ObjectiveTo discuss the risk factors of acute respiratory distress syndrome (ARDS) in patients with severe pneumonia.MethodsData of 80 patients with severe pneumonia admitted in our ICU were analyzed retrospectively, and they were divided into two groups according to development of ARDS, which was defined according to the Berlin new definition. The age, gender, weight, Acute Physiology and Chronic Health EvaluationⅡscore, lactate, PSI score and LIPS score, etc. were collected. Statistical significance results were evaluated by multivariate logistic regression analysis after univariate analysis. Receiver operating characteristic (ROC) curve was plotted to analyze the predictive value of the parameter for ARDS after severe pneumonia.ResultsForty patients with severe pneumonia progressed to ARDS, there were 4 moderate cases and 36 severe cases according to diagnostic criteria. Univariate analysis showed that procalcitonin (t=4.08, P<0.001), PSI score (t=10.67, P<0.001), LIPS score (t=5.14, P<0.001), shock (χ2=11.11, P<0.001), albumin level (t=3.34, P=0.001) were related to ARDS. Multivariate logistic regression analysis showed that LIPS ［odds ratio (OR) 0.226, 95%CI=4.62-5.53, P=0.013］ and PSI (OR=0.854, 95%CI=132.2-145.5, P=0.014) were independent risk factors for ARDS. The predictive value of LIPS and PSI in ARDS occurrence was significant. The area under ROC curve (AUC) of LIPS was 0.901, the cut-off value was 7.2, when LIPS ≥7.2, the sensitivity and specificity were both 85.0%. AUC of PSI was 0.947, the cut-off value was 150.5, when PSI score ≥150.5, the sensitivity and specificity were 87.5% and 90.0% respectively.ConclusionsPSI and LIPS are independent risk factors of ARDS in patients with severe pneumonia, which may be references for guiding clinicians to make an early diagnosis and treatment plan.
ObjectiveTo study the distribution of bone-specific alkaline phosphatase (BALP), type Ⅰ collagen cross-linked C-telopeptide (CTX) and tartrate-resistant acid phosphatase (TRAP)-5b in plateau area builders, and analyze the influencing factors under plateau environment. MethodsBetween April and May, 2014, using random stratified cluster sampling, we included in our study 650 blood samples from the power grid construction people in Batang County of Ganzi Autonomous Prefecture of Sichuan Province and Mangkang County of Tibet Autonomous Region with an altitude ranging from 2 600 to 4 450 meters, averaging (3 586.50±610.85) meters. We collected their fasting blood and detected their TRAP-5b, CTX and BALP by enzyme-linked immunosorbent assay method. By using SPSS 13.0, we analyzed the relationship between TRAP-5b, CTX, BALP and the influencing factors such as age, working intensity, residence time in the plateau area and altitude of the plateau. In the end, we tried to find out the main influencing factors of bone metabolic markers in the plateau environment.ResultsThe levels of CTX, BALP and TRAP-5b were the highest before the age of 20, and the average levels of them were respectively (1.04±0.38) ng/mL, (52.09±14.62) μg/L, and (4.22±1.38) U/L. With the increase of age, the levels of CTX, TRAP-5b and BALP showed a downward trend, but CTX and BALP reached the lowest level in the age group of 40 to 49 years old, and the average levels of CTX and BALP were (0.44±0.26) ng/mL and (24.77±9.89) μg/L, respectively. Then they gradually increased after the age of 50. TRAP-5b reached the lowest level in the age group of 30 to 39 years old, and the average level of TRAP-5b was (2.59±0.95) U/L. Then it gradually increased after the age of 40. The activity of CTX and BALP increased obviously with the increase of altitude. With the increase of labor intensity, BALP, TRAP-5b and CTX all increased. However, no matter what labor intensity, the bone formation marker BALP first increased and then decreased with the plateau residence time, while the bone absorption marker TRAP-5b increased after the first reduction.ConclusionsBone metabolic markers are different in different age groups. Altitude, working intensity and plateau working time have significant effects on bone metabolism markers.