Controlled trial of a collaborative primary care team model for patients with diabetes and depression: Rationale and design for a comprehensive evaluation

<p>Abstract</p> <p>Background</p> <p>When depression accompanies diabetes, it complicates treatment, portends worse outcomes and increases health care costs. A collaborative care case-management model, previously tested in an urban managed care organization in the US, achieved significant reduction of depressive symptoms, improved diabetes disease control and patient-reported outcomes, and saved money. While impressive, these findings need to be replicated and extended to other healthcare settings. Our objective is to comprehensively evaluate a collaborative care model for comorbid depression and type 2 diabetes within a Canadian primary care setting.</p> <p>Methods/design</p> <p>We initiated the TeamCare model in four Primary Care Networks in Northern Alberta. The intervention involves a nurse care manager guiding patient-centered care with family physicians and consultant physician specialists to monitor progress and develop tailored care plans. Patients eligible for the intervention will be identified using the Patient Health Questionnaire-9 as a screen for depressive symptoms. Care managers will then guide patients through three phases: 1) improving depressive symptoms, 2) improving blood glucose, blood pressure and cholesterol, and 3) improving lifestyle behaviors. We will employ the RE-AIM framework for a comprehensive and mixed-methods approach to our evaluation. Effectiveness will be assessed using a controlled “on-off” trial design, whereby eligible patients would be alternately enrolled in the TeamCare intervention or usual care on a monthly basis. All patients will be assessed at baseline, 6 and 12 months. Our primary analyses will be based on changes in two outcomes: depressive symptoms, and a multivariable, scaled marginal model for the combined outcome of global disease control (i.e., A1c, systolic blood pressure, LDL cholesterol). Our planned enrolment of 168 patients will provide greater than 80% power to observe clinically important improvements in all measured outcomes. Direct costing of all intervention components and measurement of all health care utilization using linked administrative databases will be used to determine the cost-effectiveness of the intervention relative to usual care.</p> <p>Discussion</p> <p>Our comprehensive evaluation will generate evidence to reliability, effectiveness and sustainability of this collaborative care model for patients with chronic diseases and depression.</p> <p>Trials registration</p> <p>Clintrials.gov Identifier: NCT01328639</p

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future

Pancreatic surgery outcomes: multicentre prospective snapshot study in 67 countries

Background: Pancreatic surgery remains associated with high morbidity rates. Although postoperative mortality appears to have improved with specialization, the outcomes reported in the literature reflect the activity of highly specialized centres. The aim of this study was to evaluate the outcomes following pancreatic surgery worldwide.Methods: This was an international, prospective, multicentre, cross-sectional snapshot study of consecutive patients undergoing pancreatic operations worldwide in a 3-month interval in 2021. The primary outcome was postoperative mortality within 90 days of surgery. Multivariable logistic regression was used to explore relationships with Human Development Index (HDI) and other parameters.Results: A total of 4223 patients from 67 countries were analysed. A complication of any severity was detected in 68.7 percent of patients (2901 of 4223). Major complication rates (Clavien-Dindo grade at least IIIa) were 24, 18, and 27 percent, and mortality rates were 10, 5, and 5 per cent in low-to-middle-, high-, and very high-HDI countries respectively. The 90-day postoperative mortality rate was 5.4 per cent (229 of 4223) overall, but was significantly higher in the low-to-middle-HDI group (adjusted OR 2.88, 95 per cent c.i. 1.80 to 4.48). The overall failure-to-rescue rate was 21 percent; however, it was 41 per cent in low-to-middle-compared with 19 per cent in very high-HDI countries.Conclusion: Excess mortality in low-to-middle-HDI countries could be attributable to failure to rescue of patients from severe complications. The authors call for a collaborative response from international and regional associations of pancreatic surgeons to address management related to death from postoperative complications to tackle the global disparities in the outcomes of pancreatic surgery (NCT04652271; ISRCTN95140761)