ABSTRACT
OBJECTIVES: To assess the survival predictivity of baseline blood cell differential count (BCDC), discretised according to two different methods, in adults visiting an emergency room (ER) for illness or trauma over 1 year. DESIGN: Retrospective cohort study of hospital records. SETTING: Tertiary care public hospital in northern Italy. PARTICIPANTS: 11 052 patients aged >18 years, consecutively admitted to the ER in 1 year, and for whom BCDC collection was indicated by ER medical staff at first presentation. PRIMARY OUTCOME: Survival was the referral outcome for explorative model development. Automated BCDC analysis at baseline assessed haemoglobin, mean cell volume (MCV), red cell distribution width (RDW), platelet distribution width (PDW), platelet haematocrit (PCT), absolute red blood cells, white blood cells, neutrophils, lymphocytes, monocytes, eosinophils, basophils and platelets. Discretisation cut-offs were defined by benchmark and tailored methods. Benchmark cut-offs were stated based on laboratory reference values (Clinical and Laboratory Standards Institute). Tailored cut-offs for linear, sigmoid-shaped and U-shaped distributed variables were discretised by maximally selected rank statistics and by optimal-equal HR, respectively. Explanatory variables (age, gender, ER admission during SARS-CoV2 surges and in-hospital admission) were analysed using Cox multivariable regression. Receiver operating curves were drawn by summing the Cox-significant variables for each method. RESULTS: Of 11 052 patients (median age 67 years, IQR 51-81, 48% female), 59% (n=6489) were discharged and 41% (n=4563) were admitted to the hospital. After a 306-day median follow-up (IQR 208-417 days), 9455 (86%) patients were alive and 1597 (14%) deceased. Increased HRs were associated with age >73 years (HR=4.6, 95% CI=4.0 to 5.2), in-hospital admission (HR=2.2, 95% CI=1.9 to 2.4), ER admission during SARS-CoV2 surges (Wave I: HR=1.7, 95% CI=1.5 to 1.9; Wave II: HR=1.2, 95% CI=1.0 to 1.3). Gender, haemoglobin, MCV, RDW, PDW, neutrophils, lymphocytes and eosinophil counts were significant overall. Benchmark-BCDC model included basophils and platelet count (area under the ROC (AUROC) 0.74). Tailored-BCDC model included monocyte counts and PCT (AUROC 0.79). CONCLUSIONS: Baseline discretised BCDC provides meaningful insight regarding ER patients' survival.
Subject(s)
Erythrocyte Indices , RNA, Viral , Humans , Adult , Female , Aged , Male , Retrospective Studies , Blood Platelets , Hemoglobins , PrognosisABSTRACT
INTRODUCTION: Interventions aimed at increasing comfort of patients treated with Helmet Continuous Positive Airway Pressure (H-CPAP) increase its endurance and the duration of treatment. AIM: To assess the effect of nursing interventions on factors of discomfort for H-CPAP patients. METHODS: The fixing method of the helmet (5 subjects), the noise generated by the gas source and the level of humidity in the helmet were assessed. Fixing method: pain measured with Numeric rating scales (NRS) and Stress detector after the application of armpit straps or counterweights. Noise: level of noise (decibel measurement) in the helmet and the interventions to reduce it. Humidity: level of humidity with different models of active humidifiers. RESULTS: The armpit straps increase the pain measured with the stress detector of 0.206 microSiemens and of 4.8 points of the NRS after 5 minutes. The system with counterweights does not increase pain. The Heath and Moisture Exchangers (HME) Filters and tubes with smooth inner surface decrease the level of noise in the helmet from 70 to 48 decibel, with a gas flow of 30 l/min. The humidification and warming of gases (26 degrees C (-2 gradient) and warmed tubes) delivers a relative humidity of 33.9 +/- 1.9 mgH2O/l thus avoinding the steaming of the helmet. CONCLUSIONS: The use of counterweights, HME filters, tubes with smooth surface, ear plugs to reduce the noise level and active humidification and warming of gases reduce the discomfort associated to H-CPAP.