{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T23:01:40Z","timestamp":1790031700148,"version":"4.0.1"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Colorectal cancer (CRC) and cardiovascular disease (CVD) share overlapping molecular pathogenic axes\u2014including chronic systemic inflammation, immune dysregulation, metabolic reprogramming, and cellular senescence\u2014that collectively amplify perioperative neurological vulnerability in elderly patients. Postoperative delirium (POD), the most prevalent acute neuropsychiatric complication following major oncological surgery, emerges at the intersection of these shared pathogenic pathways: tumor-driven neuroinflammation, anesthesia-induced cerebral hypoperfusion, cardio-metabolic derangements, and frailty-associated multi-system reserve failure collectively prime the aging brain for acute cognitive disruption. Despite this mechanistic convergence, clinically actionable risk stratification tools anchored in this cardio-oncological molecular framework remain absent.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To construct and validate a precision nomogram for POD prediction in elderly CRC patients by integrating preoperative frailty phenotyping, cardio-metabolic biomarkers, and anesthesia-related intraoperative indicators, positioning each predictor within the shared CRC-CVD molecular landscape and translational omics evidence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A retrospective cohort of 283 elderly patients (\u226565 years) undergoing elective radical resection for CRC (January 2021\u2013June 2024) was analyzed. Preoperative frailty was assessed using the Fried Frailty Phenotype across five physiological dimensions. POD was diagnosed by the Confusion Assessment Method (CAM). Data encompassed demographic characteristics, cardio-metabolic comorbidities, inflammatory and nutritional biomarkers, frailty dimensions, and anesthesia-related indicators. Multivariate logistic regression identified independent predictors, and a nomogram was constructed using the rms package (R 4.3.0). Model performance was evaluated by C-index, AUC, Hosmer\u2013Lemeshow test, calibration curves, and decision curve analysis (DCA), with Bootstrap internal validation (1,000 iterations). Each predictor is mechanistically contextualized within existing multi-omics, proteomics, and translational CRC-CVD molecular biology evidence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>POD developed in 53\/283 patients (18.7%). Seven independent predictors were identified: advanced age (OR = 1.125, 95%CI: 1.058\u20131.196), low education level (OR = 2.341, 95%CI: 1.287\u20134.259), frailty score \u22653 items (OR = 4.862, 95%CI: 2.154\u201310.975), intraoperative hypotension (OR = 3.524, 95%CI: 1.723\u20137.209), intraoperative hypothermia (OR = 3.187, 95%CI: 1.542\u20136.589), anesthesia duration \u2265200\u00a0min (OR = 2.678, 95%CI: 1.328\u20135.400), and albumin &amp;lt;35\u00a0g\/L (OR = 2.814, 95%CI: 1.245\u20136.358). The nomogram achieved C-index 0.842 (95%CI: 0.792\u20130.892), Bootstrap-corrected C-index 0.835, AUC 0.842 (95%CI: 0.791\u20130.893), sensitivity 79.2%, specificity 82.6%, and NPV 92.7%. DCA demonstrated robust net clinical benefit across threshold probabilities of 0.10\u20130.70.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This nomogram operationalizes the convergent CRC-CVD molecular pathogenic landscape into a clinically deployable perioperative precision medicine tool. Its predictors\u2014spanning neuroinflammatory priming, vascular homeostatic failure, metabolic-nutritional derangement, and phenotypic frailty\u2014map directly onto shared molecular axes of CRC and CVD, validating the cardio-oncological framework as a foundation for POD risk stratification. Future multi-omics integration\u2014incorporating inflammatory proteomics, metabolomic signatures, and machine-learning models\u2014will further advance individualized perioperative management in elderly CRC patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fgene.2026.1902646","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T22:10:20Z","timestamp":1790028620000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Shared molecular mechanisms between colorectal cancer and cardiovascular disease drive perioperative neurological vulnerability"],"prefix":"10.3389","volume":"17","author":[{"given":"Ling","family":"Jiang","sequence":"first","affiliation":[{"name":"Department of Anesthesiology, Chongqing Jiangjin Central Hospital","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingqian","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology Surgery, Ezhou Central Hospital","place":["Ezhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology Surgery, Zibo Central Hospital","place":["Zibo, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology Head and Neck Surgery, Chongqing Jiangjin Central Hospital","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liyang","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Huai\u2019an Hospital of Huai\u2019an City (Huai\u2019an Clinical Medical College of Jiangsu University)","place":["Huai\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,22]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1161\/STROKEAHA.122.040578","article-title":"Blood-brain barrier dysfunction in normal aging and neurodegeneration","volume":"54","author":"Andjelkovic","year":"2023","journal-title":"Stroke"},{"key":"B2","doi-asserted-by":"publisher","first-page":"3000605241274553","DOI":"10.1177\/03000605241274553","article-title":"Preoperative frailty and postoperative complications after non-cardiac surgery: a systematic review","volume":"52","author":"Becerra-Bola\u00f1os","year":"2024","journal-title":"J. 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