The Predictive Value of Serum Uric Acid on Acute Kidney Injury following Traumatic Brain Injury.

BACKGROUNDS: Acute kidney injury (AKI) is a prevalent nonneurological complication in patients with traumatic brain injury (TBI). We designed this study to explore the association between serum uric acid (SUA) level and the occurrence of AKI following TBI. METHODS: This is a retrospective single-center study. A total of 479 patients admitted with TBI were included in this study. We utilized SUA and other risk factors for AKI to construct a predictive model by performing multivariate logistic regression. 374 patients and 105 patients were, respectively, divided into a training set and validation set. The predictive value of the single SUA and constructed model was evaluated by drawing a receiver operating characteristic (ROC) curve. AKI was diagnosed according to the KIDGO criteria. RESULTS: 79 (21.12%) patients were diagnosed with AKI in the training cohort. The patients in the AKI group are older than those in the non-AKI group (p = 0.01). And the Glasgow Coma Scale (GCS) of the AKI group was lower than that of the non-AKI group (p < 0.001). In a multivariate logistic regression analysis, we found that heart rate (p = 0.041), shock (p = 0.018), serum creatinine (p < 0.001), and serum uric acid (SUA) (p < 0.001) were significant risk factors for AKI. Bivariate correlation analyses showed that serum creatinine was moderately positively correlated with SUA (r = 0.523, p < 0.001). Finally, the area under the receiver operating characteristic curve (AUC) of SUA for predicting AKI in the training set and validation set was 0.850 (0.805-0.895) and 0.869 (0.801-0.938), respectively. CONCLUSIONS: SUA is an effective risk factor for AKI following TBI. Combining SUA with serum creatinine could more accurately identify TBI patients with high risk of developing AKI.

The predictive value of RDW in AKI and mortality in patients with traumatic brain injury.

BACKGROUND: Red blood cell distribution width (RDW) has been validated valuable in predicting outcome and acute kidney injury (AKI) in several clinical settings. The aim of this study was to explore whether RDW is associated with outcome and AKI in patients with traumatic brain injury (TBI). METHODS: Patients admitted to our hospital for TBI from January 2015 to August 2018 were included in this study. Multivariate logistic regression analysis was performed to identify risk factors of AKI and outcome in patients with TBI. The value of RDW in predicting AKI and outcome was evaluated by receiver operating characteristic (ROC) curve. RESULTS: Three hundred and eighteen patients were included in this study. The median of RDW was 14.25%. We divided subjects into two groups based on the median and compared difference of variables between two groups. The incidence of AKI and mortality was higher in high RDW (RDW > 14.25) group (31.45% vs 9.43%, P < .001; 69.81% vs 29.56%, P < .001). Spearman's method showed RDW was moderately associated with 90-day Glasgow Outcome Scale (GOS) (P < .001). In multivariate logistic regression analysis, RDW, lymphocyte, chlorine, and serum creatinine were risk factors of AKI. And Glasgow Coma Scale (GCS), glucose, chlorine, AKI, and RDW were risk factors of mortality. The area under the ROC curve (AUC) of RDW for predicting AKI and mortality was 0.724 (0.662-0.786) and 0.754 (0.701-0.807), respectively. Patients with higher RDW were likely to have shorter median survival time (58 vs 70, P < .001). CONCLUSIONS: Red blood cell distribution width is an independent risk factor of AKI and mortality in patients with TBI.

Serum Procalcitonin Level Predicts Acute Kidney Injury After Traumatic Brain Injury.

BACKGROUND: A common non-neurologic complication after traumatic brain injury (TBI), acute kidney injury (AKI) is a risk factor of mortality. Some studies confirmed the predictive value of procalcitonin (PCT) on AKI in several clinical settings. We designed this study to explore the predictive value of PCT on AKI after TBI. METHODS: We retrospectively enrolled patients with TBI admitted to our hospital from February 2015 to June 2019. Multivariate logistic regression analysis was performed to find the risk factors of AKI and construct a predictive model for AKI. Receiver operating characteristics curves were drawn to compare the predictive value of PCT and the constructed model. RESULTS: A total of 214 patients were included in this study. The incidence of AKI after TBI was 25.70% in this study. Compared with the non-AKI group, the AKI group had higher age (P = 0.031), lower Glasgow Coma Scale (P < 0.001), and higher incidence of coagulopathy (P < 0.001) and shock (P < 0.001). Moreover, patients complicated with AKI had higher in-hospital mortality (P < 0.001) and worse 90-day outcome (P < 0.001). Multivariate logistic regression analysis indicated that age (P = 0.033), PCT (P = 0.002), serum chlorine (P = 0.011), and creatinine (P < 0.001) were independent risk factors of AKI. We constructed a predictive model using these 4 risk factors. The area under receiver operating characteristics curves of the predictive model was 0.928, which was significantly higher than that of a single PCT value (area under receiver operating characteristics curves = 0.833) (Z = 2.395, P < 0.05). CONCLUSIONS: PCT is valuable in predicting AKI after TBI. To avoid AKI after TBI, physicians can adjust treatment strategies according to the level of PCT.

The Effects of Safflower Yellow on Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Randomized, Controlled Clinical Trial.

OBJECTIVES: To evaluate the efficacy of safflower yellow in the acute exacerbation of chronic obstructive pulmonary disease (AECOPD). METHODS: In a prospective, randomized, controlled trial, 127 patients who met the inclusion criteria were enrolled and were randomly divided into two groups. The control group included 64 patients treated according to the global strategy for diagnosis, management, and prevention of COPD (www.goldcopd.org, updated 2011). The intervention group included 63 patients who received intravenous infusions of safflower yellow (100 mg of safflower yellow dissolved in 250 ml 0.9% saline) once daily for 14 consecutive days in addition to standard diagnosis and treatment. The difference in the average length of the hospital stay between the two groups of patients was determined. The follow-up period was 28 days; the differences in symptoms, clinical indicators, and 28-day mortality in the two groups were compared. Statistical analysis was conducted using SPSS 22.0 software to determine whether there were statistically significant differences (P <0.05) between groups. RESULTS: There were no statistically significant differences between the intervention group and the control group in changes in secondary indicators. There were no statistically significant differences in the 28-day mortality or in the survival curves of the two groups (P=0.496 and P=0.075, respectively). Safflower yellow treatment of AECOPD may relieve the patient's clinical symptoms, such as dyspnoea, shorten the average length of hospital stay (P=0.006, respectively), and decrease the duration of mechanical ventilation. CONCLUSION: Safflower yellow in the treatment of AECOPD has a degree of clinical value. This trial is registered under the identifier ChiCTR-IPR-17014176.

Perineural versus intravenous dexamethasone as an adjuvant in regional anesthesia: a systematic review and meta-analysis.

BACKGROUND: Dexamethasone is a common adjuvant for local anesthetics in regional anesthesia, but the optimal route of administration is controversial. Therefore, we did a systematic review and meta-analysis of randomized controlled trials to assess the effect of perineural versus intravenous dexamethasone on local anesthetic regional nerve-blockade outcomes. MATERIALS AND METHODS: Medline (through PubMed), Embase, Cochrane, Web of Science, and Biosis Previews databases were systematically searched (published from inception of each database to January 1, 2017) to identify randomized controlled trials. The data of the selected trials were statistically analyzed to find any significant differences between the two modalities. The primary outcome was the duration of analgesia. Secondary outcomes included duration of motor block, postoperative nausea and vomiting, and postoperative analgesic dose at 24 hours. We conducted a planned subgroup analysis to compare the effects between adding epinephrine or not. RESULTS: Ten randomized controlled trials met the inclusion criteria of our analysis, with a total of 749 patients. Without the addition of epinephrine, the effects of perineural and intravenous dexamethasone were equivalent concerning the duration of analgesia (mean difference 0.03 hours, 95% CI -0.17 to 0.24). However, with the addition of epinephrine, the analgesic duration of perineural dexamethasone versus intravenous dexamethasone was prolonged (mean difference 3.96 hours, 95% CI 2.66-5.27). Likewise, the impact of epinephrine was the same on the duration of motor block. The two routes of administration did not show any significant differences in the incidence of postoperative nausea and vomiting, nor on postoperative analgesic consumption at 24 hours. CONCLUSION: Our results show that perineural dexamethasone can prolong the effects of analgesic duration when compared to the intravenous route, only when epinephrine is coadministered. Without epinephrine, the two modalities show equivalent effect as adjuvants on regional anesthesia.