Søgeresultater - Clinical algorithms
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Comorbidities in clinical practice. Algorithms for diagnostics and treatment
Udgivet 2019-03-01Få fuldtekst.
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Vasospastic angina: pathophysiology and clinical significance
Udgivet 2020-03-01Få fuldtekstThe review discusses an analysis of the literature on various aspects of the pathogenesis, diagnosis and treatment of vasospastic angina (VA). Data on the prevalence of coronary artery spasm (CAS) in various populations, as well as risk factors and triggers, are presented. We considered pathophysiol...
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Does an Algorithm Replace Clinical and Sports Judgment in Exercise Prescription?
Udgivet 2025-06-01Få fuldtekstArtificial intelligence presents itself as a facilitator of connections, but it is not, in fact, a facilitator of specialized knowledge spaces. ChatGPT has democratized information, allowing general recommendations to be applied in communities with limited access. Its effectiveness depends on the tr...
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The clinical and laboratory algorithm for the diagnosis of acute cytomegalovirus infection in children
Udgivet 2019-12-01Få fuldtekstThe aim. of the study is to optimize the Iaboratory diagnosis of cytomegaIovirus infection in chiIdren by finding cIinicaI and Iaboratory predictors corresponding to the acute stage of infection.MateriaIs and methods. The resuIts of 65 chiIdren age from 1 to 3 years outpatient of with cytomegaIoviru...
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Contemporary algorithms for diagnosing obstructive coronary artery disease in real clinical practice
Udgivet 2024-07-01Fag: Få fuldtekstBackground. Despite the high evidence level of the currently existing international recommendations on stable coronary heart disease (CHD) and chronic coronary syndrome, their implementation in domestic clinical practice is insufficient.The aim of the work. To analyze the choice of diagnostic tactic...
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Prognostic algorithms for the progression of chronic heart failure depending on the clinical phenotype
Udgivet 2019-06-01“...To develop a mathematical equation (algorithm) to predict the development of chronic heart failure (CHF) for three years, depending on the clinical phenotype.Material and methods. ...”Aim. To develop a mathematical equation (algorithm) to predict the development of chronic heart failure (CHF) for three years, depending on the clinical phenotype.Material and methods. Three hundred forty five patients with CHF with a different left ventricular ejection fraction (preserved, mean, lo...
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How to identify a patient with autoinflammatory syndrome: Clinical and diagnostic algorithms
Udgivet 2013-10-01“...A clinical diagnostic algorithm is presented, which can be used to detect patients with AIS and to determine indications to and the time of molecular genetic typing, and to choose priority genes....”Autoinflammatory syndromes (AISs) are a group of predominantly hereditary diseases associated with the spontaneous uncontrolled production of proinflammatory cytokines. Most diseases are known to have molecular mechanisms and an inheritance pattern. The paper describes major AISs, such as familial M...
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Proposed Algorithm for the Diagnosis and Management of Diabetic Gastroparesis in the Indian Clinical Setting
Udgivet 2025-05-01“...It offers a systematic approach tailored to Indian clinical settings, emphasising a comprehensive evaluation encompassing medical history, clinical examination, and laboratory investigations for diagnosing DGP. ...”Diabetic gastroparesis (DGP) is a microvascular complication of diabetes, characterised by delayed gastric emptying and cardinal symptoms such as nausea, vomiting, early satiety, post-meal discomfort, bloating, and appetite loss. Diagnosis relies on identifying these symptoms and excluding obstructi...
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Algorithm of management of patients with acute cholestatic hepatitis (Clinical case presentation)
Udgivet 2011-12-01“...To show diagnostic and treatment algorithm for patients with cholestatic syndrome by the example of clinical case.Features of clinical case. ...”The aim of publication. To show diagnostic and treatment algorithm for patients with cholestatic syndrome by the example of clinical case.Features of clinical case. The patient self treated for a long time by various infusions and medicinal herbs (including the Chinese tea; celandine) with no medica...
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Clinical and immunological biomarkers in hypereosinophilic syndrome: the second step after diagnostic algorithms
Udgivet 2025-07-01Få fuldtekstBackgroundIdiopathic hypereosinophilic syndrome currently represents a major unmet need for all medical specialties dealing with this disease. Markers capable of characterising the wide variability of its clinical presentation are currently lacking.ObjectiveThis study aims to evaluate a panel of pos...
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Russian Trial ALGORITHM: Implementation of Combined Antihypertensive and Hypolipidemic Treatment for Clinical Efficacy Achievement in Routine Clinical Practice
Udgivet 2020-01-01Få fuldtekstAim. To study the clinical outcomes (achievement of target blood pressure [BP]) and tolerability of antihypertensive and hypolipidemic therapy with fixed combinations of indapamide/perindopril, amlodipine/perindopril, amlodipine/indapamide/perindopril and rosuvastatin in patients with hypertension a...
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False Thrombocytopenia Phenomenon. Algorithm for Diagnostic Problem Solution and Description of Clinical Case
Udgivet 2023-08-01Få fuldtekstЛабораторные методы исследования активно применяются клиницистами для уточнения и установления диагноза, но часто возникают случаи, которые сбивают с толку практикующих врачей и заставляют проводить широкий дифференциально диагностический поиск. Выявление тромбоцитопении в общем анализе крови требуе...
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Diagnostic algorithms in patients with chronic coronary syndromes — what does clinical practice show?
Udgivet 2023-09-01Fag: Få fuldtekstThe European Society of Cardiology (ESC) 2019 guidelines propose a novel diagnostic algorithm for examining stable patients with suspected coronary artery disease (CAD). In retrospective analysis of previous studies, a new pretest probability scale was validated and a method for assessing clinical p...
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Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss
Udgivet 2025-07-01“...Three methods were used for screening 100+ clinical indicators, and five machine learning algorithms were used to develop and evaluate diagnostic models based on the most relevant indicators.ResultsMultivariate analysis revealed significant differences in several factors between the patients and the control group. 25-hydroxy vitamin D3 (25OHVD3) was the factor exhibiting the most prominent difference, and most patients presented deficiency in the levels of this vitamin. 25OHVD3 is associated with blood lipids, hormones, thyroid function, human papillomavirus infection, hepatitis B infection, sedimentation rate, renal function, coagulation function, and amino acids in patients with infertility. ...”Background and objectivesDiagnosis and treatment of infertility and pregnancy loss are complicated by various factors. We aimed to develop a simpler, more efficient system for diagnosing infertility and pregnancy loss.MethodsThis study included 333 female patients with infertility and 319 female pat...
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Clinical characteristics of bronchopulmonary dysplasia and the risk of sepsis onset prediction via machine learning models
Udgivet 2025-06-01“...We subsequently utilized ten machine learning (ML) algorithms and used clinical features to acquire models to predict BPD with sepsis. ...”Bronchopulmonary dysplasia (BPD), also known as chronic lung disease, is the most common cause of respiratory morbidity in preterm infants. Sepsis plays a significant role in the pathogenesis of BPD, and the systemic inflammatory response caused by sepsis is associated with lung development, leading...
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Clinical Algorithms and the Legacy of Race-Based Correction: Historical Errors, Contemporary Revisions and Equity-Oriented Methodologies for Epidemiologists
Udgivet 2025-07-01Fag: “...Clinical algorithms...”Laura J Horsfall, Paulina Bondaronek, Julia Ive, Shoba Poduval Institute of Health Informatics, University College London, London, UKCorrespondence: Laura J Horsfall, Email laura.horsfall@ucl.ac.ukAbstract: Clinical algorithms are widely used tools for predicting, diagnosing, and managing diseases....
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Reconsidering the use of race, sex, and age in clinical algorithms to address bias in practice: A discussion paper
Udgivet 2025-12-01Fag: “...Clinical decision-making...”Clinical algorithms are commonly used as decision-support tools, incorporating patient-specific characteristics to predict health outcomes. Risk calculators are clinical algorithms particularly suited for resource allocation based on risk estimation. Although these calculators typically use physiolo...
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Barriers and enablers of using a clinical decision support algorithm to consult sick children at primary health facilities: A qualitative study from Uttar Pradesh, India
Udgivet 2025-07-01Fag: “...Clinical Decision Support Algorithms...”Introduction: In Indian public health system, adherence to Integrated Management of Childhood Illness (IMNCI) guidelines is low due to inadequate capacity building, high workload and shortage of healthcare providers (HCPs). Objective was to explore barriers and enablers experienced by HCPs using a d...
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Takotsubo cardiomyopathy. Literature review: clinical performance, diagnostic algorithm, treatment, prognosis. Part II
Udgivet 2022-09-01“...Up-to-date data on the problem of takotsubo cardiomyopathy, including data on the clinical manifestations, diagnostic algorithm and treatment approaches, as well as the prognosis of possible complications is presented in review....”Up-to-date data on the problem of takotsubo cardiomyopathy, including data on the clinical manifestations, diagnostic algorithm and treatment approaches, as well as the prognosis of possible complications is presented in review.
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Proposal for Using AI to Assess Clinical Data Integrity and Generate Metadata: Algorithm Development and Validation
Udgivet 2025-06-01“...Quality assurance of clinical data, mainly through predictive quality algorithms and machine learning, is essential to mitigate risks such as misdiagnosis, inappropriate treatment, bias, and compromised patient safety. ...”Abstract BackgroundEvidence-based medicine combines scientific research, clinical expertise, and patient preferences to enhance the patient outcomes and improve health care quality. Clinical data are crucial in aligning medical decisions with evidence-based practices, whether...
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