Pragmatic and Observational Research最新文献

Background: Cohort matching and regression modeling are used in observational studies to control for confounding factors when estimating treatment effects. Our objective was to evaluate exact matching and propensity score methods by applying them in a 1-year pre-post historical database study to investigate asthma-related outcomes by treatment.

Methods: We drew on longitudinal medical record data in the PHARMO database for asthma patients prescribed the treatments to be compared (ciclesonide and fine-particle inhaled corticosteroid [ICS]). Propensity score methods that we evaluated were propensity score matching (PSM) using two different algorithms, the inverse probability of treatment weighting (IPTW), covariate adjustment using the propensity score, and propensity score stratification. We defined balance, using standardized differences, as differences of <10% between cohorts.

Results: Of 4064 eligible patients, 1382 (34%) were prescribed ciclesonide and 2682 (66%) fine-particle ICS. The IPTW and propensity score-based methods retained more patients (96%-100%) than exact matching (90%); exact matching selected less severe patients. Standardized differences were >10% for four variables in the exact-matched dataset and <10% for both PSM algorithms and the weighted pseudo-dataset used in the IPTW method. With all methods, ciclesonide was associated with better 1-year asthma-related outcomes, at one-third the prescribed dose, than fine-particle ICS; results varied slightly by method, but direction and statistical significance remained the same.

Conclusion: We found that each method has its particular strengths, and we recommend at least two methods be applied for each matched cohort study to evaluate the robustness of the findings. Balance diagnostics should be applied with all methods to check the balance of confounders between treatment cohorts. If exact matching is used, the calculation of a propensity score could be useful to identify variables that require balancing, thereby informing the choice of matching criteria together with clinical considerations.

Purpose: The purpose of the present study was to investigate the association between the perioperative neutrophil to lymphocyte ratio (NLR) and cardiac surgery patient outcomes.

Patients and methods: A retrospective cohort study of 145 patients who underwent cardiac surgery in a tertiary hospital of Athens, Greece, from January to March 2015, was conducted. By using a structured short questionnaire, this study reviewed the electronic hospital database and the medical and nursing patient records for data collection purposes. The statistical significance was two-tailed, and p-values <0.05 were considered significant. The statistical analysis was performed with Mann-Whitney U test and Spearman's correlation coefficient, by using the Statistical Package for Social Sciences software (IBM SPSS 21.0 for Windows).

Results: The increased preoperative levels of NLR were associated with significantly higher mortality, both in-hospital (p=0.001) and 30-day (p=0.002), prolonged postoperative hospital length of stay (LOS), both in the cardiac intensive care unit (ICU) (p=0.002), and in-hospital (p=0.018), and likewise with delayed tracheal extubation (p≤0.001). Furthermore, patients with elevated NLR during the second postoperative day had significantly higher in-hospital mortality (p=0.018), increased incidence of pneumonia (p=0.022), higher probability of readmission to the ICU (p=0.002), prolonged ICU LOS (p≤0.001), and delayed tracheal extubation (p≤0.001).

Conclusion: Increased perioperative NLR seems to be associated with significantly higher mortality and morbidity in cardiac surgery patients. At the same time, NLR is a significant and inexpensive biomarker for the early identification of patients at high risk for complications. In addition, NLR levels could lead clinicians to perform measures for the optimal therapeutic patient approach.

Atrial fibrillation (AF) is the most common arrhythmia worldwide, leading to an extensive public health and economic burden. The increasing incidence and prevalence of AF is due to the advancing age of the population, structural heart disease, hypertension, diabetes, and thyroid disease. The majority of costs associated with AF have been attributed to the cost of hospitalization. In order to minimize costs and decrease hospitalizations, counseling on modifiable risk factors contributing to AF has been strongly emphasized. With the release of novel oral anticoagulants bypassing the need for anticoagulant bridging or laboratory monitoring, post-discharge nurse-led home intervention, and novel methods of heart rate monitoring, home-based AF management has reached a new level of ease and sophistication. In this review, we aimed to review modifiable risk factors for AF and various methods of home-based management of AF, along with their benefits.

Chronic kidney disease (CKD) is an important and common noncommunicable condition globally. In national and international guidelines, CKD is defined and staged according to measures of kidney function that allow for a degree of risk stratification using commonly available markers. It is often asymptomatic in its early stages, and early detection is important to reduce future risk. The risk of cardiovascular outcomes is greater than the risk of progression to end-stage kidney disease for most people with CKD. CKD also predisposes to acute kidney injury - a major cause of morbidity and mortality worldwide. Although only a small proportion of people with CKD progress to end-stage kidney disease, renal replacement therapy (dialysis or transplantation) represents major costs for health care systems and burden for patients. Efforts in primary care to reduce the risks of cardiovascular disease, acute kidney injury, and progression are therefore required. Monitoring renal function is an important task, and primary care clinicians are well placed to oversee this aspect of care along with the management of modifiable risk factors, particularly blood pressure and proteinuria. Good primary care judgment is also essential in making decisions about referral for specialist nephrology opinion. As CKD commonly occurs alongside other conditions, consideration of comorbidities and patient wishes is important, and primary care clinicians have a key role in coordinating care while adopting a holistic, patient-centered approach and providing continuity. This review aims to summarize the vital role that primary care plays in predialysis CKD care and to outline the main considerations in its identification, monitoring, and clinical management in this context.

Purpose: The purpose of this study was to evaluate the optimization of fasting blood glucose (FBG) levels in patients with type 2 diabetes mellitus newly initiated on insulin glargine who were enrolled in the Australian Diabetes CoStars Patient Support Program (PSP).

Patients and methods: A retrospective analysis of data from 514 patients with type 2 diabetes mellitus who completed the 12-week Diabetes CoStars PSP was performed. All patients were initiated on insulin glargine in primary care and enrolled by their general practitioner, who selected a predefined titration plan and support from a local Credentialled Diabetes Educator. The data collected included initial and final insulin dose, self-reported FBG, and glycated hemoglobin (A_1c) levels.

Results: The insulin dose increased in 81% of patients. Mean FBG was reduced from 208.8 mg/dL (11.6 mmol/L) to 136.8 mg/dL (7.6 mmol/L) after 12 weeks. Initial and final A_1c values were available for 99 patients; mean A_1c was reduced from 9.5% (80 mmol/mol) to 8.1% (65 mmol/mol). The reductions in mean FBG and A_1c were similar irrespective of titration plan. Overall, 27.2% of patients achieved FBG levels within the titration plan target range of 72-108 mg/dL (4-6 mmol/L) and an additional 43.4% of patients achieved FBG within the range recommended by current Australian guidelines (110-144 mg/dL [6.1-8.0 mmol/L]). Overall, 23.3% of patients achieved the A_1c target of ≤7%.

Conclusion: These data demonstrate that the majority of patients enrolled in the Diabetes CoStars PSP achieved acceptable FBG levels 12 weeks after starting insulin therapy irrespective of titration plan.

The discussion about the optimal design of clinical trials reflects the perspectives of theory-based scientists and practice-based clinicians. Scientists compare the theory with published results. They observe a continuum from explanatory to pragmatic trials. Clinicians compare the problem they want to solve by completing a clinical trial with the results they can read in the literature. They observe a mixture of what they want and what they get. None of them can solve the problem without the support of the other. Here, we summarize the results of discussions with scientists and clinicians. All participants were interested to understand and analyze the arguments of the other side. As a result of this process, we conclude that scientists tell what they see, a continuum from clear explanatory to clear pragmatic trials. Clinicians tell what they want to see, a clear explanatory trial to describe the expected effects under ideal study conditions and a clear pragmatic trial to describe the observed effects under real-world conditions. Following this discussion, the solution was not too difficult. When we accept what we see, we will not get what we want. If we discuss a necessary change of management, we will end up with the conclusion that two types of studies are necessary to demonstrate efficacy and effectiveness. Efficacy can be demonstrated in an explanatory, ie, a randomized controlled trial (RCT) completed under ideal study conditions. Effectiveness can be demonstrated in an observational, ie, a pragmatic controlled trial (PCT) completed under real-world conditions. It is impossible to design a trial which can detect efficacy and effectiveness simultaneously. The RCTs describe what we may expect in health care, while the PCTs describe what we really observe.