Takehiro Sugiyama - the University of Tokyo
the University of Tokyo
Publications Authored By Takehiro Sugiyama
Two hundred and eighty-two patients who were admitted to the ICU.
Blood samples were obtained at ICU admission.
We analyzed the associations among nine representative laboratory variables of each organ system using network analysis. We compared the network structure of the variables in the 40 nonsurvivors with that in the 40 survivors. Their baseline characteristics, including the degree of organ dysfunction, were matched using propensity score matching method. Network structure was quantitatively evaluated using edge (significant correlation among variables evaluated by the p value), weight (connective strength of edge evaluated by coefficient), and cluster (group with tight connection evaluated by edge betweenness). The number of edges among the nine variables was significantly fewer for the nonsurvivors than for the severity-matched survivors (3 vs 12; p = 0.035). The mean weight of edges was significantly smaller for the nonsurvivors (0.055 vs 0.119; p = 0.007). The nine laboratory variables for the nonsurvivors were divided into a significantly larger number of clusters (7 vs 2; p = 0.001). Statistical conclusions were preserved with Bonferroni multiple comparison procedure. These findings were consistently observed in comparison of the 40 nonsurvivors with all the survivors.
This study, as a preliminary proof-of-concept, quantitatively demonstrated a more disrupted network structure of organ systems in the nonsurvivors compared with that in the survivors. These observations suggest the necessity of assessment for organ system interactions to evaluate critically ill patients.
This cross-sectional study used a set of databases on medical institutions and personnel. We analyzed a sample of 168,594 clinically active physicians practicing in institutions as of May 2014, who passed the National Medical Practitioners Examination between 1985 and 2013. We assessed the retention rate and the schools' establishment period and funding source (pre-1970/post-1970, private/public), using a hierarchical regression model with random intercept unique to each medical school. We used the following factors as covariates: gender, physicians' length of professional experience, and the geographical features of the medical schools.
The retention rate was widely distributed from 16.2 to 81.5 % (median: 48.4 %). Physicians who graduated from post-1970 medical schools were less likely to practice in the prefecture of their medical school location, relative to those who graduated from pre-1970 medical schools (adjusted odds ratio: 0.75; 95 % confidence interval: 0.62-0.90). Physicians who graduated from private medical schools were also less likely to practice in the prefecture of their medical school location, relative to those who graduated from public medical schools (adjusted odds ratio: 0.63; 95 % confidence interval: 0.51-0.77). In addition, the ability to retain graduates varied by school according to the school's characteristics.
There was a considerable difference between medical schools in retaining graduates locally. The study results may have significant implications for government policy to alleviate maldistribution of physicians in Japan.
We conducted secondary analyses of data from the Diabetes Self-Care Study, a randomized controlled trial of a community-based DSME intervention. Study participants (n = 516) were African Americans and Latinos 55 years or older with poorly controlled diabetes (HbA1c ≥ 8.0%) recruited from senior centers and churches in Los Angeles. The intervention group received six weekly small-group self-care sessions based on the empowerment model. The control group received six lectures on unrelated geriatrics topics. The primary outcome variable in this secondary analysis was the change in Mental Component Summary score (MCS-12) from the SF-12 Health Survey between baseline and six-month follow-up. We used the change in HbA1c during the study period as the main mediator of interest in our causal mediation analysis. Additionally, possible mediations via social support and perceived empowerment attributable to the program were examined.
MCS-12 increased by 1.4 points on average in the intervention group and decreased by 0.2 points in the control group (difference-in-change: 1.6 points, 95% CI: 0.1 to 3.2). In the causal mediation analysis, the intervention had a direct effect on MCS-12 improvement (1.7 points, 95% CI: 0.2 to 3.2) with no indirect effects mediated via HbA1c change (-0.1 points, 95% CI: -0.4 to 0.1), social support (0.1 points), and perception of empowerment (0.1 points).
This Diabetes Self-Care Study empowerment intervention had a modest positive impact on mental HRQoL not mediated by the improvement in glycemic control, as well as social support and perception of empowerment. This favorable effect on mental HRQoL may be a separate clinical advantage of this DSME intervention.
Hospitalizations were stratified by type of AMI and intervention, and the time trends of in-hospital mortality and hospital costs were examined for each combination of the AMI type and intervention, after adjusting for both patient- and hospital-level characteristics. Compared with 2001, adjusted in-hospital mortality improved significantly for NSTEMI patients in 2011, regardless of the intervention received (PCI odds ratio [OR] 0.68, 95% CI 0.56 to 0.83; CABG OR 0.57, 0.45 to 0.72; without intervention OR 0.61, 0.57 to 0.65). As for STEMI, a decline in adjusted in-hospital mortality was significant for those who underwent PCI (OR 0.83; 0.73 to 0.94); however, no significant improvement was observed for those who received CABG or without intervention. Hospital costs per hospitalization increased significantly for patients who underwent intervention, but not for those without intervention.
In the United States, the decrease in in-hospital mortality and the increase in costs differed by the AMI type and the intervention received. These non-uniform trends may be informative for designing effective health policies to reduce the health and economic burdens of AMI.
A repeated cross-sectional study in a nationally representative sample of 27,886 US adults, 20 years or older, from the National Health and Nutrition Examination Survey, 1999 through 2010.
Caloric and fat intake measured through 24-hour dietary recall. Generalized linear models with interaction term between survey cycle and statin use were constructed to investigate the time trends of dietary intake for statin users and nonusers after adjustment for possible confounders. We calculated model-adjusted caloric and fat intake using these models and examined if the time trends differed by statin use. Body mass index (BMI) changes were also compared between statin users and nonusers.
In the 1999-2000 period, the caloric intake was significantly less for statin users compared with nonusers (2000 vs 2179 kcal/d; P = .007). The difference between the groups became smaller as time went by, and there was no statistical difference after the 2005-2006 period. Among statin users, caloric intake in the 2009-2010 period was 9.6% higher (95% CI, 1.8-18.1; P = .02) than that in the 1999-2000 period. In contrast, no significant change was observed among nonusers during the same study period. Statin users also consumed significantly less fat in the 1999-2000 period (71.7 vs 81.2 g/d; P = .003). Fat intake increased 14.4% among statin users (95% CI, 3.8-26.1; P = .007) while not changing significantly among nonusers. Also, BMI increased more among statin users (+1.3) than among nonusers (+0.4) in the adjusted model (P = .02).
Caloric and fat intake have increased among statin users over time, which was not true for nonusers. The increase in BMI was faster for statin users than for nonusers. Efforts aimed at dietary control among statin users may be becoming less intensive. The importance of dietary composition may need to be reemphasized for statin users.
Of 349 hospitals, 286 (81.9%) responded to the survey. Sixty-five percent of hospitals had a policy about POLST, 87% had available blank POLST forms, 84% had educated staff, and 94% reported handling POLST properly in the emergency department and on admission. In multivariable analyses, hospitals in poor areas and for-profit (vs nonprofit) hospitals were less likely to stock blank POLST forms and to have educated staff, and hospitals with community coalition interaction and in wealthier areas were more likely to handle POLST forms correctly. Although POLST is widely used in California, a significant minority of hospitals remain unprepared 3 years after implementation. Efforts to improve implementation should emphasize dissemination in poorer areas and in for-profit hospitals.
A 68-yr-old nondiabetic woman with an ovarian tumor was suffering from hyper- and hypoglycemia. Based on the results of an oral glucose tolerance test and continuous glucose monitoring, we speculated that the fluctuating blood glucose level was accompanied not only by a low insulin level but also by low counter-regulatory hormones levels, and that those broad hormonal suppressions were caused by a high somatostatin level produced in the ovarian tumor. We performed an oophorectomy and assessed the pathology of the tumor and changes in the blood glucose profile as well as hormonal levels postoperatively.
The blood glucose level was completely normalized after the oophorectomy. Insulin secretion was also normalized. Histological examination showed that the tumor comprised a mature cystic teratoma and a stromal carcinoid. Immunohistochemically, the stromal carcinoid component was positive for somatostatin. The somatostatin level was 8505 pmol/liter preoperatively, which dropped down to 71.5 pmol/liter postoperatively. We found two previous reports of somatostatin-producing ovarian neuroendocrine tumors. Somatostatin levels among cases of ovarian origin were much higher than those among cases of gastrointestinal origins, and cases of ovarian origin all experienced blood glucose fluctuations.
Extremely high somatostatin levels and blood glucose fluctuations may be characteristics of somatostatin-producing ovarian neuroendocrine tumors.
The serum levels of the cholesterol absorption markers were significantly reduced, while those of the cholesterol synthesis markers were significantly increased at 12 weeks of ezetimibe therapy. No significant differences were noted in the values of the parameters of glucose metabolism in all patients. We also investigated the clinical characteristics of patients who exhibited a good response to ezetimibe (ezetimibe responders); however, multivariate regression analysis did not reveal a correlation between ezetimibe efficacy and patient characteristics such as gender, age, BMI, diabetic condition, method of ezetimibe administration, and the initial absolute values of cholesterol absorption/synthesis markers levels. In conclusion, ezetimibe therapy significantly improved the lipid profile without disturbing glucose metabolism. We were unable to identify the specific characteristics of ezetimibe responders among our subjects. However, we may interpret this result as suggesting that ezetimibe can be used in any population to lower low-density lipoprotein cholesterol levels.
A cross-sectional study was conducted of 4508 12-19-year-old respondents of the 1999-2002 National Health and Nutrition Examination Survey. Systolic and diastolic blood pressure (SBP and DBP) were measured and adjusted for gender, age, and height using z-scores (SBPZ and DBPZ). Body mass index (BMI) was adjusted for gender and age (BMIZ). Questionnaires were used to measure nutrient intake (carbohydrate, protein, saturated and unsaturated fat, sodium, potassium, calcium, magnesium, fiber, and caffeine) and activities (physical activities and sedentary activities, including television watching).
In the adjusted model (R2 = .115), SBPZ was higher by .022 standard deviation (SD) (95% confidence interval [CI]: .007-.038, equivalent to approximately .2 mmHg) per 1-hour increments in sedentary activities; higher by .244 SD (.198-.289, approximately 2.6 mmHg) per 1 SD of BMIZ; and lower by .099 SD (-.192 to -.006, approximately 1.1 mmHg) per 100 g of carbohydrate intake. Unexpectedly, BMIZ was negatively associated with DBPZ (-.078 per 1 SD, -.114 to -.043, approximately .9 mmHg).
Among U.S. adolescents, sedentary activities and BMI are positively associated with SBP after adjustment for confounding factors and mediators, while BMI is negatively associated with DBP. If confirmed by further studies, population-based interventions aimed at sedentary activities may be practical approaches to decrease SBP and the risk of obesity among adolescents.