This study aims to investigate the association between anemia and early recurrence in endometrial cancer patients. We retrospectively analyzed the data of 473 endometrial cancer patients treated at our hospital from January 2015 to December 2020. Patients were divided into two groups based on their hemoglobin (Hb) level: anemia group (Hb < 12 g/dL) and non-anemia group (Hb ≥12 g/dL). Early recurrence was defined as recurrence within 2 years of diagnosis. Univariate and multivariate logistic regression analyses were used to identify the predictors of early recurrence. The prevalence of anemia was 38.26% (181/473). The incidence of early recurrence was 12.89% (61/473) in the anemia group and 9.24% (38/412) in the non-anemia group ( = 0.004). Univariate analysis showed that anemia was a significant predictor of early recurrence (odds ratio (OR) = 2.27, 95% confidence interval (CI): 1.35-3.80, = 0.003). Multivariate analysis confirmed that anemia was an independent predictor of early recurrence (OR = 2.11, 95% CI: 1.21-3.84, = 0.01). Anemia is an independent predictor of early recurrence in endometrial cancer patients. Patients with endometrial cancer should be screened for anemia and treated if present. Additionally, patients with anemia should be closely monitored for early signs of recurrence and treated aggressively.
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http://dx.doi.org/10.3390/jcm13030794 | DOI Listing |
J Transl Med
January 2025
Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
Small cell neuroendocrine cervical carcinoma is a highly aggressive tumor characterized by early metastasis, a high recurrence rate, and poor prognosis. This study represents the first instance of single-cell sequencing conducted on small cell neuroendocrine carcinoma of the cervix worldwide. Analysis of gene expression regulatory networks revealed that the transcription factor TFF3 drived up-regulation of ELF3.
View Article and Find Full Text PDFCardiovasc Eng Technol
January 2025
Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA.
Purpose: This study explores the use of heart rate variability (HRV) analysis, a noninvasive technique for assessing the autonomic nervous system, by applying nonlinear dynamics and chaos theory to detect chaotic behavior in RR intervals and assess cardiovascular health.
Methods: Employing the "System Analysis of Heart Rate Dynamics" (SADR) program, this research combines chaos analysis with the short-time Fourier transform to assess nonlinear dynamic parameters in HRV. It includes constructing phase portraits in Takens space and calculating measures of chaos to identify deterministic chaos indicators.
Sci Rep
January 2025
Department of Computer Science, Faculty of Computers and Information, Suez University, P. O. Box 43221, Suez, Egypt.
Diabetes is a long-term condition characterized by elevated blood sugar levels. It can lead to a variety of complex disorders such as stroke, renal failure, and heart attack. Diabetes requires the most machine learning help to diagnose diabetes illness at an early stage, as it cannot be treated and adds significant complications to our health-care system.
View Article and Find Full Text PDFHistopathology
January 2025
Department of Pathology, Cork University Hospital, Cork.
Aims: Perineural invasion (PNI) is associated with survival in oral cavity squamous cell carcinoma (OCSCC). There is evidence to suggest that PNI location and extent may be of additional significance. The primary aim of this study was to evaluate the prognostic ability of PNI, including location and extent, in early-stage OCSCC.
View Article and Find Full Text PDFJ Neurosurg Case Lessons
January 2025
Department of Radiology and Biomedical Imaging, University of California, San Francisco, California.
Background: Spinal ependymomas are typically slow-growing tumors with a favorable prognosis. Recently, a new aggressive subtype has emerged with its own distinct histopathological and molecular features characterized by MYCN amplification. However, this subtype of spinal ependymoma is rare, and studies on its imaging characteristics are limited.
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