Background: Despite numerous operative and non-operative treatment modalities, patients with glioblastoma (GBM) have a dismal prognosis. Identifying predictors of survival and recurrence is an essential strategy for guiding treatment decisions, and existing literature demonstrates associations between hematologic data and clinical outcomes in cancer patients. As such, we provide a novel analysis that examines associations between preoperative hematologic data and postoperative outcomes following GBM resection.
Methods: We performed a retrospective analysis of patients who underwent GBM resection from January 2016 to December 2020. Standard demographic and clinical variables were collected, including pre-operative complete blood count (CBC), and inferential analyses were performed to analyze associations between CBC parameters and postoperative outcomes.
Results: One hundred and eighty nine (189) patients met inclusion criteria, with a mean age of 60.7 years. On multivariate regression analysis, controlling for age, gender, and performance status, we observed trends suggesting anemic patients may have longer lengths of stay (t statistic = 3.23, = 0.0015) and higher rates of discharge to inpatient facilities [OR 3.01 (1.09-8.13), = 0.029], though these associations did not reach statistical significance after correction for multiple comparisons (Bonferroni-corrected significance threshold < 0.01).
Conclusion: Preoperative anemia may be a useful pre-operative predictor of postsurgical GBM outcomes. Further study is required to determine whether pre-operative hemoglobin optimization can improve postoperative clinical outcomes, and whether other hematologic and inflammatory markers are predictive of postoperative recovery and functional status.
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http://dx.doi.org/10.3389/fsurg.2024.1466924 | DOI Listing |
Front Surg
January 2025
Saint Luke's Cancer Institute, Saint Luke's Hospital, Kansas, MO, United States.
Background: Despite numerous operative and non-operative treatment modalities, patients with glioblastoma (GBM) have a dismal prognosis. Identifying predictors of survival and recurrence is an essential strategy for guiding treatment decisions, and existing literature demonstrates associations between hematologic data and clinical outcomes in cancer patients. As such, we provide a novel analysis that examines associations between preoperative hematologic data and postoperative outcomes following GBM resection.
View Article and Find Full Text PDFData Brief
February 2025
Department of Child Health, Faculty of Medicine, Dr. Cipto Mangunkusumo Hospital, University of Indonesia, Jakarta 10430, Indonesia.
Glycogen storage disease type IV (GSD IV) is a rare disease caused by a defect in glycogen branching enzyme 1 (GBE1), which played a crucial role in glycogen branching. GSD IV occurs once in approximately 1 in every 760,000 to 960,000 live births and is inherited in an autosomal recessive pattern. Early diagnosis of GSD IV is challenging due to non-specific symptoms, such as liver and spleen enlargement, which can overlap with other hematologic and hepatobiliary disorders.
View Article and Find Full Text PDFCureus
December 2024
Pediatrics, King Faisal University, Al-Hofuf, SAU.
Background The incidence of pregnancy-associated diabetes has increased in recent decades, leading to neonatal adverse outcomes like metabolic and hematologic disorders, respiratory distress, cardiac disorders, and neurologic impairment. Macrosomia, a common consequence of diabetes, is influenced by maternal blood glucose levels, impacting adverse neonatal outcomes. Aim The current study aimed to assess the neonatal and maternal outcomes of the infants of diabetic mothers.
View Article and Find Full Text PDFFront Pharmacol
January 2025
Department of Neurological Rehabilitation, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Objective: This study aims to evaluate the association between the white blood cell-to-platelet ratio (WPR) and 28-day all-cause mortality among patients experiencing cardiac arrest.
Methods: Utilizing data from 748 cardiac arrest patients in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) 2.2 database, machine learning algorithms, including the Boruta feature selection method, random forest modeling, and SHAP value analysis, were applied to identify significant prognostic biomarkers.
Front Immunol
January 2025
Adaptive Biotechnologies, Seattle, WA, United States.
Introduction: T cells are involved in the early identification and clearance of viral infections and also support the development of antibodies by B cells. This central role for T cells makes them a desirable target for assessing the immune response to SARS-CoV-2 infection.
Methods: Here, we combined two high-throughput immune profiling methods to create a quantitative picture of the T-cell response to SARS-CoV-2.
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