The da Vinci Single-Port (SP) system received CE Mark approval for transoral robotic surgery in January 2024. Nevertheless, clinical experience with this platform in Europe remains limited - particularly in the field of minimally invasive head and neck surgery. In this report, we present the case of a 51-year-old man with p16-positive squamous cell carcinoma of the right tonsil who underwent transoral robotic resection using the da Vinci SP system, combined with contralateral tonsillectomy and bilateral neck dissection, at a German university hospital. To our knowledge, this represents one of the earliest reported oncologic applications of the da Vinci SP system in Germany following CE mark approval, highlighting its integration into established multimodal treatment pathways for oropharyngeal carcinoma. Further multicenter studies are required to define its role in clinical implementation compared with established techniques such as transoral laser microsurgery and earlier robotic systems.

BACKGROUND:Language barriers are an obstacle in everyday clinical practice. Webbased translation software can offer a low-barrier solution. This study examines the attitudes of employees at a German university hospital towards language barriers and web-based translation software. Furthermore, general data protection aspects for their application in everyday clinical practice are adressed. METHODS:Employees of a university hospital were surveyed on language barriers, their occurrence, strategies for overcoming them, as well as  their use of web-based translation software. Furthermore, the use of such software was analyzed from a data protection and liability perspective. RESULTS:A majority of 80% (111/138) stated that they encountered language barriers in less than half of all patient contacts. Translation software was used in at least half of such cases by 22% (31/138) of respondents. The usefulness of translation software was rated as predominantly positive by 49% (68/138). From a legal perspective, it is strongly recommended that personal data be excluded when using web-based translation software. The use of anonymized data is permissible under data protection regulations. In emergencies or similar exceptional situations, the processing of personal data is also subject to the applicable data protection legislation in these situations. Provided that data protection legislation  requirements are met, the use of personal data is permissible. A general assessment of liability during the use of webbased translation software to fulfill the duty of informed consent is not possible, as it is highly dependent on case-specific factors. However, since translation errors may be attributable in individual cases, a human interpreter should be consulted whenever the treating professional has doubts regarding the patient's understanding or the comprehensibility of the information provided. CONCLUSION:Language barriers pose a potential risk in everyday clinical practice. Webbased translation software is easily accessible and could improve patient safety and treatment outcomes. As the use of anonymized data is feasible in most cases, there are no data protection obstacles to using webbased translation software with such data. In the event of any doubt regarding the patient's understanding of the information provided, the involvement of a human translator is recommended to minimize liability risks.

Purpose:Sleep medicine is a highly resource-intensive field where large language models (LLMs) could offer a promising solution by supporting diagnostic processes. As web-based LLMs have obvious data protection constraints, locally run LLMs are essential for clinical implementation. This study is the first to investigate the performance of locally run LLMs in the interpretation of real-world polysomnographic (PSG) results. Methods:We randomly selected N=30 patients (18 male, 12 female, mean age 50.5 ± 11.1 years, mean body mass index 29.7 ± 5.5 kg/m², mean apnea hypopnea index 30.9 ± 23.8) from the clinical database of our sleep laboratory who underwent PSG due to clinical complaints typical of obstructive sleep apnea (OSA). The board-certified sleep physician's interpretations of diagnosis, suitable first-line therapy or alternative therapy were compared with those of three locally run LLMs (Gemma2, Llama3 and Mistral Nemo) assessing the level of concordance. Results:Gemma2 showed the lowest concordance of 33% (10/30 patients) with the board-certified sleep physician regarding OSA severity, followed by Mistral Nemo at 47% (14/30 patients) and Llama3 at 50% (15/30 patients). For automatic positive airway pressure (aPAP) recommendations, Mistral Nemo showed the highest concordance at 90% (27/30 patients), followed by Gemma2 and Llama3 with 83% (25/30 patients) each. Conclusion:Although locally run LLMs bypass data security constraints and show promising potential for clinical practice, their performance needs significant improvement prior to real-world implementation. Therefore, at present, the routine implementation of locally run LLMs in sleep medicine needs more refinement and fine tuning before they can be used for interpretation of real-world PSG results.

Since the first use of a da Vinci system to perform a radical tonsillectomy in 2007, transoral robotic surgery (TORS) has been further developed and finally accepted as a safe surgical method. The recent introduction of the da Vinci Single-Port (SP) system has brought new innovations in the field of ears, nose and throat (ENT) medicine, e.g. to perform minimally invasive head and neck tumor surgery. In Europe, the da Vinci SP system has recently received CE Mark approval for TORS application. We present the first case of a robot-assisted bilateral benign tonsillectomy with the da Vinci SP system in Germany and demonstrate the technical feasibility of this platform.

Purpose:Timely identification of comorbidities is critical in sleep medicine, where large language models (LLMs) like ChatGPT are currently emerging as transformative tools. Here, we investigate whether the novel LLM ChatGPT o1 preview can identify individual health risks or potentially existing comorbidities from the medical data of fictitious sleep medicine patients. Methods:We conducted a simulation-based study using 30 fictitious patients, designed to represent realistic variations in demographic and clinical parameters commonly seen in sleep medicine. Each profile included personal data (eg, body mass index, smoking status, drinking habits), blood pressure, and routine blood test results, along with a predefined sleep medicine diagnosis. Each patient profile was evaluated independently by the LLM and a sleep medicine specialist (SMS) for identification of potential comorbidities or individual health risks. Their recommendations were compared for concordance across lifestyle changes and further medical measures. Results:The LLM achieved high concordance with the SMS for lifestyle modification recommendations, including 100% concordance on smoking cessation (κ = 1; p < 0.001), 97% on alcohol reduction (κ = 0.92; p < 0.001) and endocrinological examination (κ = 0.92; p < 0.001) or 93% on weight loss (κ = 0.86; p < 0.001). However, it exhibited a tendency to over-recommend further medical measures (particularly 57% concordance for cardiological examination (κ = 0.08; p = 0.28) and 33% for gastrointestinal examination (κ = 0.1; p = 0.22)) compared to the SMS. Conclusion:Despite the obvious limitation of using fictitious data, the findings suggest that LLMs like ChatGPT have the potential to complement clinical workflows in sleep medicine by identifying individual health risks and comorbidities. As LLMs continue to evolve, their integration into healthcare could redefine the approach to patient evaluation and risk stratification. Future research should contextualize the findings within broader clinical applications ideally testing locally run LLMs meeting data protection requirements.

PurposeInstagram ranks among the most used social media platforms worldwide. An increasing number of posts are dedicated to specific medical topics, such as sleep medicine. The educational content of these posts is largely unknown. Therefore, a structured content analysis of posts linked to the hashtag "obstructivesleepapnea" was conducted, as obstructive sleep apnea (OSA) represents the most common sleep-related breathing disorder.MethodsThe hashtag "obstructivesleepapnea" was entered into Instagram's search field. The first linked post was selected and then subdivided into visual content and text content for systematic analysis with a focus on educational information on OSA. Demographic factors of the post such as likes, hashtags and the posting account were also included in the analysis. The data collection was completed for N = 150 consecutive posts.Results37.3% of the visual content and 32.7% of the text content addressed educational information on OSA. In both subgroups, the most frequently discussed aspects were OSA symptoms, comorbidities, and therapy (visual content: 50.0%, 39.3, and 41.1%, respectively; text content: 42.9%, 44.9%, and 24.9%, respectively). The most common (professional) background of the account, as self-stated by the holder, was dentists (29.5%). Additional sleep medicine content was posted by 34.3% of all accounts.ConclusionInstagram offers informative content about OSA and is therefore a potential source for patient education. However, the content available is often poorly organized and in most cases incomplete. Patients may have difficulty categorizing the information provided to benefit from it.

BACKGROUND:Frugal innovations are essential in low-resource settings to provide cost-effective medical solutions without compromising functionality. The Arclight is a robust, solar-powered device that functions as both an ophthalmoscope and an otoscope, priced at approximately 12€ in low- and middle-income countries (LMICs). OBJECTIVES:This study evaluates the Arclight's potential as a video otoscope when attached to smartphones, aiming to enhance telemedicine capabilities in ear examinations. METHODS:Twenty otorhinolaryngology (ORL) specialists rated the standalone Arclight as well as its attachment to an iPhone 12 and a Samsung Galaxy A14 for ear examinations at the University Medical Centre in Mainz, Germany. RESULTS:The standalone Arclight received the highest ratings overall, followed by the Arclight attached to a Samsung Galaxy A14. Attached to the Samsung Galaxy A14, the Arclight demonstrated significantly higher performance regarding ease of focus (p < 0.01), quality of view (p < 0.05), and zoom capabilities (p < 0.05) compared to the iPhone12 attachment. The iPhone12 setup performed lowest in all categories. CONCLUSION:The Arclight is an effective, low-cost tool for ear examinations in low-resource settings. While smartphone integration enhances its potential for telemedicine, performance varies depending on the smartphone used. The Samsung Galaxy A14 proved to be a more reliable option for tele-otoscopy than the iPhone 12. Further optimization is needed to improve smartphone integration and address identified limitations, enhancing the Arclight's utility in telemedicine applications. LEVEL OF EVIDENCE:NA.

Background Large language models (LLMs) have great potential to improve and make the work of clinicians more efficient. Previous studies have mainly focused on web-based services, such as ChatGPT, often with simulated cases. For the processing of personalized patient data, web-based services have major data protection concerns. Ensuring compliance with data protection and medical device regulations therefore remains a critical challenge for adopting LLMs in clinical settings. Objective This retrospective single-center study aimed to evaluate locally run LLMs (Gemma 2, Mistral Nemo, and Llama 3) in providing diagnosis and treatment recommendation for real-world outpatient cases in otorhinolaryngology (ORL). Methods Outpatient cases (n=30) from regular consultation hours and the emergency service at a university hospital ORL outpatient department were randomly selected. Documentation by ORL doctors, including anamnesis and examination results, was passed to the locally run LLMs (Gemma 2, Mistral Nemo, and Llama 3), which were asked to provide diagnostic and treatment strategies. Recommendations of the LLMs and the treating ORL doctors were rated by 3 experienced ORL consultants on a 6-point Likert scale for medical adequacy, conciseness, coherence, and comprehensibility. Moreover, consultants were asked whether the answers pose a risk to the patient’s safety. A modified Turing test was performed to distinguish responses generated by LLMs from those of doctors. Finally, the potential influence of the information generated by the LLMs on the raters’ own diagnosis and treatment opinions was evaluated. Results Over all categories, ORL doctors achieved superior (P<.0005) ratings compared to locally run LLMs (Llama 3, Mistral Nemo, and Gemma 2). ORL doctors’ responses were considered hazardous for patients in only 1% of the ratings, whereas recommendations by Llama 3, Gemma 2, and Mistral Nemo were considered hazardous in 54%, 47%, and 32% of cases, respectively. According to the raters, the LLM’s information rarely influenced their judgment, with Mistral Nemo, Gemma 2, and Llama 3 achieving 1%, 3%, and 4% of the ratings, respectively. Conclusions Although locally run LLM models still underperform compared with their web-based counterparts, they achieved respectable results on outpatient treatment in this study. Nevertheless, the retrospective and single-center nature of the study, along with the clinicians’ documentation style, may have introduced bias in favor of human recommendations. In the future, locally run LLMs will help address data protection concerns; however, further refinement and prospective validation are still needed to meet strict medical device requirements. As locally run LLMs continue to evolve, they are likely to become comparably powerful to web-based LLMs and become established as useful tools to support doctors in clinical practice.

Introduction:Hypoglossal nerve stimulation (HGNS) is a treatment option for patients with moderate-to-severe obstructive sleep apnea (OSA) and intolerance or non-acceptance of positive airway pressure (PAP) therapy. Improvements in respiratory outcomes, sleepiness and quality of life have been demonstrated in treated patients. We aimed at evaluating the bed partner's perspective on HGNS therapy. Methods:In a cross-sectional exploratory prospective study (Clinical Trial Registration: DRKS00030554), 33 consecutive bed partners of patients treated with a unilateral, respiratory-coupled HGNS device in a tertiary medical center completed a 23-item custom-made questionnaire with questions that addressed the bed partner's perceptions and their satisfaction with HGNS therapy. Results:Bed partners reported that the patients were more comfortable with HGNS therapy (97.0%) compared to PAP therapy, their own sleep quality was better (90.9%) and their sexual partnership was equivalent in 69.0% and better in 27.3%. Their partners' snoring was reported as reduced in 87.9%. This trend was especially reported by bed partners of therapy responders. Bed partners did not need to motivate the patients to use HGNS therapy (81.8%), were satisfied with their partners' HGNS therapy (78.9%) and would recommend HGNS therapy to others (81.8%). Response to HGNS treatment or sex did not influence the reported outcomes. Conclusion:Bed partners of HGNS-implanted OSA patients perceive the HGNS therapy mostly positive and are very often satisfied with this therapy. Nonetheless, single aspects of HGNS therapy for OSA may be experienced differently by the patients' bed partners.

Zusammenfassung Hintergrund Biologika ergänzen durch gezielte, hemmende Mechanismen der Typ-2-Entzündung die Standardtherapie für unzureichend kontrollierte schwere Formen der chronischen Rhinosinusitis mit Nasenpolypen (CRSwNP). Trotz Standardisierung mithilfe papierbasierter Checklisten stellen Dokumentation von Anamnese und notwendigen Befunden zur Erfüllung aktueller Verordnungskriterien eine große Herausforderung für Ärzt:innen dar. Ziel der vorliegenden Studie war es, mithilfe von strukturierter Befunderhebung („ structured reporting “, SR) die Qualität jener Dokumentation und den Therapieentscheidungsprozess effizienter zu gestalten. Als Vergleich dienten hierzu die bisher erhältlichen Papier-Checklisten. Methoden Für diese Studie wurde ein inkrementelles Tool programmiert, um aktuelle Befunde zu erfassen und die Erfüllung der Indikationskriterien zu überprüfen. Das Tool wurde in puncto Vollständigkeit, Zeitaufwand und Lesbarkeit mit anderen Checklisten verglichen Ergebnisse Für jede der 3 Dokumentationsmöglichkeiten wurden 20 Befunde erhoben und in die Analyse einbezogen. Die Dokumentation auf den papierbasierten Checklisten hatte einen vergleichbaren Informationsgehalt: 17,5 ± 5,1 bzw. 21,7 ± 7,6 von maximal 43 möglichen Punkten; p > 0 ,05. Die Dokumentation mit der digitalen Anwendung führte zu einem signifikanten Anstieg des Informationsgehalts im Vergleich zu allen papierbasierten Dokumentationen. Die durchschnittliche Punktzahl betrug 38,25 ± 3,7 (88,9 % der Maximalpunktzahl; p < 0,001). Die Nutzerzufriedenheit war im Durchschnitt hoch (9,6/10). Die Nutzung der digitalen Anwendung war anfangs zeitaufwendiger, verringerte sich aber mit zunehmender Anzahl der dokumentierten Fälle erheblich. Schlussfolgerung Die strukturierte Befundung mittels (Web‑)Apps könnte in Zukunft die papierbasierte Befundung zur Indikation einer Biologikatherapie bei CRSwNP-Patient:innen ersetzen und zusätzliche Vorteile in Bezug auf die Datenqualität und Nachvollziehbarkeit der Ergebnisse bieten. Das zukünftig steigende Dokumentationsvolumen, die fortschreitende Digitalisierung und die Möglichkeit der Vernetzung zwischen einzelnen Zentren machen die Einführung einer App in naher Zukunft wahrscheinlich und wirtschaftlich.

Background Few data are available comparing first-line positive airway pressure (PAP) therapy of obstructive sleep apnea (OSA), especially auto-adjusting PAP (aPAP), with second-line hypoglossal nerve stimulation (HGNS) therapy. The aim of this study was to directly compare these therapeutic options by standard polysomnography (PSG)-related parameters and patient-reported outcomes in comparable groups. Methods 20 patients (aged 57.30 ± 8.56 years; 6 female) were included in the HGNS and 35 patients (aged 56.83 ± 9.20 years; 9 female) were included in the aPAP group. In both groups participants had to fit the current guideline criteria for HGNS treatment. Groups were compared by analysis of covariance (ANCOVA) using inverse propensity score weighting. Results Propensity scores did not differ between groups. Pre-therapeutic AHI (HGNS: 40.22 ± 12.78/h; aPAP: 39.23 ± 12.33/h) and ODI (HGNS: 37.9 ± 14.7/h, aPAP: 34.58 ± 14.74/h) were comparable between the groups. After 413.6 ± 116.66 days (HGNS) and 162.09 ± 140.58 days (aPAP) of treatment AHI (HGNS: 30.22 ± 17.65/h, aPAP group: 4.71 ± 3.42/h; p < 0.001) was significantly higher in the HGNS group compared to the aPAP group. However, epworth sleepiness scale (ESS) was post-interventionally significantly lower in the HGNS group compared to the aPAP group (pretherapeutic: HGNS: 13.32 ± 5.81 points, aPAP: 9.09 ± 4.71 points; posttherapeutic: HGNS: 7.17 ± 5.06 points; aPAP: 8.38 ± 5.41 points; p < 0.01). Conclusion These are novel real-world data. More research on the key parameters regarding titration of the HGNS neurostimulation parameter tuning and on the impact of factors influencing HGNS adherence is needed.

Key Clinical Message Color changes of the tympanic membranes without an inflammatory component or perforation are rarely described. They may result from hemorrhage after barotrauma or spontaneously. Other explanatory models include discoloration due to otomycosis. Abstract This is a case of a 61‐year‐old patient with an unexplained incidental of black dots located almost symmetrically on the antero‐inferior quadrant of both tympanic membranes. This harmless anatomical rarity has not been published before. Underlying pathologies should be excluded in the case of discoloration of the tympanic membranes.

From a healthcare professional's perspective, the use of ChatGPT (Open AI), a large language model (LLM), offers huge potential as a practical and economic digital assistant. However, ChatGPT has not yet been evaluated for the interpretation of polysomnographic results in patients with suspected obstructive sleep apnea (OSA). To evaluate the agreement of polysomnographic result interpretation between ChatGPT-4o and a board-certified sleep physician and to shed light into the role of ChatGPT-4o in the field of medical decision-making in sleep medicine. For this proof-of-concept study, 40 comprehensive patient profiles were designed, which represent a broad and typical spectrum of cases, ensuring a balanced distribution of demographics and clinical characteristics. After various prompts were tested, one prompt was used for initial diagnosis of OSA and a further for patients with positive airway pressure (PAP) therapy intolerance. Each polysomnographic result was independently evaluated by ChatGPT-4o and a board-certified sleep physician. Diagnosis and therapy suggestions were analyzed for agreement. ChatGPT-4o and the sleep physician showed 97

Purpose: The gold standard in obstructive sleep apnea (OSA) diagnostics is nocturnal full-night polysomnography (PSG). Due to high costs and high time effort portable respiratory polygraphy (PG or home sleep apnea testing-HSAT) has been developed. In contrast to PG the PSG gains relevant further information concerning sleep stages, arousals and leg movements. However, the role of PG in the diagnostic of OSA remains largely undefined. The aim of this study was to investigate the difference of PG- and PSG-related metrics in OSA, to understand if there is a difference in PG and PSG-based treatment decision and show up the time between performed PG and PSG. Patients and Methods: 99 consecutive patients with existing outpatient performed PG and followed PSG in our tertiary care otorhinolaryngology department between February 2020 and December 2023 were retrospectively assessed. All patients were treatment-naive at the time of consultation. The time between performed outpatient PG and PSG was calculated. Furthermore, clinical baseline parameter and PG as well as PSG data were evaluated. All data were then blinded presented with relevant comorbid diseases to two experts in sleep medicine in our tertiary care centre to decide whether PAP therapy was indicated or not. Results: Mean AHI was significantly higher in PSG (32.32 +/- 22.78/h) compared to PG (22.60 +/- 15.12/h) (p<0.001). Mean duration between performed PG and PSG was 194.99 +/- 131.96 days (range between 37 and 842 days). Only in two patients PAP-therapy was indicated with PG results but not with PSG results. Only in one case PAP-therapy was not indicated with PG results but with PSG results. Conclusion: These data suggest initiating OSA therapy based on PG results for patients with at least moderate OSA on PG, followed by a confirming PSG and a control PSG under treatment to avoid unnecessary prolongation of treatment start.

Purpose:Obstructive sleep apnoea (OSA) is a common disease that benefits from early treatment and patient support in order to prevent secondary illnesses. This study assesses the capability of the large language model (LLM) ChatGPT-4o to offer patient support regarding first line positive airway pressure (PAP) and second line hypoglossal nerve stimulation (HGNS) therapy. Methods:Seventeen questions, each regarding PAP and HGNS therapy, were posed to ChatGPT-4o. Answers were rated by experienced experts in sleep medicine on a 6-point Likert scale in the categories of medical adequacy, conciseness, coherence, and comprehensibility. Completeness of medical information and potential hazard for patients were rated using a binary system. Results:Overall, ChatGPT-4o achieved reasonably high ratings in all categories. In medical adequacy, it performed significantly better on PAP questions (mean 4.9) compared to those on HGNS (mean 4.6) (p < 0.05). Scores for coherence, comprehensibility and conciseness showed similar results for both HGNS and PAP answers. Raters confirmed completeness of responses in 45 of 51 ratings (88.24%) for PAP answers and 28 of 51 ratings (54.9%) for HGNS answers. Potential hazards for patients were stated in 2 of 52 ratings (0.04%) for PAP answers and none for HGNS answers. Conclusion:ChatGPT-4o has potential as a valuable patient-oriented support tool in sleep medicine therapy that can enhance subsequent face-to-face consultations with a sleep specialist. However, some substantial flaws regarding second line HGNS therapy are most likely due to recent advances in HGNS therapy and the consequent limited information available in LLM training data.

Purpose: The coexistence of insomnia and obstructive sleep apnea (OSA) is very prevalent. Hypoglossal nerve stimulation (HGNS) is an established second -line therapy for patients suffering OSA. Studies investigating the effect of the different aspects of insomnia on the therapeutic outcome are largely missing. Therefore, this study aimed to understand the impact of the different aspects of insomnia on the therapeutic outcome under HGNS therapy in clinical routine. Patients and Methods: This is a retrospective study including 30 consecutive patients aged 55.40 +/- 8.83 years (8 female; 22 male) undergoing an HGNS implantation in our tertiary medical center between 2020 and 2023. All patients underwent preoperative polysomnography (PSG) according to AASM. First follow-up PSG was performed 95.40 +/- 39.44 days after activation (30 patients) and second follow-up PSG was performed 409.89 +/- 122.52 days after activation (18 patients). Among others, the following PSGrelated parameters were evaluated: apnea-hypopnea index (n/h) (AHI) and oxygen desaturation index (n/h) (ODI). Insomnia was assessed by the insomnia severity index (ISI) questionnaire. Preoperatively, all patients included filled out each ISI item. Spearman's-rho correlation coefficient was calculated for correlations. Results: Preoperative score of ISI item 1 (difficulty falling asleep) was 1.93 +/- 1.34 and preoperative cumulative ISI score (item1-7) was 18.67 +/- 5.32. Preoperative AHI was 40.61 +/- 12.02 (n/h) and preoperative ODI was 38.72 +/- 14.28 (n/h). In the second follow-up, the mean difference in AHI was triangle 10.47 +/- 15.38 (n/h) and the mean difference in ODI was triangle 8.17 +/- 15.67 (n/h). Strong significant correlations were observed between ISI item 1 (difficulty falling asleep) and both triangle AHI (r: -0.65, p =0.004) and triangle ODI (r: -0.7; p =0.001) in the second follow-up. Conclusion: Difficulty falling asleep may hence negatively influence HGNS therapeutic outcome. Insomnia -related symptoms should be considered in the preoperative patient evaluation for HGNS.

BackgroundPeriodic limb movement disorder (PLMD) and obstructive sleep apnea (OSA) are overlapping clinical syndromes with common risk factors. However, current literature has failed to establish a clear pathophysiological link between them. Thus, little is known about periodic limb movements (PLM) in otherwise healthy patients with suspected OSA.MethodsWe performed a retrospective analysis of 112 patients (age: 44.5 ± 12.0 years, 14.3% female) with suspected OSA who underwent full night polysomnography for the first time. Patients with chronic diseases of any kind, recent infections, malignancies, or daily or regular use of any type of medication were excluded. Group comparisons were made based on the severity of OSA (using the apnea hypopnea index, AHI) or the periodic limb movement index (PLMI).ResultsBoth, PLMI and the total number of periodic limb movements during sleep (PLMS), showed a significant increase in patients with severe OSA. In addition, AHI and apnea index (AI) were significantly higher in patients with PLMI >15/h, with a similar trend for hypopnea index (HI) (p < 0.001, p < 0.001, and p > 0.05, respectively). PLMI was significantly positive correlated with AHI, AI, and HI (r = 0.392, p < 0.001; r = 0.361, p < 0.001; and r = 0.212, p < 0.05, respectively). Patients with PLMI >15/h were significantly older (p < 0.001). There was no significant association between body mass index (BMI) and PLMI >15/h.ConclusionWe found a significant association between the severity of OSA and PLM in our study population with suspected OSA but without other comorbidities. PLMI and PLMS were significantly increased in patients with severe OSA. Future prospective studies with larger collectives should verify the presented results and should include mechanistic aspects in their evaluation.

Obstructive sleep apnea (OSA) has been associated with various acute and chronic inflammatory diseases, as has serum ferritin, an intracellular iron storage protein. Little is known about the relationship between severity of OSA and serum ferritin levels in otherwise healthy subjects. In this study, all polysomnographic recordings, serum levels of ferritin, C-reactive protein (CRP), and hemoglobin, as well as patient files from 90 consecutive, otherwise healthy individuals with suspected OSA who presented to a tertiary sleep medical center were retrospectively analyzed. For comparison, three groups were formed based on apnea–hypopnea index (AHI; none or mild OSA: <15/h vs. moderate OSA: 15–30/h vs. severe OSA: >30/h). Serum ferritin levels were significantly positively correlated with AHI (r = 0.3240, p = 0.0020). A clear trend of higher serum ferritin levels was found when patients with severe OSA were compared to those without or with mild OSA. Serum CRP and serum hemoglobin levels did not differ significantly among OSA severity groups. Age and body–mass index (BMI) tended to be higher with increasing OSA severity. The BMI was significant higher in patients with severe OSA compared to those without or with mild (p < 0.001). Therefore, serum ferritin levels may provide a biochemical surrogate marker for OSA severity.