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: 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.

The link between obstructive sleep apnea (OSA) and obesity, and their common comorbidities such as diabetes mellitus (DM) or cardiovascular diseases, is not fully understood. The aim of this study was to investigate the possible association of OSA severity in obese individuals with polysomnography-based sleep parameters, as well as C-reactive protein (CRP) and glycated hemoglobin (HbA1c) serum levels. Polysomnographic recordings and blood samples were retrospectively compared between a group of 23 adult obese individuals with mild OSA (apnea–hypopnea index (AHI) = 7.5 (5.5–12.5)/h, age = 42.57 ± 11.44 years, 16 male, 7 female, body mass index (BMI) = 37.35 ± 3.88 kg/m²) and an age-, sex-, and BMI-matched group of individuals with moderate or severe OSA (AHI 41.5 (25.7–71.8)/h, age = 43.43 ± 11.96 years, 16 male, 7 female, BMI = 37.87 ± 4.74 kg/m²). All respiratory sleep-associated parameters were significantly higher in individuals with moderate and severe OSA compared to those with mild OSA. CRP levels did not differ between the two OSA severity groups. However, serum levels of HbA1c were significantly higher in the moderate/severe OSA group. Therefore, OSA severity may have a significant impact on glycemic control in obese individuals. Additionally, OSA severity did not appear to be further associated with systemic inflammation in obese individuals. Obese individuals may benefit not only from lifestyle modification, but also from OSA screening and treatment, particularly to prevent DM-associated disorders and conditions.

Hypoglossal nerve stimulation (HGNS) is a treatment for obstructive sleep apnea (OSA) patients with intolerance of positive airway pressure therapy. Comorbid insomnia is quite prevalent in OSA patients. We investigated the impact of insomnia and excessive daytime sleepiness (EDS) on polysomnography metrics after HGNS treatment. Data of 27 consecutive patients (9 female; mean age 55.52 ± 8.6 years) were retrospectively evaluated. Insomnia was assessed using the ISI (insomnia severity index) and EDS using the Epworth sleepiness scale (ESS). The median ISI was reduced significantly 3 months after HGNS activation (preoperative: 19; postoperative: 14; p < 0.01). Significant correlations emerged between preoperative ISI and postoperative AHI (apnea/hypopnea index; Spearman’s rho = 0.4, p < 0.05), ∆ AHI (r = −0.51, p < 0.01) and ∆ ODI (oxygen desaturation index; r = −0.48, p < 0.05). ISI correlated strongly with EES both preoperatively (r = 0.46; p < 0.02) and postoperatively (r = 0.79; p < 0.001). Therefore, HGNS therapy is associated with a significant reduction of insomnia-related symptoms, in addition to the improvement in respiratory metrics in OSA. Nonetheless, the preoperative severity of patient-reported insomnia symptoms was inversely correlated with the respiratory PSG-outcomes after HGNS. Insomnia should be considered in studies of EDS in OSA patients, especially those treated with HGNS.

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.

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. 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. 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). 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.