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| http://dx.doi.org/10.1182/blood.2021012589 | DOI Listing |
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Improving postoperative outcomes in patients with pancreatic cancer: Inflammatory and nutritional biomarkers.
World J Clin Oncol
January 2025
Department of Biochemistry, School of Medicine, College of Medicine, China Medical University, Taichung 404328, Taiwan.
This editorial assesses the prognostic value of preoperative inflammatory and nutritional biomarkers in patients undergoing surgical resection for pancreatic cancer. Lu evaluated the ability of seven biomarkers to predict postoperative recovery and long-term outcomes. These biomarkers were albumin-to-globulin ratio, prognostic nutritional index (PNI), systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, nutritional risk index, and geriatric nutritional risk index.
View Article and Find Full Text PDFPrognostic impact of inflammatory and nutritional biomarkers in pancreatic cancer.
World J Clin Oncol
January 2025
Department of Radiation Oncology, GenesisCare-San Francisco de Asís University Hospital, Madrid 28002, Spain.
Pancreatic cancer is usually associated with a poor prognosis. Surgery is the main curative treatment but pancreatic operations are aggressive and new tools that help clinicians to predict surgical and prognostic outcomes are necessary. Lu recently published a retrospective, single centre cohort study evaluating the impact of seven nutritional and inflammatory markers in pancreatic cancer surgical patients: The albumin-to-globulin ratio, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), nutritional risk index, and the geriatric nutritional risk index.
View Article and Find Full Text PDFCorrelation Between Inflammatory Markers and Pathogenic Bacteria in Children's Winter Respiratory Infections in Xinjiang.
Int J Gen Med
January 2025
Department of Respiratory and Critical Care Medical Department Infectious Diseases Ward, The Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University, Urumqi, Xinjiang, People's Republic of China.
Background: This study examines the distribution characteristics of pathogenic bacteria in respiratory infections and their relationship with inflammatory markers to guide clinical drug use.
Methods: We selected 120 patients with lower respiratory tract infection in the electronic medical record system of Xinjiang Provincial People's Hospital from March 2019 to March 2023 for a case-control study. Using Indirect Immunofluorescence Antibody test(IFA), blood routine, C-reactive Protein (CRP), and High-sensitivity C-reactive Protein(hsCRP), we detected nine respiratory pathogens (Respiratory syncytial virus; Influenza A virus; Influenza B virus; Parainfluenza virus; Adenovirus; Mycoplasma pneumoniae; Chlamydia pneumoniae; Legionella pneumophila type 1; Rickettsia Q) in all patients and analyzed their distribution and correlation.
What is the origin of the normal ranges of blood cell counts? An evolutionary perspective.
EJHaem
February 2025
Centre International de Recherche en Infectiologie (CIRI, INSERM U1111, CNRS UMR 5308, École Normale supérieure de Lyon) Lymphoma ImmunoBiology team Faculté de Médecine Lyon sud Université Claude Bernard Lyon 1 Lyon France.
Background: The normal values of the complete blood count are part of the foundational medical knowledge that is seldom questioned due to their well-established nature. These normal values are critical for optimal physiological function while minimizing the harmful consequences of an excessive number of blood cells. Thus, they represent an evolutionary trade-off likely shaped by natural selection if they significantly influence individual fitness and exhibit heritability.
View Article and Find Full Text PDFPredictive Laboratory Markers for Gastrointestinal Complications in Children with Henoch-Schönlein Purpura.
J Multidiscip Healthc
January 2025
Department of Rheumatology and Immunology, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science &Technology, Wuhan, 430016, People's Republic of China.
Background: Henoch-Schönlein Purpura (HSP) is a common systemic vasculitis in children that often involves the gastrointestinal system (GIS). Identifying reliable predictive markers for GIS complications is crucial for early intervention and improved patient outcomes.
Objective: This study aims to identify laboratory markers predictive of GIS complications in children with HSP using a machine learning approach.
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