The gut–kidney axis in chronic kidney disease: mechanisms, microbial metabolites, and microbiome-targeted therapeutics
Sami Alobaidi · 2025 · Frontiers in Medicine
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Chronic kidney disease (CKD) remains a major global health issue, affecting millions and presenting persistent diagnostic and therapeutic challenges. Conventional biomarkers such as serum creatinine and estimated glomerular filtration rate have well-recognized limitations, underscoring the need for novel diagnostic tools and interventions. Emerging evidence highlights the gut-kidney axis as a central contributor to CKD pathogenesis, shaped by microbial dysbiosis and altered metabolite production. Harmful metabolites such as indoxyl sulfate, p-cresyl sulfate, and trimethylamine-N-oxide promote
Abstract by Sami Alobaidi, Frontiers in Medicine (2025) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Power and Predictive Accuracy of Polygenic Risk Scores
Negative / Null Result ReportLocoregional Recurrence After Sentinel Lymph Node Dissection With or Without Axillary Dissection in Patients With Sentinel Lymph Node Metastases
Negative / Null Result ReportCritical aspects of using bacterial cell viability assays with the fluorophores SYTO9 and propidium iodide
Negative / Null Result ReportAlpelisib plus fulvestrant for PIK3CA-mutated, hormone receptor-positive, human epidermal growth factor receptor-2–negative advanced breast cancer: final overall survival results from SOLAR-1
Negative / Null Result ReportA randomized placebo-controlled trial of idebenone in Leber’s hereditary optic neuropathy
Negative / Null Result ReportThe CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.3389/fmed.2025.1675458
