Purpose: This study aimed to elucidate the factors that affect the dynamics of blood D-dimer in ovarian hyperstimulation syndrome (OHSS).
Methods: We retrospectively reviewed medical records from two hospitals and extracted data obtained during assisted reproductive technology and OHSS treatment. Blood D-dimer levels during hospitalization were plotted against body weight. Other factors possibly related to blood D-dimer levels were also analyzed.
Results: The analysis included 10 patients with OHSS admitted between January 2013 and June 2023. In all patients, blood D-dimer levels increased significantly when they convalesced from OHSS and lost weight. None of the patients showed clinical signs of thrombosis, which was confirmed using imaging tests in 8 of 10 patients. Two patients underwent cell-free and concentrated ascites reinfusion therapy (CART), and their blood D-dimer levels increased dramatically after the procedure.
Conclusion: Weight change and CART are associated with blood D-dimer dynamics in OHSS. Our results show that elevated blood D-dimer levels in patients with OHSS do not always represent the presence of thrombosis. Reinfusion of pooled D-dimer in ascites may explain the D-dimer surge during the recovery phase or after CART in these patients. Our study provides new perspectives on the clinical implications of D-dimer during OHSS.
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http://dx.doi.org/10.1002/rmb2.12563 | DOI Listing |
Front Neurosci
January 2025
Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.
Introduction: Delirium, frequently experienced by ischemic stroke patients, is one of the most common neuropsychiatric syndromes reported in the Intensive Care Unit (ICU). Stroke patients with delirium have a high mortality rate and lengthy hospitalization. For these reasons, early diagnosis of delirium in the ICU is critical for better patient prognosis.
View Article and Find Full Text PDFZhongguo Gu Shang
January 2025
Department of Orthopaedics, Xuzhou Central Hospital, Xuzhou 221009, Jiangsu, China.
Objective: To investigate the clinical utility of novel of new hematological markers in the preoperative diagnosis of periprosthetic joint infection (PJI).
Methods: A retrospective analysis was conducted on a total of 149 patients who underwent revision of total hip arthroplasty (THA) or total knee arthroplasty (TKA) at a single center between January 2016 and June 2022, including 63 males and 86 females, aged from 47 to 93 years old with an average of (69.5±11.
Shock
January 2025
Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 599 Taylor Road, Room 209, Piscataway, NJ, USA 08854.
Introduction: Coagulopathy following traumatic injury impairs stable blood clot formation and exacerbates mortality from hemorrhage. Understanding how these alterations impact blood clot stability is critical to improving resuscitation. Furthermore, the incorporation of machine learning algorithms to assess clinical markers, coagulation assays and biochemical assays allows us to define the contributions of these factors to mortality.
View Article and Find Full Text PDFMed Klin Intensivmed Notfmed
January 2025
University Heart Center Lübeck, Department of Cardiology, Angiology and Intensive Care Medicine, University of Lübeck, German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Ratzeburger Allee 160, 23538, Lübeck, Germany.
Background: Pulmonary arterial embolism (PE) is not well characterized in elderly patients. In addition, unnecessary computed tomography pulmonary angiography (CTPA) examinations are often performed within this patient group, especially if the pretest probability is low.
Objective: To identify differences in clinical presentation in patients aged ≥80 years compared to patients <80 years and the effect of a BGA-optimized pretest probability to reduce unnecessary CTPAs according to age category.
Front Med (Lausanne)
January 2025
Hepatobiliary Pancreatic Surgery Department, Huadu District People's Hospital of Guangzhou, Guangzhou, China.
Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population. This study compared the performance of traditional logistic regression and machine learning models in predicting adult sepsis mortality.
Objective: To develop an optimum model for predicting the mortality of adult sepsis patients based on comparing traditional logistic regression and machine learning methodology.
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