Objective: To investigate whether the recommendations for the follow-up after a positive cervical smear test, made within the Dutch national screening programme on cervical cancer, are followed in practice.
Design: Descriptive.
Setting: The Rotterdam Municipal Health Services Area.
Method: All cytological and clinical-histological findings on women who had a Pap smear of at least Pap class IIIA in the period 1989-1991, were collected from the Pathological Anatomical National Automised Archives (PALGA). Per smear test result, the cervix-cytological and histological examinations that took place after the screening programme were arranged in order of occurrence.
Results: 61% of the women with Pap class IIIA had been followed according to the recommendations, in 12% no follow-up had been done. Repeat cytology was often done much later than after three months as recommended. After Pap class IIIB, IV or V smear test outcome the recommendations were followed in respectively over half, about three-quarters, and all cases. In 9% of women with Pap class IIIB or IV, no follow-up was recorded in the PALGA data base.
Conclusion: Often, the recommendations for follow-up after a positive smear were followed poorly. Further research into the problems in the follow-up route is necessary.
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J Cardiovasc Dev Dis
January 2025
Department of Cardiology, University Hospital Galway, Saolta University Healthcare Group, Newcastle Road, H91YR71 Galway, Ireland.
Hospitalisation for acute decompensated heart failure (HF) portends a poor prognosis. Fluid retention manifesting in dyspnoea and oedema are important clinical features of decompensated heart failure and drive hospital admissions. Intracardiac and pulmonary artery pressure (PAP) monitoring can help predict heart failure decompensation, as changes in these haemodynamics occur before clinical congestion manifests.
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December 2024
Decisions LAB, Department of Law, Economics and Human Sciences, University Mediterranea of Reggio Calabria, Via dei Bianchi, 2, 89131, Reggio Calabria, Italy.
Cervical cancer is one of the deadly diseases that affects women, which requires periodic examinations to identify and treat any cancerous tumors at a preliminary stage. The most prevalent examination tool for cervical cancer prompt identification is the cervical smear (Pap smear) testing; however, due to human negligence, this examination method has an elevated probability of negative findings. Cervical cancer classification using machine learning (ML) and deep learning (DL) has been extensively studied to enhance the conventional diagnostic process.
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Arbor Research Collaborative for Health Ann Arbor MI USA.
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Department of Internal Medicine, Institute of Health, Jimma University, Jimma, Ethiopia.
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September 2024
Northeastern University, Department of Electrical and Computer Engineering, Boston, MA, USA.
This paper addresses the inference challenges associated with a class of hidden Markov models with binary state variables, known as partially observed Boolean dynamical systems (POBDS). POBDS have demonstrated remarkable success in modeling the ON and OFF dynamics of genes, microbes, and bacteria in systems biology, as well as in network security to represent the propagation of attacks among interconnected elements. Despite existing optimal and approximate inference solutions for POBDS, scalability remains a significant issue due to the computational cost associated with likelihood evaluations and the exploration of extensive parameter spaces.
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