Hypertrophic obstructive cardiomyopathy (HOCM), the cause of which is unknown, is a heart disease characterized by obstruction of the left ventricular outflow tract and an increase in interventricular septum thickness. Octreotide, a synthetic analogue of somatostatin, was administered subcutaneously to 15 patients for 6 months in order to determine its efficacy in HOCM. Echocardiographic examination was performed in each patient before we had initiated treatment and after treatment. Interventricular septum thickness, interventricular septum thickness/left ventricular posterior wall thickness, and subaortic gradient decreased significantly at the end of treatment. The ratio of the mitral valve E to A waves increased significantly. We observed that octreotide treatment caused a significant decrease in interventricular septum thickness and subaortic pressure gradient. Before and after therapy left ventricular enddiastolic diameter, left ventricular endsystolic diameter, ejection fraction and fractional shortening were not changed. No adverse effect was observed during the therapy. According to our results, octreotide has some beneficial effects on HOCM and it seems to be a new therapeutic approach for HOCM.

Background: Multimodal large language models (LLMs) are increasingly being explored as clinical support tools, yet their capacity for orthodontic biomechanical reasoning has not been systematically evaluated. This retrospective study assessed their ability to analyze treatment mechanics and explored their potential role in supporting orthodontic decision-making. Methods: Five publicly available models (GPT-o3, Claude 3.7 Sonnet, Gemini 2.5 Pro, GPT-4.0, and Grok) analyzed 56 standardized intraoral photographs illustrating a diverse range of active orthodontic force systems commonly encountered in clinical practice. Three experienced orthodontists independently scored the outputs across four domains—observation, interpretation, biomechanics, and confidence—using a 5-point scale. Inter-rater agreement and consistency were assessed, and statistical comparisons were made between models. Results: GPT-o3 achieved the highest composite score (3.34/5.00; 66.8%), significantly outperforming all other models. The performance ranking was followed by Claude (57.8%), Gemini (52.6%), GPT-4.0 (48.8%), and Grok (38.8%). Inter-rater reliability among the expert evaluators was excellent, with ICC values ranging from 0.786 (Confidence Evaluation) to 0.802 (Observation). Model self-reported confidence showed poor calibration against expert-rated output quality. Conclusions: Multimodal LLMs show emerging potential for assisting orthodontic biomechanical assessment. With expert-guided validation, these models may contribute meaningfully to clinical decision support across diverse biomechanical scenarios encountered in routine orthodontic care.