ArticleObesity surgery2025
Letter to the Editor Regarding "A Nomogram for Prediction of Weight Loss Outcomes After Bariatric Surgery".
Article in Obesity surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
4 authors.
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Abstract
Qiu et al. present a nomogram integrating demographic, anthropometric, and comorbidity variables to predict weight loss outcomes one year after bariatric surgery. While this tool has potential for patient counseling and shared decision-making, its applicability in heterogeneous clinical settings requires careful consideration. In this commentary, we provide insights from a surgical and translational research perspective, emphasizing the need for external validation across diverse ethnic and procedural cohorts, integration with perioperative nutritional and psychological metrics, and the role of dynamic modeling for long-term outcomes. We propose potential expansions, including adaptive machine learning approaches, preoperative metabolic imaging, and postoperative telemonitoring data, to refine prediction accuracy and clinical utility.
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Registered trials
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