, pain tests occurred before affective testing to prolong the time between re-exposure to anxiogenic contexts. Finally, the NSF test was performed last as food deprivation is a known stressor  and coulTwenty-four hours after the last alcohol presentation, rats were anesthetized with isoflurane and transcardially perfused using PBS followed by 4% paraformaldehyde. Brains were postfixed in 4% PFA at 4°C overnight and then transferred to 30% sucrose in PBS at 4°C until brains sank. Brains were serially sectioned at 40 μm and stored in cryoprotectant  at 4°C.For each animal, four to six sections containing the medial prefrontal cortex , Welch’s t test , or a Mann–Whitney U test (nonparametric data). For cumulative incidence graphs, Kaplan–Meier survival curves were generated and were followed by Mantel–Cox log-rank test (followed by Bonferroni when applicable). Fluid intake and preference were analyzed by a mixed model two-way ANOVA, using session as a within-subjects factor and sex as a between-subjects factor. Cumulative intake data were analyzed using an unpaired Student’s t test  or an unpaired Welch’s t test . When behavioral tests were repeated (following drinking), data were analyzed using a three-way mixed ANOVA . When applicable, Bonferroni’s correction was used for multiple comparisons. Correlational analyses were performed using Pearson’s correlation (parametric data) or Spearman’s correlation (nonparametric data). To compare correlations between males and females, Fisher’s r to z transformation was used:Baseline behavioral tests were analyzed using an unpaired Student’s r from males and females  was used to compute an observed z value, zobs with the following calculation:m) or females (Nf).Zobs.In each set of correlations, the same analysis (Pearson’s or Spearman’s) was used for both sexes to calculate a zImmunofluorescence data were analyzed by a two-way ANOVA using sex and EtOH as between-subjects factors.As shown in 10.1523/ENEURO.0055-23.2023.f1-1Extended Data Figure 1-12 = 1.430, df = 1, p = 0.2318). There was also no sex difference in total time spent grooming . Download Figure 1-1, EPS file.Cumulative incidence of grooming initiation in the splash test. Even when accounting for the rats that never groomed , there was no sex difference in grooming initiation . Download Figure 1-2, EPS file.Cumulative incidence of feeding initiation in the novelty suppressed feeding test. There was no effect of sex on cumulative occurrence of feeding initiation . Interestingly, there was no association between initial EtOH intake and basal thermal withdrawal (B), or basal latency to groom (C) and time spent grooming (D) in the splash test. There was also no significant relationship between initial EtOH intake and latency to eat (E) or post-test consumption (F) in the NSF test. Pearson’s correlations: A, M&F: r(14) = −0.4742, p = 0.0635; Males: r(6) = 0.5673, p = 0.1425; Females: r(6) = −0.2699, p = 0.5179; B, M&F r(14) = 0.1836, p = 0.4962; Males: r(6) = 0.3344, p = 0.4162; Females: r(6) = 0.1388 p = 0.7431; F, M&F: r(14) = 0.1751, p = 0.5167; Males: r(6) = 0.4654, p = 0.2451; Females: r(6) = −0.01082, p = 0.9797. Spearman’s correlations: C, M&F: rs(14) = 0.3991, p = 0.1266; Males: rs(6) = 0.03593, p = 0.9434; Females: rs(6) = 0.4637, p = 0.2619; D, M&F together: rs(14) = −0.2088, p = 0.4355, Males: rs(6) = 0.3234, p = 0.4317; Females: rs(6) = −0.4364, p = 0.3036; E, M&F: rs(14) = 0.1177, p = 0.6631; Males: rs(6) = 0.3571; p = 0.3894; Females: rs(6) = −0.2857, p = 0.5008 Download Figure 2-1, EPS file.Behavioral measures did not correlate with first day EtOH intake in both males (M) and females (F). There was a trend where the rats with lower withdrawal thresholds drank more EtOH  or Hargreaves testing (B) on EtOH consumption. Two-way ANOVAs: A, Sex × Day: F = 0.1799, p = 0.6779; Sex: F = 0.01875, p = 0.8930; Day: F = 1.244, p = 0.2835; B, Sex × Day: F = 0.01586, p = 0.9016; Sex: F = 5.719e005, p = 0.9941; Day: F = 0.2869, p = 0.6006 Download Figure 3-1, EPS file.Pain testing does not affect EtOH intake. There was no effect of Von Frey testing  = 1.958, p = 0.1852; Sex: F = 1.883, p = 0.1932; Day: F = 1.989, p = 0.1819 Download Figure 4-1, EPS file.Splash test testing does not affect EtOH Intake. Two-way ANOVA: Sex × Day: w (x (x. This suggests sex differences in latency to groom occur only in rats with a history of EtOH drinking (and not in EtOH-naive rats).To account for animals that failed to groom during the 10-min test period, the cumulative incidence of grooming was plotted using the Kaplan–Meier survival curve followed by the Mantel–Cox log-rank test. There were no differences in cumulative incidence of grooming during the pre-testw C. Howevew  or post-test . Lastly, there was no effect of testing on EtOH intake  = 0.5462, p = 0.4721; Sex: F = 1.901, p = 0.3442; Day: F = 1.901, p = 0.1896). Download Figure 5-1, EPS file.Cumulative occurrence of behavioral initiation in the NSF is not affected by EtOH drinking, nor is EtOH intake affected by NSF testing. There was no effect of group on cumulative occurrence of feeding initiation in the pre-test  = 0.01105, p = 0.9170; Sex: F = 1.998, p = 0.1685; EtOH: F = 0.002337, p = 0.9618). Body weight change was not associated with latency to eat  = −0.01471, p = 0.9607; Males: rs(6) = −0.2619, p = 0.5364; Females: rs(6) = 0.02381, p = 0.9768) or post-test consumption  = −0.2642, p = 0.3228; Males: r(6) = −0.2771, p = 0.5064; Females: r(6) = −0.2744 p = 0.5107). One important consideration is that body weights were not measured immediately before food deprivation (and instead were taken 1 week prior to the test). However, body weights were taken on the day of the NSF test . Percent body weight was calculated as [100 + 100 × (body weightNSF day – body weight1 week prior)/body weight1 week prior]. Download Figure 5-2, EPS file.Percent change in body weight does not account for effects seen in NSF. There was no difference in body weight changes  and cFos . The medial prefrontal cortex was divided into prelimbic (PL) and infralimbic (IL) cortices, based on the Paxinos and Watson atlas .ai , cFos+ cells (B), total double-labeled cells (C) or double-labeled cells when expressed as %CRF1+ cells (D). Spearman’s correlations: A, M&F: rs(14) = −0.1735, p = 0.5193; Males: rs(6) = −0.5476, p = 0.1710; Females: rs(6) = 0.09524, p = 0.8401. Pearson’s correlations: B, M&F: r(14) = −0.1997, p = 0.4582; Males: r(6) = −0.25643, p = 0.5271; Females: r(6) = −0.3325, p = 0.4210); C, M&F: r(14) = −0.07430, p = 0.7842; Males: r(6) = −0.2966, p = 0.4757; Females: r(6) = −0.02222, p = 0.9583; D, M&F: r(14) = −0.01427, p = 0.9582; Males: r(6) = −0.1604, p = 0.7043; Females: r(6) = −0.09422, p = 0.82. Download Figure 6-1, EPS file.Correlations between EtOH intake and activity in the prelimbic cortex. EtOH intake did not correlate with CRF1+ expression  also found no sex differences in baseline affective behavior in the splash test . Sex difAlthough the behavioral tests used in these studies examine different aspects of affective and nociceptive behavior, one common theme emerged in the postdrinking tests: these behaviors increased in both EtOH drinking animals as well as EtOH-naive animals. Specifically, we found increases in the Von Frey test , splash test , and NSF test . Our study aimed to investigate the directionality of the relationship between negative affect, nociception, and EtOH drinking; therefore, having baseline measures was crucial. However, affective tests are rarely repeated in the same subjects; thus, there are limited findings regarding the effects of time and re-testing on behavior. Our lab previously demonstrated that male rats, but not female rats, spent significantly less time grooming on the second splash test .Additionally, test conditions were not changed between pre-test and post-test. Although this was intentionally designed based on findings that demonstrate three weeks is sufficient to wait between testing , we cannMany studies have reported increased negative affect and nociception following chronic EtOH drinking . HoweverDespite the lack of group effects of EtOH, there were significant individual correlations between behavioral readouts and EtOH intake, thus highlighting the importance of examining individual differences in the context of EtOH-related behaviors. More specifically, this study found previous EtOH intake correlated with thermal sensitivity as well as alterations in affective behavior. There was an inverse relationship between EtOH intake and thermal sensitivity, where males that consumed more EtOH were less sensitive to thermal stimuli and males with increased thermal sensitivity consumed less EtOH on the next day. These findings are in accordance with a previous study reporting that EtOH withdrawal increases nociceptive threshold . HoweverIn addition to associations with thermal sensitivity, previous day EtOH intake was also associated with negative affect in the splash test and NSF test. These associations were specific to the EtOH group as they are lost when water-drinking animals are included in the analysis (data not shown), likely because of the loss of dynamic range when EtOH intake is zero for all subjects. Collectively, these results suggest that while basal negative affect is variable and likely determined by a number of factors, chronic drinking does contribute to EtOH-affective state interactions. These findings are consistent with previous studies that demonstrate increased fear-potentiated startle in various genetic lines of alcohol preferring rats  and miceThe effects of alcohol on affective and nociceptive behaviors are known to be mediated by key brain regions including the medial prefrontal cortex. Many studies fail to differentiate the prelimbic (PL) and infralimbic (IL) subdivisions of this region, but it is clear that these regions often play opposing roles in mediating behavior. For example, dopamine blockade in the PL reduces place conditioning without affecting cue conditioning but dopamine blockade in the IL reduces cue conditioning without affecting place conditioning . While bCrhr1 mRNA levels in the IL of male rats and found that three weeks of self-administration followed by 10d of extinction decreased Crhr1 transcript levels in the IL (PL and IL also exert opposing effects on stress reactivity, especially in the context of EtOH. One important study found that the CRF1 antagonist CP154,526 injected directly into the IL could inhibit stress-induced reinstatement of EtOH seeking, an effect that did not occur if the drug was injected directly into the PL . These sn the IL . This isn the IL . One impn the IL ; howevern the IL , complicn the IL . These aTogether, our results illustrate the complex interplay between affective state, EtOH drinking, and the role of prefrontal cortex CRF1+ neurons in mediating these behaviors. Moreover, these data highlight the importance of examining individual differences in addition to group averages when investigating AUD-related behaviors and affective states. There are currently only four FDA-approved medications to treat AUD, and persistent issues with efficacy and compliance complicate effective treatment. Clinical trials have demonstrated differential efficacies of medications when stratified by factors such as sex, age of AUD onset, severity of AUD, and impulsivity levels . However


The video otoscope has already proven to be useful for the diagnosis of several pathologies, so the objective of this study was to evaluate the diagnostic accuracy of the video otoscope in cases of tympanic membrane perforation.This is a diagnostic accuracy study performed at the hearing health division of a tertiary-level referral hospital. Patients older than 8 years of age who had any symptom that could be related to perforation  were invited to participate in the study. Participants were evaluated by three different diagnostic methods  performed by three different evaluators in a blind fashion. The microscope was considered the reference standard.p <  0.001) considered the video otoscope as the best method for understanding the tympanic membrane condition presented by them.176 patients were evaluated, totaling 352 tympanic membranes. Twenty-seven tympanic membrane perforations were diagnosed by the microscope, a prevalence of 7.7%. The video otoscope showed a sensitivity of 85.2% (95% CI 81.5%‒88.9%), specificity of 98.1% (95% CI 96.7%‒99.5%) and accuracy of 97.1% (95% CI 95.4 %–98.8 %). The conventional otoscope showed a sensitivity of 96.3% (95% CI 94.3–98.3), specificity of 98.8% (95% CI 97.7–99.9) and accuracy of 98.6% (95% CI 97.4–99.8). The Kappa value between the microscope and the video otoscope was 0.8 and between the microscope and the conventional otoscope was 0.9. Regarding the participants' perception, 53.4% —Level 2 . The Tympanic Membrane (TM) is a thin tissue layer that separates the outer ear from the middle ear, playing an important role in transmitting and conducting sound waves to the ear bones.3Although part of the perforations may heal spontaneously,In this regard, it is noteworthy that the surgical microscope showed high accuracy in the evaluation of tympanic alterations,Although the video otoscope has been the subject of studies aimed at determining its diagnostic accuracy in other otologic conditions, such as acute otitis media,Thus, the main purpose of this study was to evaluate the diagnostic accuracy of the video otoscope compared to the microscope in cases of TM perforation in patients with otologic complaints seen in the hearing health division of a tertiary-level hospital.The secondary objectives were to evaluate: the diagnostic accuracy of the conventional otoscope in cases of TM perforation; the agreement between methods regarding the estimated size of the TM perforation; and the participants' preference regarding the method used.This is a diagnostic accuracy study conducted in the hearing health division of a tertiary-level referral hospital in the areas of otology and craniofacial anomaly rehabilitation.All patients over 8-years of age seen at the outpatient clinic of the study site were considered eligible. The inclusion criteria was the presence of any otologic symptom that indicated otoscopy and that could be related to TM perforation, including otalgia, otorrhea, tinnitus and hypoacusis.The exclusion criteria were previous history of TM perforation recorded in the participant's medical records and the presence of obstruction in the external ear canal that made it impossible to visualize the TM. It is noteworthy that the cases of obstruction caused by cerumen accumulation were managed by the evaluator responsible for evaluating the conventional otoscope, since the procedure for cleaning the canal is simpler with this method. Once unobstructed, the participant was evaluated by the remaining methods in the sequence.Informed consent was obtained from the study participants by one of the research team members. In cases of participants between the ages of 8 and 18, in addition to the consent form signed by the child's guardian, an informed consent form was also obtained from the participant.•OPMI Sensera surgical microscope (Zeiss®)•Diagnostic Otoscope K100 (HEINE Optotechnik GmbH & Co. KG®)•-Lens diameter: 4.5 mm-Focal length: 1.5–2 cm-Pixel: 3 MP-Resolution: 1080p-Light source: 6 LEDsWiFi Digital Otoscope R1 (Bebird®):The following materials were used in this study for the TM assessment of all participants:After acceptance of participation in the study, all participants were evaluated by three different diagnostic methods , in a sequential and blind fashion between the three different examiners, which were performed by the otology team of the hospital, composed of otolaryngologists.The research team defined at the time of the exam which examiner would use each method, so that the examiners did not systematically repeat the method they used. After each evaluation, the physician filled out the electronic form with the participant's otoscopy data and did not communicate the findings either with the patient or with the rest of the research team. Thus, the participant was always submitted to three evaluations performed by three different methods and by three different evaluators.When describing the otologic physical examination, the evaluator filled in whether the participant had an intact or perforated TM, what the estimated size of the perforation was when present, and reported other otoscopy findings, such as tympanosclerosis, otorrhea, desquamation, etc. The information about the presence or absence of perforation was used to determine the accuracy levels of the methods, as reported below.1)With which diagnostic method did you feel more comfortable ?2)With which diagnostic method did you feel most uncomfortable ?3)Which diagnostic method do you consider to have been most useful for a better understanding of your TM's presented condition?After the three otoscopies were done, the findings were shared between the examiners and with the participant, in order to define the management to be followed in each case. In addition, the participants were asked to answer a form with the three questions above:For each question, participants were asked to choose one of the four options listed: microscope, conventional otoscope, video otoscope, or indifferent.The sample size was calculated based on an estimated sensitivity of the video otoscope in diagnosing cases of TM perforation of 80%, with a maximum margin of error of 15%. These values were indicated from the clinical experience of the hospital specialists. Additionally, a prevalence of 7.8% of TM perforation cases was considered among patients seen at a reference hospital in the area, based on the literature.Data collection began after project approval by the Ethics in Research Committee of the institution, under protocol n° 4.822.715. The REDCap platform was used for data registration and the project was registered at the beginning of the research in the Brazilian Clinical Trials Registry (ReBEC) platform, under number RBR-3786p33.The data obtained in this study were exported from REDCap and initially submitted to a descriptive statistical analysis. For the analysis of the main objective, McNemar's test for paired data was used, comparing the diagnoses made by conventional methods and by video to the reference standard ‒ microscope. In addition, the Cohen's Kappa Test was performed to assess the agreement between the methods. The Bland-Altman analysis was performed for agreement between the methods regarding the size of the perforation. Finally, for the analysis of the participants' preferences regarding the methods used, the chi-square adherence test was performed.According to the sample calculation performed at the beginning of the study, 352 TMs from 176 different patients were evaluated, totaling 1056 otoscopies. Besides these, five patients (10 TMs) were excluded from the sample, since three patients had a record of TM perforation in their medical records, one had bilateral external otitis that made it impossible to visualize the TM, and the last patient had bilateral external ear canal stenosis .Figure 1The sample was composed of 54% (95) of female patients and 46% (81) of male patients. The mean age of the participants was 52.2 (±17.8) years, with the lowest age found being 10 years and the highest being 91 years.Regarding the complaints reported by the participants, hypoacusis was the most frequent, present in 93.5% (329) of the evaluated ears. In the sequence, tinnitus appeared in 16.4% (58) of the sample, besides otorrhea with 9.4% (33) and otalgia with 4.5% (16).In the sample evaluated, 27 TM perforations were diagnosed by microscopy, representing 7.7% of prevalence. Of these, 48.1% (13) were in the right ear and 51.9% (14) in the left ear. In these perforation cases, otorrhea appeared as the second most prevalent symptom, with 48.1% (13), behind hypoacusis with 85.2% (23). Besides these, otalgia presented 22.2% (6) and tinnitus 14.8% (4) of prevalence.p =  0.527).In the contingency table  are the p =  0.180).p <  0.001), while the value for agreement between the microscope and the conventional otoscope was 0.9 (p < 0.001).The Cohen's Kappa Test was performed to assess the agreement between the methods. The Kappa value for agreement between the microscope and the video otoscope was 0.8 . Additionally, the linear regression test showed that there was no trend toward overestimation or underestimation of perforation size when evaluated by the video otoscope (p =  0.743).In addition, the evaluators were asked to estimate the size of the perforation, assigning a value in percentage, being the total perforation considered as 100%. To compare the agreement between the video otoscope and the microscope in the question of the perforation size, the Bland-Altman analysis was performed  with thet-test also showed that the differences were not significantly different from 0 (p =  0.375). In addition, the linear regression test showed no trend towards higher or lower values of this method in relation to the evaluated perforation size (p =  0.531).Bland-Altman analysis was also performed to evaluate the agreement between the conventional otoscope and the microscope regarding the size of the TM perforation, in true-positive cases (26), estimated by the evaluators . The t-tp <  0.001).Regarding the participants' perception of comfort, i.e., the method they classified as the least uncomfortable, the microscope got 26.7% (47) of the votes, the video otoscope got 13.1% (23), and the conventional otoscope got 3.4% (6). However, most patients, 56.8% (100), said there was no difference between the methods regarding comfort, and the Chi-Square test showed a statistically significant difference in this attribution (p <  0.001). Also in this context, the video otoscope got 14.8% (26) of the votes, followed by the microscope and conventional otoscope with 6.8% (12) each.Regarding discomfort, i.e., the method that was most uncomfortable during otoscopy, most participants also classified as having no difference between the methods, with 71.6% (126), a statistically significant result (p <  0.001).As for the method classified by the participants as being the most useful for understanding the otologic condition presented by them, whether normal or pathological, the video otoscope was the most chosen, with 53.4% (94). In addition, 34.1% (60) of people considered that there was no difference between the methods, followed by the microscope with 11.9% (21) and the conventional otoscope with 0.6% (1). The choice of the video otoscope as the best method in this question also showed statistical significance in the Chi-Square test , project number 2021/09023-0.This study was supported by The authors declare no conflicts of interest.


Paravalvular leak (PVL) is a shortcoming that can erode the clinical benefits of transcatheter valve replacement (TAVR) and therefore a readily applicable method (aortography) to quantitate PVL objectively and accurately in the interventional suite is appealing to all operators. The ratio between the areas of the time-density curves in the aorta and left ventricular outflow tract (LVOT-AR) defines the regurgitation fraction (RF). This technique has been validated in a mock circulation; a single injection in diastole was further tested in porcine and ovine models. In the clinical setting, LVOT-AR was compared with trans-thoracic and trans-oesophageal echocardiography and cardiac magnetic resonance imaging. LVOT-AR > 17% discriminates mild from moderate aortic regurgitation on echocardiography and confers a poor prognosis in multiple registries, and justifies balloon post-dilatation. The LVOT-AR differentiates the individual performances of many old and novel devices and is being used in ongoing randomized trials and registries. Among the imperfect results, paravalvular leak (PVL) is one that contributes considerably to the erosion of clinical benefits with its adverse effects on mortality, morbidity, and reverse cardiac remodeling. Consequently, a simple method, readily applicable in the interventional suite to timely detect and quantitate PVL objectively, reproducibly, and accurately remains the wish and goal of the “minimalist” operator.Trans-thoracic echocardiography (TTE) is a safe and convenient tool that provides real-time information on the severity of trans- or para-valvular aortic regurgitation (AR) and is thus the preferred method of assessing and monitoring PVL. However, TTE is not exempt from methodological drawbacks such as the significant influence of the imaging plane and a lack of consistency in the severity of PVL described between core labs and between imaging modalities  1)..1).in vitro and in vivo validation, correlation with other imaging modalities, prognostic value, current limitations, and potential for future development. To find relevant articles for this narrative review, we searched MEDLINE and Embase for articles in English language with the following terms: “Paravalvular leak”, “PVL”, “aortic regurgitation”, “AR”, “Transcatheter aortic valve implantation”, “TAVI”, “transcatheter aortic valve replacement”, “TAVR”, “video-densitometry”, “aortography”, and “Quantitative Aortography”.In the era of minimalist TAVR the use of angiography has become more common as it provides PVL grading as the sum of all jets regardless of their number, level, or trajectory, furthermore as it is performed immediately post implant, any significant PVL can be corrected by device post-dilatation, repositioning, or implantation of a second valve. Interventional cardiologists are familiar with this technique, which is fast, readily available, and part of their technical environment, however, angiographic grading is qualitative and subjective. These issues highlighted the need for a quantitative assessment of PVL from aortography. In this comprehensive narrative review, we delve into the principles and history of video-densitometric assessment of aortic regurgitation, discussing its In the eighties, long before the TAVR era, aortography was dethroned by echocardiography for the iterative and non-invasive assessment of AR, however, aortography was actually already “quantitative” at the time, and several attempts had been made to make the assessment of AR by aortography more objective, less categorical and more numerically quantitative –5. At thThe most common objection raised by clinicians regarding the methodology of video-densitometry is the potential for measurement errors due to an assumed parallax effect when the outflow tract is assessed from various angiographic views. However, the approach is aimed at circumventing this issue; a video-densitometric measurement is the constant product of an area in which the radiopaque contrast is detected, multiplied by the density (hemodilution) of the radiopaque contrast medium in that area/volume . This meIn 2014, Schultz et al.  used vidn = 44) of 285 retrospective aortograms and in 69% (n = 22) of 32 prospectively collected aortograms. Nevertheless, the visual grade of AR (Sellers) was highly correlated with the time-density measurements including the Relative Area Under the Curve (RAUC) and qRA index . Inter-observer reproducibility of visual grading was moderate . Inter-observer measurement of RAUC and qRA index were highly correlated  and showed a high level of agreement (0.00 ± 0.25).However, the criteria for analyzability were only met in 15%  constructs two time-density curves assessed in two ROI: the aortic root where contrast is injected and the LVOT where the regurgitation is quantified. To define the LVOT area a line is drawn from the valve plane to the apex, subdivided in three equal regions; the upper region is the ROI for the video-densitometric assessment of regurgitation in the LVOT. The ratio between the areas under the two-time density curves of these regions over at least three cardiac cycles is the Regurgitation Fraction expressed in percentage.This new approach was called “LVOT-AR”—left ventricular outflow tract-aortic regurgitation  –and itsp = 0.53], and the two observers’ measurements highly correlated .Using the LVOT-AR, inter-observer variability in a Bland Altman analysis was low  among patients with an LVOT-AR > 17% compared to an LVOT-AR ≤ 17% ..p = 0.00P = 0.03) as well as in patients with an LVOT AR > 17% vs. an LVOT-AR ≤ 17%    Central p = 0.0023, HR 2.64 (1.27–5.50), p = 0.0023]  and the prevalence of LV hypertrophy  compared to baseline. In contrast, among patients with an LVOT-AR > 17%, the LVMi  and the prevalence of LVH  evolved in the opposite direction and failed to show any significant change  Central Illustration D. Of note the cut-off criteria of video-densitometric regurgitation vs. categorical echocardiographic assessment of none/trace, mild, and moderate/severe regurgitation has been specifically determined in a blind fashion (CORRIB lab) by C statistic and AUC in a cohort of patients studied at Bad Krozingen (Courtesy of Prof Neuman and dr Schoechlin) -, on the prediction of 5-year mortality, a preliminary analysis shows diverging Kaplan-Meyer curves and suggest a potential mortality discrimination between none/trace (LVOT-AR 0%-2%), mild (LVOT-AR 3%-16%) and moderate/severe (LVOT-AR >16%)regurgitation  .LVOT-AR by video-densitometry has been evaluated in comparison with TTE, TEE and CMR using a variety of THV devices. However, due to the retrospective nature of these analyses and the absence of any specific acquisition protocols, analyses were only feasible in 57.1% and 57.5% of the patients enrolled in the respective Brazilian TAVR Registry , 20 and The major issue impacting on the feasibility of retrospective LVOT-AR assessment is the overlap of the descending aorta with either the ROI (LVOT) or the reference area (aortic root). The software analyses the density changes over time in both regions, thus any other change in density in the background of the RX acquisition due to contrast passing through the descending aorta and overlapping with these regions impacts on the final result. Although the analyses are still technically possible in these situations, the results would not reflect the true regurgitation; therefore, they are considered non-analysable.Methods to improve the feasibility of video-densitometry include using pre-procedural multi-slice computed tomography (MSCT) to optimize the angiographic projection, and this was first tested at the Yamaguchi University along with other directives to optimise the angiographic acquisition protocol for video-densitometry n = 54) or following (n = 38) implementation of a standardized acquisition protocol. The protocol involved using MSCT for planning the optimal angiographic projection, and its use led to the feasibility of video-densitometry improving from 57.4% to 100% r = 0.94, p < 0.0001)  .p = 0.159: or Circle 98.5% vs. 3mensio 95.8% vs. Teng's rule 93%, p = 0.247) (These promising results paved the way for the ASSESS-REGURGE (NCT03644784) registry, which was a multi-continental trial conducted in four centres in Asia (Japan), North America (Canada), and Europe (the Netherlands and Germany) enrolling 354 consecutive patients with Heart Team consensus in favour of TAVR over a median period of 12 months. In this registry, operators performed the final aortogram according to an angiographic projection which was pre-planned by CT (3mensio or Circle) or visually by fluoroscopy (Teng's rule) . An inde= 0.247)  Figure 7R2 0.87, p < 0.001), with an intraclass correlation coefficient of 0.962   to determine the feasibility of online assessment of regurgitation  and the reproducibility of results between online and offline analysis by the core laboratory. One hundred consecutive patients with aortic stenosis and indications to undergo TAVR were enrolled. The planning of optimal views for video-densitometry was determined with the use of Heart Navigator software  < 0.001) .χ2p < 0.001). p < 0.001).Taking advantage of our large network, we performed a multicentre retrospective corelab pooled analysis of aortograms from over 2,665 consecutive patients treated with 14 different THV devices –27 whichPost-hoc two-by-two testing showed that the Lotus valve had a significantly lower RF compared with each of the other valves except for the ACURATE neo2, which had a significantly lower RF compared with SAPIEN 3, Evolut R, SAPIEN XT, Venus-A, ACURATE neo, and CoreValve. Similarly, the first generation CoreValve had a significantly higher RF than all the other valves. Apart from the CoreValve, Lotus, and ACURATE neo2, no other valve differed in the amount of RF from each other.These result highlight that the Lotus valve has the lowest average RF and the ACURATE neo2 the lowest percentage of moderate/severe regurgitation, with the latter device performing significantly better than the ACURATE neo. Myval, VitaFlow and Venus-A are promising options in the THV armamentarium. In our latest report of 103 patients receiving the new Myval Octacor THV, moderate AR was basically eliminated in patients with tricuspid valve morphology . Of noteWith our colleagues and industrial partners, we continue to analyze new commercially available THVs. Analysis post-TAVR using JenaValve  Comparison of aortic regurgitation following different TAVR devices by video-densitometry and echocardiography is explained in detail in the Serruys et al.  used LVOVideo-densitometric angiography is, however, not without limitations. Various radio-opaque objects intrathoracic or extracorporeal  may interfere with the video-densitometric background of ROI's. Whenever possible the radio-opaque structures not permanently implanted should be removed prior to aortography.Video-densitometric angiography is also sensitive to pulmonary diaphragm/patient/table motion. If the standardized protocol of acquisition avoiding the over-projection of the ascending and descending aorta over LVOT has dramatically improved the feasibility of analysis (see above), nevertheless it remains that the volume, rate, and time of injection could be further optimized and regulated by single diastolic injection triggered by ECG, thereby reducing the injected amount of contrast medium to a minimum of 8 ml , 12. The.Although still absent on European and American practice guidelines of TAVR, Quantitative aortography with video-densitometric assessment is increasingly recognized as a valid method for aortic regurgitation assessment. Indeed, video-densitometry was mentioned in the VARC III document  as an acCurrently, the Pause-VD trial  investigThe OVAL GUIDE trials are prospective, multicentre, observational, investigator-initiated studies, aimed at intraprocedural TAVR guidance using online video-densitometric angiographic AR quantification for determining whether a PVL requires further corrective measures. Design of both trial is described in the in vivo by thermodilution Angiographic assessment of mitral regurgitation fraction (MRF) remains at best semi-quantitative (Sellers's method) and operator dependent. Recently an attempt was made to adapt the video-densitometric methodology to the mitral space. In vitro MRF and MRV were assessed in a mock circulation with transonic flow measurement at a cardiac output comparable as the one measured in vitro and in vivo MRF, MRV, and interobserver reproducibility for QMR analysis strongly correlated. There were also very strong correlations of in vivo MRF between 2 independent analysts, in vivo MRF using the novel software is feasible, accurate, and highly reproducible. These promising results have led us to initiate the first human feasibility study comprising patients undergoing percutaneous mitral valve edge-to-edge repair (The e repair  or mitraOne of the limitations of two-dimensional video-densitometry is the lack of three-dimensional localization of the regurgitation jet. Development of three-dimensional video-densitometric analysis from biplane aortography is ongoing .Automatic identification of the aortic root and the LVOT during video-densitometric analysis by applying deep learning algorithms is considered the next step towards a seamless integration of quantitative video-densitometric assessment of aortic regurgitation into a minimalist TAVR approach.Quantitative video-densitometric assessment of paravalvular leak by aortography is an objective, accurate, and reproducible tool which has been extensively vetted and validated in-vitro, in-vivo, and in clinical settings, for the assessment of AR following TAVR. Many TAVR devices have been evaluated using video-densitometry, and the technique is currently being used in ongoing trials and registries. Three-dimensional video-densitometric analysis for precise spatial localization of paravalvular jets might be the next frontier.


Pouch of Douglas obliteration, which prevents exteriorization of the uterus, increases surgical morbidity in patients with placenta previa. We aimed to identify magnetic resonance imaging features that can predict pouch of Douglas obliteration preoperatively.We retrospectively assessed 39 women with posterior placenta previa who underwent magnetic resonance imaging for the preoperative assessment of placenta accreta spectrum. We defined the angle formed by the anatomical conjugate line (based on pelvimetry) and the cervical canal as the cervical inclination angle, which was measured on sagittal T2-weighted magnetic resonance imaging. Subsequently, we analyzed the correlation between the cervical inclination angle and pouch of Douglas obliteration.The median maternal age was 34 years  and 26 (66.7%) women delivered at term. The median cervical inclination angle was 98° . Pouch of Douglas obliteration was confirmed in six patients (15.4%). The cut-off value of the cervical inclination angle for the prediction of pouch of Douglas obliteration was 102° with a sensitivity of 66.7%, specificity of 78.8%, positive predictive value of 36.4%, and negative predictive value of 92.9% .Measuring the cervical inclination angle may help in ruling out an obliteration of the pouch of Douglas. It may also be useful in the operative management of women with posterior placenta previa. However, caution should be exercised when generalizing the results of this study because of the small sample size, which makes the results prone to bias. Placenta previa is associated with significant intraoperative and postpartum bleeding , 2. AccoThis retrospective observational cohort study was conducted at Yamanashi Prefectural Central Hospital between April 2016 and December 2021. We enrolled women with posterior placenta previa, including those with low-lying placenta as defined by a previous study , who und2]. The presence of ≥1 abnormal plasma glucose value  after a 75-g oral glucose tolerance test was diagnosed as GDM [Obstetric data were collected from the medical and operative records. Gestational age was determined on the basis of the maternally reported last menstrual period and was confirmed by the crown-rump length measured on ultrasonography performed during the first-trimester. We recorded data on the mother’s age at delivery, orientation of the uterus in the early first trimester, gestational age at MRI examination, cervical length, history of previous cesarean section, use of in vitro fertilization, parity, amount of bleeding including amniotic fluid, gestational age at delivery, maternal stature, pre-pregnancy weight status, fetal sex, neonatal birth weight, presence of gestational diabetes mellitus (GDM), and hypertensive disorders of pregnancy (HDP). Placenta previa was defined as the presence of placental tissue extending over the internal cervical os . Low-lyid as GDM . Cervicad as GDM .We defined the angle formed by the anatomical conjugate line (based on pelvimetry) and the cervical canal as the cervical inclination angle (CIA), which was measured using MRI. MRI was performed at approximately 34 weeks gestation, since the mean reported gestational age at delivery in patients with placenta previa is 34–35 weeks . HoweverBased on a previous study , we consAll patients included in our study underwent MRI at Yamanashi Prefectural Central Hospital using two 1.5-T MR scanners .2 test were performed to compare the maternal and neonatal outcomes. Fisher’s exact test was used when the expected frequency was <5.First, the Mann-Whitney U test and χp-values <0.05 were considered statistically significant.As the histograms were not normally distributed for several continuous variables, we selected the Mann-Whitney U Test, which can be used to test whether there is a difference between two groups, and the data need not be normally distributed. Second, receiver operating characteristic (ROC) curve analysis was conducted to determine the best cut-off value for the CIA and cervical canal angle. We used the Youden index, which describes the maximum vertical distance between the ROC curve and the diagonal (random chance), to estimate the optimal cut-off values . Finallyn = 2; PROM, n = 1; strong cervical canal curvature, n = 1; gauze tamponade, n = 1). The median maternal age was 34  years; 15 (38.5%) women were nulliparous, and 26 (66.7%) had term deliveries. The median CIA was 98° . The overall incidence pouch of Douglas obliteration was six (15.4%). In evaluating the orientation of the uterus, 32 of the 39 women with posterior placenta previa were included in this study, after excluding 7 women . Three (9.4%) of the 32 women had a retroflexed uterus. Although the sample size of the retroflexed group was too small for us to draw a conclusion, the frequency of pouch of Douglas obliteration  differed significantly between the retroflexed (n = 3) and non-retroflexed groups (n = 29).During the study period, 44 women with posterior placenta previa underwent MRI for the preoperative assessment of PAS. Thirty-nine women were included in this study, after excluding 5 women  of 6 women with posterior extrauterine adhesions in this study cohort did not have pelvic inflammatory disease or a history of pelvic surgery, which are known risk factors for posterior extrauterine adhesions , and wer.3% of 6 Previous studies reported that the atypical orientation of the uterus, such as retroflexion, which reflects the adhesion between the posterior wall of the uterus and the retroperitoneum or intestinal tract due to endometriosis, pelvic inflammatory disease, and pelvic surgery, is associated with pouch of Douglas obliteration –22.We examined the association between the atypical orientation of the uterus and obliteration of the pouch of Douglas using ultrasonography imaging performed in the early first trimester. We found that the frequency of pouch of Douglas obliteration was significantly higher in the retroflexed group than in the non-retroflexed group. However, as shown in A previous study that conducted propensity score matching for patients with placenta previa reported that the amount of intraoperative blood loss was significantly higher in the posterior extrauterine adhesion group than in the control group . MoreoveMatsuzaki et al. reported that the cervical canal angle is useful for predicting the absence of pouch of Douglas obliteration in women with placenta previa  . We examThis study has several limitations. First, extrapolating our results to the general population may be difficult because it is difficult to draw conclusions on the relationship between CIA and obliteration of the pouch of Douglas in this study due to the sample size and single center setting. The positive predictive value and sensitivity for predicting pouch of Douglas obliteration in this study were relatively low. As a result, it was challenging to accurately predict pouch of Douglas obliteration using CIA. However, the negative predictive value was very high at 92.9%, which may be useful in ruling out pouch of Douglas obliteration.Therefore, a large-scale, multicenter, prospective cohort study is required to confirm these results in the general population. Second, MRI scans are generally not performed in cases of placenta previa, unless an adherent placenta is suspected; therefore, the results of this study should be interpreted with caution. Third, some potential risk factors that affected or biased the CIA, such as fetal weight, uterine myoma, and uterine adenomyosis, were not evaluated, which may have influenced the study results . Fourth,CIA may have a high ability to rule out an obliteration of the pouch of Douglas. It may also be a useful indicator in the surgical management of women with posterior placenta previa. However, caution should be exercised when generalizing the results of this study because of the small sample size, which makes the results prone to bias.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S1 File(XLSX)Click here for additional data file.