Hybrid Cardiac Imaging for Clinical Decision-Making: From Diagnosis to Prognosis

$39.99

Performing any diagnostic test in medicine is always a matter of trying to get the condition of the patient diagnosed properly with the least effort, exposure, discomfort and at the same time with the lowest possible error probability. Pre-test probability is helpful but often imprecise, effectively overestimating the patient's risk profile. In a broader prevention objective, the phases of a disease, its onset, progression, and complications must be taken into account. The negative predictive value, which is so important, has in turn its main limitation in identifying the healthy patient, that is, the one who does not belong to any cluster of patients in which we would act in terms of prevention. In coronary syndromes, the goal is instead to evaluate coronary heart disease, from mild to more extensive and significant forms. For this purpose, it is necessary to use parameters that investigate different and complementary aspects: stenosis, ischemia, the morphology ofthe atherosclerotic plaque, metabolic processes, in particular vitality and apoptosis, the presence of inflammatory processes. The possibility, already present thanks to Hybrid Imaging, of ‘joining’ exams that study different aspects, will allow the patient to be increasingly characterized not only from a diagnostic point of view but also from a prognostic and personalized therapeutic choice. Hybrid Cardiac Imaging for Clinical Decision-Making: From Diagnosis to Prognosis and published by Springer. ISBNs for Hybrid Cardiac Imaging for Clinical Decision-Making are 9783030993917, 3030993914 and the print ISBNs are 9783030993900, 3030993906.

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We accept returns and exchanges within 30 days from the date your order is delivered. Items must be unused, in the original condition, and accompanied by the original packaging and receipt or proof of purchase.

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Contact our customer support at contact@zetlly.com with your order number and reason for return or exchange.
Our team will respond within 24 hours to provide detailed instructions, including the specific Return Address for your shipment.
Package your item securely and include all original packaging and proof of purchase.

Return shipments should be sent to: Blanq LLC 1201 South Hope Street Apt 2413, Los Angeles, CA 90015, USA

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Items returned without prior authorization or not meeting the above conditions may not qualify for a refund or exchange.

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Performing any diagnostic test in medicine is always a matter of trying to get the condition of the patient diagnosed properly with the least effort, exposure, discomfort and at the same time with the lowest possible error probability. Pre-test probability is helpful but often imprecise, effectively overestimating the patient’s risk profile. In a broader prevention objective, the phases of a disease, its onset, progression, and complications must be taken into account. The negative predictive value, which is so important, has in turn its main limitation in identifying the healthy patient, that is, the one who does not belong to any cluster of patients in which we would act in terms of prevention. In coronary syndromes, the goal is instead to evaluate coronary heart disease, from mild to more extensive and significant forms. For this purpose, it is necessary to use parameters that investigate different and complementary aspects: stenosis, ischemia, the morphology ofthe atherosclerotic plaque, metabolic processes, in particular vitality and apoptosis, the presence of inflammatory processes. The possibility, already present thanks to Hybrid Imaging, of ‘joining’ exams that study different aspects, will allow the patient to be increasingly characterized not only from a diagnostic point of view but also from a prognostic and personalized therapeutic choice.
Hybrid Cardiac Imaging for Clinical Decision-Making: From Diagnosis to Prognosis and published by Springer. ISBNs for Hybrid Cardiac Imaging for Clinical Decision-Making are 9783030993917, 3030993914 and the print ISBNs are 9783030993900, 3030993906.