Background Early identification of patients who are at high risk of poor clinical outcomes is of great importance in saving the lives of patients with novel coronavirus disease 2019 (COVID-19) in the context of limited medical resources. Objective To evaluate the value of the neutrophil to lymphocyte ratio (NLR), calculated at hospital admission and in isolation, for the prediction of the subsequent presence of disease progression and serious clinical outcomes (e.g., shock, death). Methods We designed a prospective cohort study of 352 hospitalized patients with COVID-19 between January 9 and February 26, 2020, in Yichang City, Hubei Province. Patients with an NLR equal to or higher than the cutoff value derived from the receiver operating characteristic curve method were classified as the exposed group. The primary outcome was disease deterioration, defined as an increase of the clinical disease severity classification during hospitalization (e.g., moderate to severe/critical; severe to critical). The secondary outcomes were shock and death during the treatment. Results During the follow-up period, 51 (14.5%) patients’ conditions deteriorated, 15 patients (4.3%) had complicated septic shock, and 15 patients (4.3%) died. The NLR was higher in patients with deterioration than in those without deterioration (median: 5.33 vs. 2.14, P < 0.001), and higher in patients with serious clinical outcomes than in those without serious clinical outcomes (shock vs. no shock: 6.19 vs. 2.25, P < 0.001; death vs. survival: 7.19 vs. 2.25, P < 0.001). The NLR measured at hospital admission had high value in predicting subsequent disease deterioration, shock and death (all the areas under the curve > 0.80). The sensitivity of an NLR ≥ 2.6937 for predicting subsequent disease deterioration, shock and death was 82.0% (95% confidence interval, 69.0 to 91.0), 93.3% (68.0 to 100), and 92.9% (66.0 to 100), and the corresponding negative predictive values were 95.7% (93.0 to 99.2), 99.5% (98.6 to 100) and 99.5% (98.6 to 100), respectively. Conclusions The NLR measured at admission and in isolation can be used to effectively predict the subsequent presence of disease deterioration and serious clinical outcomes in patients with COVID-19.
PurposeThe aim of this study was to investigate the clinical significance of circulating tumor cells (CTCs) in the peripheral blood of an osteosarcoma and the Ezrin gene expressed in CTCs.Patients and methodsCTC enrichment was done with CanPatrol™ CTC enrichment technique in 41 patients with osteosarcoma. The characterization of CTCs was performed using a multiple messenger RNA in situ analysis (MRIA). The expression of the Ezrin gene in CTCs was detected by RNA probe technology. The correlations of CTC counts, cell type and the expression level of the Ezrin gene with clinical stage and metastasis of osteosarcoma were analyzed using SPSS 16.0 software.ResultsThe CTC counts correlated significantly with Enneking stage (P<0.001). The ratio of mesenchymal CTCs correlated with the distant metastases (P<0.001). Ezrin gene expression in CTCs correlated significantly with distant metastases (χ2=152.51, P=0.000).ConclusionThe ratio of mesenchymal CTCs in the peripheral blood of osteosarcoma correlates with distant metastases. High expression of Ezrin gene in CTCs correlates with distant metastases.
Background COVID-19 pandemic has forced physicians to quickly determine the patient’s condition and choose treatment strategies. This study aimed to build and validate a simple tool that can quickly predict the deterioration and survival of COVID-19 patients. Methods A total of 351 COVID-19 patients admitted to the Third People’s Hospital of Yichang between 9 January to 25 March 2020 were retrospectively analyzed. Patients were randomly grouped into training (n = 246) or a validation (n = 105) dataset. Risk factors associated with deterioration were identified using univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression. The factors were then incorporated into the nomogram. Kaplan-Meier analysis was used to compare the survival of patients between the low- and high-risk groups divided by the cut-off point. Results The least absolute shrinkage and selection operator (LASSO) regression was used to construct the nomogram via four parameters (white blood cells, C-reactive protein, lymphocyte≥0.8 × 109/L, and lactate dehydrogenase ≥400 U/L). The nomogram showed good discriminative performance with the area under the receiver operating characteristic (AUROC) of 0.945 (95% confidence interval: 0.91–0.98), and good calibration (P = 0.539). Besides, the nomogram showed good discrimination performance and good calibration in the validation and total cohorts (AUROC = 0.979 and AUROC = 0.954, respectively). Decision curve analysis demonstrated that the model had clinical application value. Kaplan-Meier analysis illustrated that low-risk patients had a significantly higher 8-week survival rate than those in the high-risk group (100% vs 71.41% and P < 0.0001). Conclusion A simple-to-use nomogram with excellent performance in predicting deterioration risk and survival of COVID-19 patients was developed and validated. However, it is necessary to verify this nomogram using a large-scale multicenter study.
Rationale:This study aims to evaluate the diagnostic value of beta-endorphin (β-EP) and brain natriuretic peptid (BNP) plasma concentrations for the early diagnosis of acute left heart failure and atrial fibrillation.Patient concerns:A total of 45 patients were included. These patients comprised 23 male and 22 female patients,and 20 healthy subjects who underwent physical examinations in the Outpatient Department during the same periodwere included and assigned to the control group.Diagnoses:The diagnos stand was that of the Chinese guidelines for the diagnosis and treatment of heart failure.Interventions:Enzyme-linked immunosorbent assay was performed to detect the plasma concentration of β-EP and BNP in the treatment and control groups, and electrocardiogram targeting was performed to determine the left ventricular ejection fraction (LVEF).Outcomes:BNP, β-EP, and LVEF levels were higher in the treatment group (688.01 ± 305.78 ng/L, 394.06 ± 180.97 ng/L, and 70.48 ± 16.62%) compared with the control group (33.90 ± 8.50 ng/L, 76.87 ± 57.21 ng/L, and 32.11 ± 5.25%). The P-values were .015, .019, and .026, respectively, which were <.05. The difference was statistically significant. The BNP and β-EP's 4 correlations (r = 0.895, P <.001), BNP, β-EP, and the combination of BNP and β-EP for acute left heart failure diagnosis in maximizing Youden index sensitivity, specific degree, area under the ROC curve (AUC), and 95% confidence interval (CI) were respectively 93.5%, 81.3%, 0.921, 0.841, 0.921; 80.5%, 78.6%, 0.697, 0.505, 0.697; 94.1%, 83.5%, 0.604 to 0.979, and 0.604. Acute left heart failure in patients with LVEF acuity plasma BNP and β-EP 50% group was obviously lower than that in the LVEF <50% group (P <.01). BNP, β-EP, and LVEF were negatively correlated (r = −0.741, −0.635, P = .013, .018).Lessons:β-EP and BNP have high specificity and sensitivity for detecting early acute left heart failure and atrial fibrillation in patients, which is convenient, easy to perform, and suitable for clinical applications.
ObjectiveTo explore the association between compliance with quality indicators and hospitalisation expenses in patients with heart failure.DesignGeneralised linear model and quantile regression model were used to examine the association between compliance with five quality indicators and hospitalisation expenses.SettingGrade A hospital in Fujian Province, China.ParticipantsData on 2568 heart failure admissions between 2010 and 2015 were analysed.ResultsThe median (IQR) of hospitalisation expenses of 2568 patients was ¥10.9 (¥6.9–¥31.6) thousand. The rates of compliance with five quality indicators were 90.3% for evaluation of left ventricular function, 43.8% for diuretics, 62.0% for ACE inhibitors (ACEI) or angiotensin receptor blockers (ARB), 67.4% for beta-blockers, and 58.9% for aldosterone receptor antagonists. After adjustment for gender, age, residence, method of payment, number of diseases before admission, number of diseases at admission, number of emergency treatments during hospital stay and length of stay, patients who received evaluation for left ventricular function, diuretics, or ACEI or ARB had lower hospitalisation expenses, and patients who received beta-blockers had higher hospitalisation expenses, compared with their counterparts in generalised linear models. Differences in hospitalisation expenses between compliance and non-compliance with quality indicators became larger across quantile levels of hospitalisation expenses, and were found to be statistically significant when quantile level exceeded 0.80 (¥39.7 thousand) in quantile regression models.ConclusionsThe quality of care for patients with heart failure was below the target level. There was a negative relationship between compliance with quality indicators and hospitalisation expenses at the extreme quantile of expenses. More attention should be given to patients who may experience extreme expenses, and effective measures should be taken to improve the quality of care they receive.
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