Development and validation of a simple-to-use nomogram to predict the deterioration and survival of patients with COVID-19.

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.

The Use of Acute Normovolemic Hemodilution in Clipping Surgery for Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: The occurrence of coronavirus disease 2019 (COVID-19) has overwhelmed the blood supply chain worldwide and severely influenced clinical procedures with potential massive blood loss, such as clipping surgery for aneurysmal subarachnoid hemorrhage (aSAH). Whether acute normovolemic hemodilution (ANH) is safe and effective in aneurysm clipping remains largely unknown. METHODS: Patients with aSAH who underwent clipping surgery within 72 hours from bleeding were included. The patients in the ANH group received 400 mL autologous blood collection, and the blood was returned as needed during surgery. The relationships between ANH and perioperative allogeneic blood transfusion, postoperative outcome, and complications were analyzed. RESULTS: Sixty-two patients with aSAH were included between December 2019 and June 2020 (20 in the ANH group and 42 in the non-ANH group). ANH did not reduce the need of perioperative blood transfusion (3 [15%] vs. 5 [11.9%]; P = 0.734). However, ANH significantly increased serum hemoglobin levels on postoperative day 1 (11.5 ± 2.5 g/dL vs. 10.3 ± 2.0 g/dL; P = 0.045) and day 3 (12.1 ± 2.0 g/dL vs. 10.7 ± 1.3 g/dL; P = 0.002). Multivariable analysis indicated that serum hemoglobin level on postoperative day 1 (odds ratio, 0.895; 95% confidence interval, 0.822-0.973; P = 0.010) was an independent risk factor for unfavorable outcome, and receiver operating characteristic curve analysis showed that it had a comparable predictive power to World Federation of Neurosurgical Societies grade (Z = 0.275; P > 0.05). CONCLUSIONS: ANH significantly increased postoperative hemoglobin levels, and it may hold the potential to improve patients' outcomes. Routine use of ANH should be considered in aneurysm clipping surgery.