Background: In patients with haemophilia (PwH), most frequently affected joints are the ankle, knee and elbow. Due to improved factor therapy in the last decades, these previous findings have to be verified in Germany.Aim: The aim of this study is to detect the most affected joint, evaluate the significance of the source of pain and determine the point prevalence of back pain in Germany today.Patients and methods: In a retrospective study, data of n = 300 patients with severe moderate and mild haemophilia were evaluated regarding the most affected joint, the most common source of pain, and the point prevalence of back pain. An anamnesis questionnaire and the German Pain Questionnaire were used for this assessment.Results: The most affected joint in German PwH is still the ankle (41%), followed by the knee (27%) and the elbow (11%). The most common source of pain is also the ankle joint (32%). Back pain was also identified as one of the most common sources of pain, which is comparable to the elbow (elbow:15%; back:13%). The point prevalence in PwH for back pain was significantly higher compared to the general German population (P = .031).Conclusion: Our data showed that the ankle is still the most affected joint and the most common source of pain in Germany. These results also showed the relevance of back pain as a pain source. The evaluations also demonstrated the high point prevalence of back pain in PwH. Future therapies should also focus on the spine because joint changes affect posture.

Prolonged gaze at a smartphone is characterized by pronounced flexion of the cervical spine and is associated with health risks. In addition, it is suspected that smartphone distraction could lead to gait changes. Therefore, the aim of this study was to detect smartphone-associated postural changes at thoracic and lumbar levels as well as gait changes. Spinal analysis was performed prospectively in 21 healthy men using the DIERS 4Dmotion^®Lab in a controlled crossover design to evaluate posture-associated parameters while standing and walking. The examination sequence provided three randomized gaze directions: GN = Gaze Neutral; S1H = Smartphone one-handed; S2H = Smartphone two-handed. Results reveal a higher vertebra prominens (VP)-flexion in S1H (23.8° ± 6.9°; p ≤ 0.001) and S2H (22.4° ± 4.7°; p ≤ 0.001) compared to GN (17.6° ± 3.8°). Kyphosis angles were also different with higher values observed in S1H (58.8° ± 5.8°; p ≤ 0.001) and S2H (61.6° ± 4.9°; p ≤ 0.001) compared to GN (49.1° ± 4.6°). During walking, similar results were observed in kyphosis angles. No differences were observed in gait during smartphone use (p = 0.180–0.883). The study revealed a significantly increased inclination of the lower cervical and thoracic spine during smartphone use. However, the inclination was larger during S2H. Standing or walking conditions did not affect the measurement outcomes. Long-term smartphone use associated with a larger inclination of the cervical and thoracic spine might result in increased pressure and shear forces acting on vertebral bodies, intervertebral discs, and muscles, which potentially increases the risk of spinal pain and disease.

Introduction: Regular physical activity (PA) is recommended for patients with haemophilia (PwH). For PwH it is crucial to ensure a sufficient factor level to prevent PA‐induced bleedings. However, there is a gap in the literature dealing with specific factor levels, which are needed when performing specific types of PA.Aim: To provide data on factor VIII (FVIII) levels at the start of PA performed by PwH.Methods: In this prospective 12‐month real‐world observational study, 23 PwH recorded every PA they performed and the FVIII levels at the start of the PA using a pharmacokinetic application. PA types were clustered according to the collision and injury risk into three categories (Cat I = low, Cat II = medium, Cat III = high risk). Haemophilia Joint Health Scores (HJHS) were performed at baseline, after 6 and 12 months.Results: 795 PA sessions of Cat I, 193 of Cat II, and 23 of Cat III were documented. FVIII levels at the start of PA were different between categories (Cat I: 29.8 ± 32.1%, Cat II: 38.3 ± 33.4%, Cat III: 86.6 ± 29.2%). Out of all PA sessions, 145 (14%) were performed at a factor level of ≤3%. Three PA‐induced bleeding occurred. Baseline HJHS was 14.5 ± 13.6 points and did not change throughout the study.Conclusion: This study provides real‐life data on FVIII levels at the start of 1011 PA sessions. PwH are mainly active in low‐risk sports with higher FVIII levels observed in Cat II and III, respectively. Only three PA‐induced bleeding occurred, even though several PA were started with low FVIII levels.

Background: There is limited research on body composition in persons with haemophilia (PwH). The literature describes an increased body fat distribution and decreased lean mass in PwH compared to healthy controls using bioimpedance analysis. Using dual x‐ray absorptiometry (DXA), which is known to be the most accurate method, this investigation aims to postulate reference data for body composition parameters within haemophilia severity phenotypes and age groups.Methods: Persons underwent whole body DXA screening using Horizon. Body fat percentage, estimated visceral adipose tissue (VAT), appendicular fat and lean mass, and lean and fat mass in relation to body height were assessed. Haemophilia severity and five age groups were distinguished.Results: Two hundred and one persons with mild (n = 44), moderate (n = 41), or severe (n = 116) haemophilia A/B (median age 40 [28–55; 1.IQ–3.IQ] years) were analysed. The median body fat percentage was 28.7% [25.5%–33.9%] and median estimated VAT was 657 g [403–954 g] with no significant difference between severity phenotypes (p = .474; p = .781). Persons with severe haemophilia had less lean mass compared to moderate and mild haemophilia (p = .013; p = .034). Total and appendicular fat is increased in older PwH (aged ≥40 years) compared to younger PwH (aged ≤29 years; p < .05). Lean mass did not differ between age groups.Conclusion: This study provides valuable reference data for body composition parameters in PwH. Persons with severe haemophilia show significantly less lean mass compared to persons with moderate or mild haemophilia. Body fat percentage and VAT did not differ between severity phenotypes, but increased with age.