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OBJECTIVE: To evaluate the predictive value of lung ultrasound score (LUS) combined with central venous oxygen saturation variations (ΔScvO2) in the outcome of ventilator weaning in patients after thoracic surgery. METHODS: The clinical data of 60 patients who received tracheal intubation ventilator-assisted breathing after thoracic surgery were retrospectively analyzed, and they were divided into successful (n = 35) and failed (n = 25) groups according to the postoperative weaning outcomes. The factors influencing the failure of weaning in patients after thoracic surgery were compared and analyzed, and the values of LUS, ΔScvO2 as well as the combination of both were calculated to predict the failure of weaning in patients after thoracic surgery. RESULTS: The results of logistic regression analysis showed that LUS, ΔScvO2, and partial pressure of carbon dioxide (PaCO2) may be risk factors influencing weaning failure in patients after thoracic surgery (OR = 1.844, 4.006, 1.271, P < 0.001 for all), while diaphragm thickening fraction (DTF) and partial pressure of oxygen (PaO2) may be protective factors (OR = 0.852, 0.674, P = 0.002 for all). Receiver operator characteristic (ROC) curve showed that area under the curves (AUCs) of LUS, ΔScvO2, and the combination of the two was 0.865 (95% CI: 0.766-0.964), 0.874 (95% CI: 0.781-0.967), and 0.925 (95% CI: 0.860-0.990), respectively, in predicting failure of weaning in patients after thoracic surgery. CONCLUSION: LUS and ΔScvO2 were closely related to chest ultrasound index and arterial blood gas index in patients after thoracic surgery, both of which may be risk factors for weaning failure in patients after thoracic surgery, and their combination can effectively predict the occurrence of weaning failure.
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BACKGROUND: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2, and outbreaks have occurred worldwide. Laboratory test results are an important basis for clinicians to determine patient condition and formulate treatment plans. METHODS: Fifty-two thousand six hundred forty-four laboratory test results with continuous values of adult inpatients who were diagnosed with COVID-19 and hospitalized in the Fifth Hospital in Wuhan between 16 January 2020 and 18 March 2020 were compiled. The first and last test results were compared between survivors and non-survivors with variance test or Welch test. Laboratory test variables with significant differences were then included in the temporal change analysis. RESULTS: Among 94 laboratory test variables in 82 survivors and 25 non-survivors with COVID-19, white blood cell count, neutrophil count/percentage, mean platelet volume, platelet distribution width, platelet-large cell percentage, hypersensitive C-reactive protein, procalcitonin, D-dimer, fibrin (ogen) degradation product, middle fluorescent reticulocyte percentage, immature reticulocyte fraction, lactate dehydrogenase were significantly increased (P < 0.05), and lymphocyte count/percentage, monocyte percentage, eosinophil percentage, prothrombin activity, low fluorescent reticulocyte percentage, plasma carbon dioxide, total calcium, prealbumin, total protein, albumin, albumin-globulin ratio, cholinesterase, total cholesterol, nonhigh-density/low-density/small-dense-low-density lipoprotein cholesterol were significantly decreased in non-survivors compared with survivors (P < 0.05), in both first and last tests. Prothrombin time, prothrombin international normalized ratio, nucleated red blood cell count/percentage, high fluorescent reticulocyte percentage, plasma uric acid, plasma urea nitrogen, cystatin C, sodium, phosphorus, magnesium, myoglobin, creatine kinase (isoenzymes), aspartate aminotransferase, alkaline phosphatase, glucose, triglyceride were significantly increased (P < 0.05), and eosinophil count, basophil percentage, platelet count, thrombocytocrit, antithrombin III, red blood cell count, haemoglobin, haematocrit, total carbon dioxide, acidity-basicity, actual bicarbonate radical, base excess in the extracellular fluid compartment, estimated glomerular filtration rate, high-density lipoprotein cholesterol, apolipoprotein A1/ B were significantly decreased in non-survivors compared with survivors (P < 0.05), only in the last tests. Temporal changes in 26 variables, such as lymphocyte count/percentage, neutrophil count/percentage, and platelet count, were obviously different between survivors and non-survivors. CONCLUSIONS: By the comprehensive usage of the laboratory markers with different temporal changes, patients with a high risk of COVID-19-associated death or progression from mild to severe disease might be identified, allowing for timely targeted treatment.
