[Establishment of nomogram predicting model for the death risk of extremely severe burn patients and the predictive value].

Objective: To explore the death risk factors of extremely severe burn patients, establish a death risk nomogram predicting model, and investigate the predictive value for death risk of extremely severe burn patients. Methods: The medical records of 231 extremely severe burn patients (190 males and 41 females, aged 18-60 years) who were admitted to the Institute of Burn Research of the First Affiliated Hospital of Army Medical University from January 2010 to October 2018 and met the inclusion criteria were analyzed retrospectively. According to the final outcome, the patients were divided into survival group of 173 patients and death group of 58 patients. The sex, age, severity of inhalation injury, total burn area, full-thickness burn area, burn index, rehydration coefficient and urine volume coefficient of the first and second 24 h after injury, the first base excess, shock index, and hematocrit (HCT) after admission, whether to have pre-hospital fluid infusion, use of ventilator, and use of continuous renal replacement therapy (CRRT), and abbreviated burn severity index (ABSI ) and Baux score on admission of patients in the two groups were recorded or calculated. According to the use of ventilator, the patients were divided into with ventilator group of 131 patients and without ventilator group of 100 patients, and the death, total burn surface area, burn index, incidence and severity of inhalation injury were recorded. According to the use of CRRT, the patients were divided into with CRRT group of 59 patients and without CRRT group of 172 patients, and the death, total burn surface area, and burn index were recorded. Data were statistically analyzed with t test, chi-square test, and Mann-Whitney U test to screen the death related factors of patients. The indexes with statistically significant differences between survival group and death group were included in the multivariate logistic regression analysis to screen the independent death risk factors of patients, and the death risk nomogram predicting model was constructed based on the results.The Bootstrap method was used to validate the death risk nomogram predicting model internally. The predictive value of the nomogram model for predicting death risk of patients was detected by drawing calibration graph and calculating concordance index, and the death risk scores of 231 patients were acquired according to the death risk nomogram model. The receiver's operating characteristic (ROC) curve was drawn, and the optimal threshold and the sensitivity and specificity of optimal threshold in the ROC curve and the area under the curve were calculated. Results: (1) There were statistically significant differences in burn index, ABSI on admission, severity of inhalation injury, total burn area, full-thickness burn area, rehydration coefficient at the first 24 h after injury, use of ventilator, use of CRRT, and Baux score on admission of patients between the two groups (Z=-7.696, -7.031, χ(2)=18.304, 63.065, 23.300, 13.073, 34.240, 59.586, t=-7.536, P<0.01). (2) There were statistically significant differences in death, incidence and severity of inhalation injury, total burn area, and burn index of patients between with ventilator group and without ventilator group (χ(2)=34.240, 17.394, 25.479, Z=-6.557, -7.049, P<0.01). (3) There were statistically significant differences in death, total burn area, and burn index of patients between with CRRT group and without CRRT group (χ(2)=62.982, Z= -47.421, -6.678, P<0.01). (4) The use of ventilator, use of CRRT, and burn index were independent risk factors for the death of extremely severe burn patients (odds ratio=3.277, 5.587, 1.067, 95% confidence interval=1.073-10.008, 2.384-13.093, 1.038-1.096, P<0.05 or P<0.01). (5) The initial concordance index of nomogram predicting model was 0.90 and the corrected concordance index was 0.89. The concordance indexes before and after correction were higher and similar, which showed that the nomogram had good concordance and predictive effect. The optimum threshold of ROC curve was 0.23, the sensitivity and specificity of optimum threshold were 86.0% and 80.0%, respectively, and the area under ROC curve was 0.90 (95% confidence interval=0.86-0.94, P<0.01). Conclusions: Severe burns and damage and/or failure of organ are the main death causes of extremely severe burn patients. The death risk nomogram predicting model established on the basis of use of ventilator, use of CRRT, and burn index have good predictive ability for death of extremely severe burn patients.

Induction of tumor necrosis-alpha, p38 and JNK in the spinal cord following acute heart injury in the rat model.

BACKGROUND: It is still not known whether the spinal cytokine signaling pathways are involved in the pathophysiologic mechanism of the acute phase of heart disease. This study examines the expression pattern of tumor necrosis factor-alpha (TNF-alpha) and its two related mitogenic-activated protein kinases, p38 and Jun-N-terminal kinase (JNK), in the spinal cord in response to acute cardiac injury (ACI). METHODS: The ACI rat model was established by intra-myocardial injection of formalin. At the indicated times after the establishment of ACI, the thoracic segments of the spinal cord were harvested and Western blot was performed to determine the expression of TNF-alpha, p38 and JNK. The localization of the cytokine and the kinases was determined by immunohistochemistry and double immunofluorescence. RESULTS: In response to ACI, TNF-alpha protein was up-regulated and reached a peak level at 6 h after ACI. The up-regulated TNF-alpha was distributed in all the laminae in the spinal cord and mainly localized in the neurons, as determined by immunohistochemistry and double immunofluorescence. In response to ACI, p38 and JNK were also up-regulated in the spinal cord. The expression profiles of p38 and JNK were similar to that of activated TNF-alpha following ACI. CONCLUSIONS: This study shows that cardiac injury can induce the activation of spinal TNF-alpha, p38 and JNK. The activated spinal cytokine signaling may contribute to disease progression in the acute phase of cardiac injury in clinical practice.

[Assessment of dry body-weight in hemodialysis patients by plasma cyclic 3'5'-guanosine monophosphate].

OBJECTIVE: The aim of this paper was to investigate the changes in cyclic 3'5'-guanosine monophosphate (cGMP) before and after hemodialysis to estimate the value of cGMP to the dry boby-weight. METHODS: Plasma cGMP levels (by radioimmunoassay), cardiothoracic ratio (CTR), and the body weight (BW) before and after hemodialysis were determined in chronic hemodialysis patients and clinical signs and symptoms were observed at the same time. RESULTS: 1. The predialytic cGMP value of the patients was significantly higher than that of healthy controls (P < 0.05). 2. The postdialytic cGMP level was significantly lower than the predialytic cGMP level (P < 0.01). 3. Postdialytic CTR and BW values were significantly lower than predialytic values (P < 0.01). 4. Compared to those of predialysis, postdialytic clinic signs and symptoms of the patients were significantly relieved. CONCLUSIONS: 1. The plasma cGMP level can sensitively reflect the hydration state and is a reliable marker for dry body-weight estimation. 2. The measurement of plasma cGMP combined with clinical parameters and radiological indexes permit a more accurate dry body-weight estimation.

[Measurement of the inferior vena cava diameter for estimating fluid status in hemodialysis patients].

OBJECTIVE: To investigate the clinical application of inferior vena cava diameter (VCD) for estimating fluid status. METHODS: VCD were measured during the expiratory phase (VCD-E) in 64 patients before hemodialysis (hypervolemia) and 71 normovolemia cases by ultrasonography, meanwhile collapsibility index (CI) were calculated. RESULTS: (1) VCD-E was (10.69 +/- 2.18) mm, CI was (26.24 +/- 6.34)% in normovolemic group; and (13.78 +/- 2.95) mm, (19.28 +/- 6.24%) in hypervolemic group respectively. There were significant differences in both (P < 0.01). (2) Change of VCD-E between pre- and post-dialysis was related with the amount of ultrafiltration during hemodialysis (r = 0.38, P < 0.01). The ratio was (2.0 +/- 1.2) mm.kg-1. (3) By using VCD-E to estimate hypervolemia, receiver operating characteristic (ROC) curve showed if VCD-E > or = 13.0 mm, the sensitivity was 87.0% and the specificity was 87.5%. CONCLUSION: VCD-E in postdialysis patients would approach (10.7 +/- 2.2) mm, which could be interpreted as being close to the dry weight. Thus VCD appears to be a valuable tool in estimating fluid status.