Introduction: Approximately one-third of patients hospitalised for an exacerbation of chronic obstructive pulmonary disease (COPD) are readmitted to the hospital within 90 days. It is of interest to identify biomarkers that predict relapse in order to prevent readmission in these patients. In our prospective study of patients admitted for COPD exacerbation, we aimed to analyse whether routine haematological parameters can help predict the three-month readmission risk.
Material And Methods: 106 patients were included, of whom 23 were female (22%). The age (mean ± SD) was 73 ± 10 years, and the forced expiratory volume in 1 second (FEV1) was 44 ± 15%. The haematological parameters were obtained from the first blood test result during admission. The variables were as follows: red cell distribution width, mean platelet volume (MPV), platelet (PLT) count, neutrophil to lymphocyte ratio, PLT to lymphocyte ratio, MPV to PLT ratio, and eosinophil count. Patients were differentiated into two groups for each haematological parameter according to median value, and the percentage of readmissions in each of the groups was recorded.
Results: Twenty-five patients (24%) were readmitted to hospital within three months of discharge. Only the difference in low-MPV and high-MPV patients was significant (37% vs 10%, p = 0.001). The predictive capacity for three-month readmission measured by the area under the curve (AUC) did not show clinically applicable values; the best result was for MPV (AUC 0.64). In the remaining values, the AUC was between 0.52 and 0.55.
Conclusion: Routine haematological parameters proposed as prognostic biomarkers in COPD obtained at the moment of hospital admission were not useful for predicting three-month readmission.
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http://dx.doi.org/10.5603/ARM.a2021.0076 | DOI Listing |
Can Urol Assoc J
October 2024
Department of Urology, Thunder Bay Regional Health Sciences Centre, Northern Ontario School of Medicine, Thunder Bay, ON, Canada.
Eur Spine J
June 2024
Spine Surgery, Department of Orthopaedic Surgery, Rothman Institute, Thomas Jefferson University, 925 Chestnut Street, 5thFloor, Philadelphia, PA, 19107, USA.
Purpose: To determine the impact of poor mental health on patient-reported and surgical outcomes after microdiscectomy.
Methods: Patients ≥ 18 years who underwent a single-level lumbar microdiscectomy from 2014 to 2021 at a single academic institution were retrospectively identified. Patient-reported outcomes (PROMs) were collected at preoperative, three-month, and one-year postoperative time points.
Diagnostics (Basel)
February 2024
Doctoral School Medicine-Pharmacy, "Victor Babes" University of Medicine and Pharmacy, 2 Eftimie Murgu Sq., 300041 Timisoara, Romania.
BMC Cardiovasc Disord
February 2024
Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, North Kargar Ave, Tehran, Iran.
Background: Frailty is proposed as a predictor of outcomes in patients undergoing major surgeries, although data on the association of frailty and coronary artery bypass grafting (CABG) are lacking. We assessed the association between frailty and cognitive and clinical complications following CABG.
Methods: This prospective study included patients aged over 60 years undergoing elective CABG at Tehran Heart Center from 2020 to 2022.
Bone Joint J
February 2024
Department of Orthopedic Surgery, New England Baptist Hospital, Boston, Massachusetts, USA.
Aims: The aim of this study was to characterize the influence of social deprivation on the rate of complications, readmissions, and revisions following primary total shoulder arthroplasty (TSA), using the Social Deprivation Index (SDI). The SDI is a composite measurement, in percentages, of seven demographic characteristics: living in poverty, with < 12 years of education, single-parent households, living in rented or overcrowded housing, households without a car, and unemployed adults aged < 65 years.
Methods: Patients aged ≥ 40 years, who underwent primary TSA between 2011 and 2017, were identified using International Classification of Diseases (ICD)-9 Clinical Modification and ICD-10 procedure codes for TSA in the New York Statewide Planning and Research Cooperative System database.
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