Objective: The prognosis for ovarian cancer patients remains poor. A key to maximizing survival rates is early detection and treatment. This requires an accurate prediction of malignancy. Our study seeks to improve the accuracy of prediction by focusing on early subjective assessment of malignancy. We therefore investigated the assessment of patients themselves in comparison to the assessment of physicians.
Methods: One thousand three hundred and thirty patients participated in a prospective and multicenter study in six hospitals in Berlin. Using univariate analysis and multivariate logistic regression models, we measured the accuracy of the early subjective assessment in comparison to the final histological outcome. Moreover, we investigated factors related to the assessment of patients and physicians.
Results: The patients' assessment of malignancy is remarkably accurate. With a positive predictive value of 58%, the majority of patients correctly assessed a pelvic mass as malignant. With more information available, physicians achieved only a slightly more accurate prediction of 63%.
Conclusions: For the first time, our study considered subjective factors in the diagnostic process of pelvic masses. This paper demonstrates that the patients' personal assessment should be taken seriously as it can provide a significant contribution to earlier diagnosis and thus improved therapy and overall prognosis.
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http://dx.doi.org/10.1080/0167482X.2020.1850684 | DOI Listing |
CNS Neurosci Ther
December 2024
Department of Functional Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Background: Patients with disorders of consciousness (DOC) undergoing spinal cord stimulation (SCS) for arousal treatment require an assessment of their conscious state before and after the procedure. This is typically evaluated using behavioral scales (CRS-R), but this method can be influenced by the subjectivity of the physician. Event-related potentials (ERP) and EEG power spectrum are associated with the recovery of consciousness.
View Article and Find Full Text PDFJ Cytol
November 2024
Division of Laboratory Medicine, Steel Memorial Yawata Hospital, Kitakyushu City, Fukuoka, Japan.
Introduction: Urine cytology is a morphological diagnostic test that is, patient-friendly and easy to sample but subjective in morphological evaluation. This study aims to evaluate the effect of combining cell findings to assess urine cytology.
Materials And Methods: Thirty cell findings found in high-grade urothelial carcinoma (HGUC) were selected for morphological abnormalities, each with detailed definitions.
This study examines the efficacy of jaw exercising products for facial contouring. The two individuals used a commercially available jaw exerciser for approximately three months, following the provided instructions. Neither case reported noticeable changes in jaw appearance based on subjective measurements.
View Article and Find Full Text PDFWorld J Gastrointest Surg
December 2024
Department of Critical Care Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, China.
Background: Acute gastrointestinal injury (AGI) is common in intensive care unit (ICU) and worsens the prognosis of critically ill patients. The four-point grading system proposed by the European Society of Intensive Care Medicine is subjective and lacks specificity. Therefore, a more objective method is required to evaluate and determine the grade of gastrointestinal dysfunction in this patient population.
View Article and Find Full Text PDFJ Gynecol Obstet Hum Reprod
December 2024
Endoscopy Unit, Glenfield Hospital, University Hospitals of Leicester, NHS Trust, Leicester, United Kingdom.
In-vitro fertilization (IVF) has been a transformative advancement in assisted reproductive technology. However, success rates remain suboptimal, with only about one-third of cycles resulting in pregnancy and fewer leading to live births. This narrative review explores the potential of artificial intelligence (AI), machine learning (ML), and deep learning (DL) to enhance various stages of the IVF process.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!