[The correlation analysis between glucose level and its variability and prognosis in traumatic patients].

OBJECTIVE: To investigate the effect of glucose level, variability on the prognosis of traumatic patients. METHODS: A retrospective study involving 300 traumatic patients admitted to intensive care unit (ICU) was performed. The average glucose (GluAve), glucose standard deviation (GluSD) and glucose coefficient of variation (GluCV) during the first 72 hours were calculated. Patients were divided into survivor group (n=249) and non-survivor group (n=51) based on outcomes. The GluAve, GluSD and GluCV were compared between the two groups. Patients were allocated into five subgroups based on GluAve (3.9-5.5, 5.6-6.6, 6.7-7.7, 7.8-9.9, ≥10.0 mmol/L) as well as four subgroups on GluCV (<15%, 15%-30%, 30%-50%, >50%). The mortality in hospital was compared among the different subgroups and the different GluCV in the same level of GluAve subgroups, respectively. Multifactor logistic regression was used to determine the risk factor of hospital death. RESULTS: The levels of GluAve, GIuSD, GluCV of non-survivor group were higher than those of survivor group [11.31±4.38 mmol/L vs. 8.50±3.40 mmol/L, 2.85±1.94 mmol/L vs. 1.87±1.67 mmol/L, (28.30±23.08)% vs. (20.90±13.70)%, all P<0.05]. With the gradual increment of GluAve and GluCV level, the mortality was raised accordingly (χ (2)(1)=26.332, P=0.000; χ (2)(2)=65.522, P=0.000). In the subgroup of GluAve 7.8-9.9 mmol/L, the mortality was 9.09% (3/33) with GluCV <15% versus 46.15% (6/13) with GluCV >50% (P<0.01) respectively, and in the subgroup of GluAve ≥10.0 mmol/L, the mortality corresponding rates were 21.05% (4/19) with GluCV < 15% and 61.54% (8/13) with GluCV > 50% (P<0.05). The multivariable logistic regression analysis demonstrated that GluAve and GluCV were risk factors of mortality[GluAve odds ratio (OR)=1.150, 95% confidence interval (95%CI) was 1.042 to 1.270, P=0.006; GluCV OR=1.022, 95%CI was 0.999 to 1.040, P=0.040], GluSD had no effect on mortality. CONCLUSIONS: The increase in GluAve and GluCV in traumatic patients are significantly correlated with mortality. Control the level and the variability of blood glucose might be an important aspect of the multiple trauma death reduction.

Learning curve of robotic portal lobectomy for pulmonary neoplasms: A prospective observational study.

BACKGROUND: We aim to assess the learning curve of robotic portal lobectomy with four arms (RPL-4) in patients with pulmonary neoplasms using prospectively collected data. METHODS: Data from 100 consecutive cases with lung neoplasms undergoing RPL-4 were prospectively accumulated into a database between June 2018 and August 2019. The Da Vinci Si system was used to perform RPL-4. Regression curves of cumulative sum analysis (CUSUM) and risk-adjusted CUSUM (RA-CUSUM) were fit to identify different phases of the learning curve. Clinical indicators and patient characteristics were compared between different phases. RESULTS: The mean operative time, console time, and docking time for the entire cohort were 130.6 ± 53.8, 95.5 ± 52.3, and 6.4 ± 3.0 min, respectively. Based on CUSUM analysis of console time, the surgical experience can be divided into three different phases: 1-10 cases (learning phase), 11-51 cases (plateau phase), and >51 cases (mastery phase). RA-CUSUM analysis revealed that experience based on 56 cases was required to truly master this technique. Total operative time (p < 0.001), console time (p < 0.001), and docking time (p = 0.026) were reduced as experience increased. However, other indicators were not significantly different among these three phases. CONCLUSIONS: The RPL-4 learning curve can be divided into three phases. Ten cases were required to pass the learning curve, but the mastery of RPL-4 for satisfactory surgical outcomes requires experience with at least 56 cases.