TY - GEN A1 - Rigamonti, Lia A1 - Estel, Katharina A1 - Gehlen, Tobias A1 - Wolfarth, Bernd A1 - Lawrence, James B. A1 - Back, David A. T1 - Use of artificial intelligence in sports medicine BT - a report of 5 fictional cases T2 - Postprints der Universität Potsdam : Humanwissenschaftliche Reihe N2 - Background Artificial intelligence (AI) is one of the most promising areas in medicine with many possibilities for improving health and wellness. Already today, diagnostic decision support systems may help patients to estimate the severity of their complaints. This fictional case study aimed to test the diagnostic potential of an AI algorithm for common sports injuries and pathologies. Methods Based on a literature review and clinical expert experience, five fictional “common” cases of acute, and subacute injuries or chronic sport-related pathologies were created: Concussion, ankle sprain, muscle pain, chronic knee instability (after ACL rupture) and tennis elbow. The symptoms of these cases were entered into a freely available chatbot-guided AI app and its diagnoses were compared to the pre-defined injuries and pathologies. Results A mean of 25–36 questions were asked by the app per patient, with optional explanations of certain questions or illustrative photos on demand. It was stressed, that the symptom analysis would not replace a doctor’s consultation. A 23-yr-old male patient case with a mild concussion was correctly diagnosed. An ankle sprain of a 27-yr-old female without ligament or bony lesions was also detected and an ER visit was suggested. Muscle pain in the thigh of a 19-yr-old male was correctly diagnosed. In the case of a 26-yr-old male with chronic ACL instability, the algorithm did not sufficiently cover the chronic aspect of the pathology, but the given recommendation of seeing a doctor would have helped the patient. Finally, the condition of the chronic epicondylitis in a 41-yr-old male was correctly detected. Conclusions All chosen injuries and pathologies were either correctly diagnosed or at least tagged with the right advice of when it is urgent for seeking a medical specialist. However, the quality of AI-based results could presumably depend on the data-driven experience of these programs as well as on the understanding of their users. Further studies should compare existing AI programs and their diagnostic accuracy for medical injuries and pathologies. T3 - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 711 KW - Artificial intelligence KW - App KW - Sport medicine KW - Orthopedics KW - Pathologies Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-515528 SN - 1866-8364 ER - TY - GEN A1 - Pérez Chaparro, Camilo Germán Alberto A1 - Zech, Philipp A1 - Schuch, Felipe A1 - Wolfarth, Bernd A1 - Rapp, Michael Armin A1 - Heiβel, Andreas T1 - Effects of aerobic and resistance exercise alone or combined on strength and hormone outcomes for people living with HIV BT - A meta-analysis T2 - Postprints der Universität Potsdam : Humanwissenschaftliche Reihe N2 - Background: Infection with human immunodeficiency virus (HIV) affects muscle mass, altering independent activities of people living with HIV (PLWH). Resistance training alone (RT) or combined with aerobic exercise (AE) is linked to improved muscle mass and strength maintenance in PLWH. These exercise benefits have been the focus of different meta-analyses, although only a limited number of studies have been identified up to the year 2013/4. An up-to-date systematic review and meta-analysis concerning the effect of RT alone or combined with AE on strength parameters and hormones is of high value, since more and recent studies dealing with these types of exercise in PLWH have been published. Methods: Randomized controlled trials evaluating the effects of RT alone, AE alone or the combination of both (AERT) on PLWH was performed through five web-databases up to December 2017. Risk of bias and study quality was attained using the PEDro scale. Weighted mean difference (WMD) from baseline to post-intervention changes was calculated. The I2 statistics for heterogeneity was calculated. Results: Thirteen studies reported strength outcomes. Eight studies presented a low risk of bias. The overall change in upper body strength was 19.3 Kg (95% CI: 9.8±28.8, p< 0.001) after AERT and 17.5 Kg (95% CI: 16±19.1, p< 0.001) for RT. Lower body change was 29.4 Kg (95% CI: 18.1±40.8, p< 0.001) after RT and 10.2 Kg (95% CI: 6.7±13.8, p< 0.001) for AERT. Changes were higher after controlling for the risk of bias in upper and lower body strength and for supervised exercise in lower body strength. A significant change towards lower levels of IL-6 was found (-2.4 ng/dl (95% CI: -2.6, -2.1, p< 0.001). Conclusion: Both resistance training alone and combined with aerobic exercise showed a positive change when studies with low risk of bias and professional supervision were analyzed, improving upper and, more critically, lower body muscle strength. Also, this study found that exercise had a lowering effect on IL-6 levels in PLWH. T3 - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 476 KW - Human-immunodeficiency-virus KW - Quality-of-life KW - Randomized controlled-trails KW - Infected patients KW - Muscle strength KW - Body-composition KW - Nandrolone decanoate KW - Cardiovascular risk KW - Style modification KW - Metabolic syndrome Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419556 SN - 1866-8364 IS - 476 ER -