A Nomogram for Predicting Acute Respiratory Failure After Cervical Traumatic Spinal Cord Injury Based on Admission Clinical Findings.

OBJECTIVES: Acute respiratory failure (ARF) is a common medical complication in patients with cervical traumatic spinal cord injury (TSCI). To identify independent predictors for ARF onset in patients who underwent cervical TSCI without premorbid respiratory diseases and to apply appropriate medical supports based on accurate prediction, a nomogram relating admission clinical information was developed for predicting ARF during acute care period. METHODS: We retrospectively reviewed clinical profiles of patients who suffered cervical TSCI and were emergently admitted to Qingdao Municipal Hospital from 2014 to 2020 as the training cohort. Univariate analysis was performed using admission clinical variables to estimate associated factors and a nomogram for predicting ARF occurrence was generated based on the independent predictors from multivariate logistic regression analysis. This nomogram was assessed by concordance index for discrimination and calibration curve with internal-validated bootstrap strategy. Receiver operating characteristic curve was conducted to compare the predictive accuracy between the nomogram and the traditional gold standard, which combines neuroimaging and neurological measurements by using area under the receiver operating characteristic curve (AUC). An additional 56-patient cohort from another medical center was retrospectively reviewed as the test cohort for external validation of the nomogram. RESULTS: 162 patients were eligible for this study and were included in the training cohort, among which 25 individuals developed ARF and were recorded to endure more complications. Despite the aggressive treatments and prolonged intensive care unit cares, 14 patients insulted with ARF died. Injury level, American Spinal Injury Association Impairment Scale (AIS) grade, admission hemoglobin (Hb), platelet to lymphocyte ratio, and neutrophil percentage to albumin ratio (NPAR) were independently associated with ARF onset. The concordance index of the nomogram incorporating these predictors was 0.933 in the training cohort and 0.955 in the test cohort, although both calibrations were good. The AUC of the nomogram was equal to concordance index, which presented better predictive accuracy compared with previous measurements using neuroimaging and AIS grade (AUC 0.933 versus 0.821, Delong's test p < 0.001). Similar significant results were also found in the test cohort (AUC 0.955 versus 0.765, Delong's test p = 0.034). In addition, this nomogram was translated to a Web-based calculator that could generate individual probability for ARF in a visualized form. CONCLUSIONS: The nomogram incorporating the injury level, AIS grade, admission Hb, platelet to lymphocyte ratio, and NPAR is a promising model to predict ARF in patients with cervical TSCI who are absent from previous respiratory dysfunction. This nomogram can be offered to clinicians to stratify patients, strengthen evidence-based decision-making, and apply appropriate individualized treatment in the field of acute clinical care.

Light-Up Nonthiolated Aptasensor for Low-Mass, Soluble Amyloid-ß40 Oligomers at High Salt Concentrations.

Herein, a light-up nonthiolated aptasensor was developed for low-mass, soluble amyloid-ß40 oligomers (LS-Aß40-O). Au nanoparticles (AuNP) were employed as colorimetric probes, and the nonthiolated aptamers (Apt) were adsorbed on AuNP surfaces, acting as binding elements for LS-Aß40-O. The aggregation of AuNPs was induced when Apt-modified AuNPs (Apt@AuNPs) were under high-salt conditions. However, upon the addition of LS-Aß40-O into the Apt@AuNP solution, the salt tolerance of the AuNPs was greatly enhanced. Further studies confirmed that the formed LS-Aß40-O-Apt complex attached onto the AuNP surfaces via interactions between LS-Aß40-O and Au, which led to electrostatic and steric stabilization of the AuNPs under high-salt conditions. On the basis of this outcome, a sensitive light-up nonthiolated aptasensor for LS-Aß40-O was achieved with a detection limit of 10.0 nM and a linear range from 35.0 to 700 nM in a 175 mM NaCl solution. Cerebrospinal-fluid (CSF) samples from healthy persons and Alzheimer's disease (AD) patients were successfully distinguished by using this proposed method. The concentrations of LS-Aß40-O in the CSF of AD patients were of nanomolar grade, but there was no detectable LS-Aß40-O in those of the healthy persons. This work provides a new insight into the interaction between Apt@AuNPs and Aß40-O and also develops a simple, rapid, highly selective and sensitive, and applicable method for LS-Aß40-O detection in real CSF samples, which is significant for the diagnosis of AD.

Development and Clinical Translation of a Perioperative Nomogram Incorporating Free Fatty Acids to Predict Poor Outcome of Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment.

Objective: A reliable prediction of clinical outcome is important for clinicians to set appropriate medical strategies in treating patients with aneurysmal subarachnoid hemorrhage (aSAH). In this study, we aim to establish a perioperative nomogram involving serum lipid signatures for predicting poor outcomes at 3 months in patients with aSAH following endovascular therapy. Methods: Data of patients with aSAH receiving endovascular therapy were collected. Univariable and multivariable analyses were performed to screen independent predictors related to unfavorable outcomes defined by the modified Rankin Scale (mFS) ≥3. A novel nomogram based on these significant features was conducted. The clinical application of this nomogram was assessed by decision curve analysis (DCA) and clinical impact curve. Results: A total number of patients included in this study were 213 (average age 58.9 years, 65.7% female), representing a poor 3-month outcome rate of 48.8%. Free fatty acid (FFA) levels on admission were efficient in predicting poor outcomes compared with other contents in serum lipids. Univariable and multivariable analyses revealed advanced age (P = 0.034), poor Hunt Hess (HH) (odds ratio, OR = 3.7, P < 0.001) and mFS (OR = 6.0, P < 0.001), aneurysms in the posterior circulation (OR = 4.4, P = 0.019), and higher FFA levels on admission (OR = 3.1, P = 0.021) were negative independent predictors of poor 3 months outcome. A novel nomogram composed of these significant features presented a concordance index (C-index) of 0.831 while the practical benefit was validated by DCA and clinical impact curve. An online calculator based on R programming promoted the clinical application of this nomogram. Conclusion: Nomogram involving age, HH grade, mFS, aneurysm location, and serum FFA levels was sufficient to provide an individualized prediction of 3-month poor outcome for each patient with aSAH who underwent endovascular therapy.