Metabolic Syndrome Predicts Worse Perioperative Outcomes in Patients Treated With Partial Nephrectomy for Renal Cell Carcinoma
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články
PubMed
32151650
DOI
10.1016/j.urology.2020.02.019
PII: S0090-4295(20)30255-7
Knihovny.cz E-zdroje
- MeSH
- hodnocení rizik metody MeSH
- hypertenze diagnóza MeSH
- index tělesné hmotnosti MeSH
- karcinom z renálních buněk * epidemiologie patologie chirurgie MeSH
- komorbidita MeSH
- krevní glukóza analýza MeSH
- lidé středního věku MeSH
- lidé MeSH
- metabolický syndrom * krev diagnóza epidemiologie patofyziologie MeSH
- nádory ledvin * epidemiologie patologie chirurgie MeSH
- nefrektomie * škodlivé účinky metody MeSH
- pooperační komplikace * klasifikace epidemiologie terapie MeSH
- prediktivní hodnota testů MeSH
- prognóza MeSH
- rizikové faktory MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Itálie epidemiologie MeSH
- Názvy látek
- krevní glukóza MeSH
OBJECTIVE: To test the association between metabolic syndrome (MetS) and its components (high blood pressure, body mass index [BMI] ≥ 30, altered fasting glucose, low high-density lipoprotein cholesterol and high triglycerides) on perioperative outcomes after partial nephrectomy (PN). METHODS: Within the National Inpatient Sample database (2000-2015) we identified all PN patients. First, temporal trends of MetS were reported. Second, the effect of MetS components was tested in multivariable logistic regression models predicting overall and specific perioperative complications. Third, we tested for dose-response from the concomitant effect of multiple MetS components. All models were weighted and adjusted for clustering, as well as all available patient and hospital characteristics. RESULTS: Of 25,875 patients: (1) 59.3% had high blood pressure, (2) 14.7% had BMI ≥ 30, (3) 21.7% had altered fasting glucose, (4) 20.2% had high triglycerides, and (5) <0.01% had low high-density lipoprotein cholesterol. One vs 2 vs 3 vs 4 MetS components were recorded in 34.9% vs 22.9% vs 8.9% vs 2.2% patients. Of all, 11.1% exhibited ≥ 3 components and qualified for MetS. The rates of MetS increased over time (estimated annual percentage changes: +12.0%;P <.001). The 4 tested MetS components (high blood pressure, BMI ≥ 30, altered fasting glucose, and high triglycerides) achieved independent predictor status in multivariable models predicting overall, cardiac, miscellaneous medical, vascular, and respiratory complications, as well as transfusions. Moreover, a statistically significant dose-response was confirmed for the same endpoints. CONCLUSION: MetS and its components consistently and strongly predict perioperative complications after PN. Moreover, the strength of the effect was directly proportional to the number of MetS components exhibited by each individual patient, even if formal MetS diagnosis of ≥ 3 components has not been met.
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