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2.
Am J Med ; 2024 Jun 11.
Artigo em Inglês | MEDLINE | ID: mdl-38871205

RESUMO

BACKGROUND: Validated syncope risk scores were aimed to predict a cardiac etiology and are mainly used in the decision of hospital admission. Whether these scores could also predict the outcomes of inpatient cardiac evaluation is unknown and was the subject of our study. METHODS: This was an observational study including consecutive patients admitted for syncope evaluation. All patients completed prolonged electrocardiogram monitoring and an echocardiography before discharge. The area under the receiver-operating characteristic curve (AUC) was used to evaluate the ability of validated risk scores to predict positive inpatient findings. Subsequently, a multivariate regression was performed to identify independent predictors for positive cardiac evaluation, which were then incorporated into the best predictive risk scores. RESULTS: Three hundred ninety-seven patients were included, 56 (14%) with a positive inpatient cardiac evaluation. The Osservatorio Epidemiologico sulla Sincope Lazio and Canadian Syncope Risk Score achieved the largest AUC (0.701, 95% confidence interval [CI] 0.63-0.77 and 0.694, 95% CI 0.62-0.77, respectively). Yet, all scores provided relatively high sensitivity with low specificity. Multivariate regression revealed age ≥75 (adjusted odds ratio 3.50, 95% CI 1.5-7.9) and abnormal cardiac auscultation (adjusted odds ratio 4.79, 95% CI 2.5-9.1) to be independent predictors. Incorporating these factors led to a significantly higher prediction ability of the Osservatorio Epidemiologico sulla Sincope Lazio (AUC of 0.787, P < .01) and Canadian Syncope Risk Score (AUC 0.778, P < .01) modified scores. CONCLUSIONS: Current syncope risk scores provide limited prediction ability for the outcomes of inpatient cardiac syncope work-up. One should specifically consider age > 75 years and either cardiac murmur or irregular heart rate on examination very significant in implying a cardiac etiology for syncope. Although these factors may be obvious, current risk scores can be interpreted in such a fashion that ignores the importance of findings extracted from a good history and physical examination.

3.
J Nephrol ; 2023 Nov 02.
Artigo em Inglês | MEDLINE | ID: mdl-37917333

RESUMO

INTRODUCTION: Acute kidney injury (AKI) is a clinically relevant and common complication among patients with acute coronary syndrome. Neutrophil gelatinase-associated lipocalin (NGAL), secreted from different cells including renal tubules, has been widely studied as an early marker for kidney injury. However, chronic kidney disease (CKD) could impact NGAL levels and alter their predictive performance. Some studies attempted to address this issue by setting different cutoff values for patients with CKD, with limited success to date. Our aim was to evaluate a novel estimated glomerular filtration rate (eGFR)-adjusted "indexed NGAL" and its ability to predict in-hospital AKI among patients with ST elevation myocardial infarction. METHODS: We performed a prospective, observational, single center study involving patients with ST elevation myocardial infarction admitted to the coronary intensive care unit. Serum samples for baseline NGAL were collected within 24 h following hospital admission. The eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. In-hospital AKI was determined as occurring after ≥ 24 h from admission. To perform an individualized adjustment, we used the result of 24 h NGAL divided by the eGFR measured upon admission to the hospital (Indexed-NGAL; I-NGAL). RESULTS: Our cohort includes 311 patients, of whom 123 (40%) had CKD, and 66 (21%) suffered in-hospital AKI. NGAL levels as well as I-NGAL levels were significantly higher in patients with AKI (136 vs. 86, p < 0.01 and 3.13 VS. 1.06, p < 0.01, respectively). Multivariate analysis revealed I-NGAL to be independently associated with AKI (OR 1.34 (1.10-1.58), p < 0.01). I-NGAL had a higher predictive ability than simple NGAL results (AUC-ROC of 0.858 vs. 0.778, p < 0.001). CONCLUSION: Adjusting NGAL values according to eGFR yields a new indexed NGAL value that enables better prediction of AKI regardless of baseline kidney function.

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