Primary nonadherence to drugs prescribed by general practitioners: A Dutch database study

Aim: Primary nonadherence (PNA) is defined as not filling the first prescription for a drug treatment. PNA can lead not only to poor patient outcomes but also to exposure misclassification in written prescription databases. This study aims to estimate PNA in primary care in the Netherlands and to investigate associated factors. Methods: Patients from the Nivel Primary Care Database (Nivel-PCD) who received a new prescription (>1 year not prescribed) from a general practitioner in 2012 were linked to pharmacy dispensing information of consenting pharmacies based on sex, year of birth, four-digit postal code and at least 50% matching Anatomical Therapeutic Classification codes. PNA was defined as not having a prescription dispensed within 30 days from the prescribing date. PNA was assessed overall and per drug class. The associations between PNA and several patient- and prescription-related characteristics were assessed using mixed-effects logistic regression models. Results: After matching 86 361 of 396 251 subjects (21.8%) in the Nivel-PCD records to the pharmacy records, this study included 65 877 subjects who received 181 939 new drug prescriptions. Overall, PNA was 11.5%. PNA was lowest for thyroid hormones (5.5%) and highest for proton pump inhibitors (12.8%). Several factors were associated with PNA, such as having comorbidities (odds ratio [OR] 1.46, 95% confidence interval [CI] 1.37-1.56 for >3 active diagnoses, compared to no active diagnoses) or reimbursement status (OR 2.78, 95% CI 2.65-2.92 for not reimbursed drugs compared to fully reimbursed drugs). Conclusions: A total of 11.5% of newly prescribed drugs were not dispensed. This can lead to overestimation of the actual drug exposure status when using written prescription databases

Rivaroxaban was found to be noninferior to warfarin in routine clinical care: A retrospective noninferiority cohort replication study

Purpose: To compare the effectiveness and safety of a drug in daily practice with the outcomes of a target non-inferiority trial by rigorously mimickingin an observational study the trial's design features. Methods: This cohort study was conducted using the British Clinical Practice Research Datalink (CPRD) to emulate the ROCKET AF (Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation) trial. Patients with atrial fibrillation who were newly prescribed (>=12 months of no use) either rivaroxaban or warfarinfrom October 2008 to December 2017 were included. Non-inferiority of rivaroxaban to warfarin in the prevention of stroke or systemic embolism was assessed in different analysis populations (intention-to-treat [ITT], per-protocol [PP], and as-treated populations) using a hazardratio (HR) of 1.46 as the non-inferiority margin. Major bleeding (safety outcome) was also assessed and compared to that of the target trial. All outcomes were analyzed using Cox-proportional hazard analyses. Results: We included 25,473 incident users of rivaroxaban (n=4,008) or warfarin(n=21,465). Similar to the trial, non-inferiority in the primary out come was demonstrated in all three analysis populations: HR=1.04 (95%CI 0.84 to 1.30) (ITT), HR=0.98 (95%CI 0.70 to 1.38) (PP), and HR=1.11 (95%CI 0.86 to 1.42) (as-treated). Risk of major bleeding was also similar to the target trial. Conclusion: The results of this study provide supportive evidence to the effectiveness of rivaroxaban and adds knowledge on the usefulness of emulating a non-inferiority trial to assess drug effectiveness

Towards tailoring of self-management for patients with chronic heart failure or chronic obstructive pulmonary disease: a protocol for an individual patient data meta-analysis

Introduction Self-management interventions in patients with chronic conditions have received increasing attention over the past few years, yet the meta-analyses encountered considerable heterogeneity in results. This suggests that the effectiveness of self-management interventions must be assessed in the context of which components are responsible for eliciting the effect and in which subgroups of patients the intervention works best. The aim of the present study is to identify condition-transcending determinants of success of self-management interventions in two parallel individual patient data meta-analyses of self-management trials in patients with congestive heart failure (CHF) and in patients with chronic obstructive pulmonary disease (COPD). Methods and analysis Investigators of 53 randomised trials (32 in CHF and 21 in COPD) will be requested to share their de-identified individual patient data. Data will be analysed using random effects models, taking clustering within studies into account. Effect modification by age, sex, disease severity, symptom status, comorbid conditions and level of education will be assessed. Sensitivity analyses will be conducted to assess the robustness of the findings. Ethics and dissemination The de-identified individual patient data are used only for the purpose for which they were originally collected and for which ethical approval has been obtained by the original investigators. Knowledge on the effective ingredients of self-management programmes and identification of subgroups of patients in which those interventions are most effective will guide the development of evidence-based personalised self-management interventions for patients with CHF and COPD as well as with other chronic diseases

Is a chest radiograph indicated after chest tube removal in trauma patients? A systematic review

PURPOSE The aim of this systematic review was to assess the necessity of routine chest radiographs after chest tube removal in ventilated and nonventilated trauma patients. METHODS A systematic literature search was conducted in MEDLINE, Embase, CENTRAL, and CINAHL on May 15, 2020. Quality assessment was performed using the Methodological Index for Nonrandomized Studies criteria. Primary outcome measures were abnormalities on postremoval chest radiograph (e.g., recurrence of a pneumothorax, hemothorax, pleural effusion) and reintervention after chest tube removal. Secondary outcome measures were emergence of new clinical symptoms or vital signs after chest tube removal. RESULTS Fourteen studies were included, consisting of seven studies on nonventilated patients and seven studies on combined cohorts of ventilated and nonventilated patients, all together containing 1,855 patients. Nonventilated patients had abnormalities on postremoval chest radiograph in 10% (range across studies, 0-38%) of all chest tubes and 24% (range, 0-78%) of those underwent reintervention. In the studies that reported on clinical symptoms after chest tube removal, all patients who underwent reintervention also had symptoms of recurrent pathology. Combined cohorts of ventilated and nonventilated patients had abnormalities on postremoval chest radiograph in 20% (range, 6-49%) of all chest tubes and 45% (range, 8-63%) of those underwent reintervention. CONCLUSION In nonventilated patients, one in ten developed recurrent pathology after chest tube removal and almost a quarter of them underwent reintervention. In two studies that reported on clinical symptoms, all reinterventions were performed in patients with symptoms of recurrent pathology. In these two studies, omission of routine postremoval chest radiograph seemed safe. However, current literature remains insufficient to draw definitive conclusions on this matter, and future studies are needed. LEVEL OF EVIDENCE Systematic review study, level IV

Rapid Response to Remdesivir in Hospitalised COVID-19 Patients:A Propensity Score Weighted Multicentre Cohort Study

Introduction: Remdesivir is a registered treatment for hospitalised patients with COVID-19 that has moderate clinical effectiveness. Anecdotally, some patients’ respiratory insufficiency seemed to recover particularly rapidly after initiation of remdesivir. In this study, we investigated if this rapid improvement was caused by remdesivir, and which patient characteristics might predict a rapid clinical improvement in response to remdesivir. Methods: This was a multicentre observational cohort study of hospitalised patients with COVID-19 who required supplemental oxygen and were treated with dexamethasone. Rapid clinical improvement in response to treatment was defined by a reduction of at least 1 L of supplemental oxygen per minute or discharge from the hospital within 72 h after admission. Inverse probability of treatment-weighted logistic regression modelling was used to assess the association between remdesivir and rapid clinical improvement. Secondary endpoints included in-hospital mortality, ICU admission rate and hospitalisation duration. Results: Of 871 patients included, 445 were treated with remdesivir. There was no influence of remdesivir on the occurrence of rapid clinical improvement (62% vs 61% OR 1.05, 95% CI 0.79–1.40; p = 0.76). The in-hospital mortality was lower (14.7% vs 19.8% OR 0.70, 95% CI 0.48–1.02; p = 0.06) for the remdesivir-treated patients. Rapid clinical improvement occurred more often in patients with low C-reactive protein (≤ 75 mg/L) and short duration of symptoms prior to hospitalisation (&lt; 7 days) (OR 2.84, 95% CI 1.07–7.56). Conclusion: Remdesivir generally does not increase the incidence of rapid clinical improvement in hospitalised patients with COVID-19, but it might have an effect in patients with short duration of symptoms and limited signs of systemic inflammation.</p

What Are Effective Program Characteristics of Self-Management Interventions in Patients With Heart Failure? An Individual Patient Data Meta-analysis

To identify those characteristics of self-management interventions in patients with heart failure (HF) that are effective in influencing health-related quality of life, mortality, and hospitalizations

Designing pragmatic trials—what can we learn from lessons learned?

Pragmatic trials aim to inform clinical decision making by measuring the effect of a treatment in clinical practice. The purpose of the PRECIS-2 tool is to support in designing a truly pragmatic trial. We comment on a study by Forbes et al., who assessed the applicability of the PRECIS-2 tool. The tool will prove particularly useful when implemented in the process of trial design. However, it is yet unclear how e.g., possible dependencies between PRECIS domains, or conducting a pragmatic trial within an existing data registry (e.g., electronic health records) affect the applicability of the tool

Efficient sampling in unmatched case-control studies when the total number of cases and controls is fixed

In the case–control design, statistical efficiency is balanced with practical efficiency. In an unmatched case–control study of a binary exposure, in which the expected odds ratio deviates from the null (i.e. no effect) and the sum of the number of cases and controls is fixed, 1:1 sampling of cases and controls may yield suboptimal statistical efficiency. This holds especially for situations where the exposure is rare and for stronger relationships between the exposure and the outcome under study. The equations presented here may provide researchers with a simple and efficient strategy for sampling cases and controls when designing an unmatched case–control study for such a situation

Designing pragmatic trials—what can we learn from lessons learned?

Pragmatic trials aim to inform clinical decision making by measuring the effect of a treatment in clinical practice. The purpose of the PRECIS-2 tool is to support in designing a truly pragmatic trial. We comment on a study by Forbes et al., who assessed the applicability of the PRECIS-2 tool. The tool will prove particularly useful when implemented in the process of trial design. However, it is yet unclear how e.g., possible dependencies between PRECIS domains, or conducting a pragmatic trial within an existing data registry (e.g., electronic health records) affect the applicability of the tool

Designing pragmatic trials—what can we learn from lessons learned?

Pragmatic trials aim to inform clinical decision making by measuring the effect of a treatment in clinical practice. The purpose of the PRECIS-2 tool is to support in designing a truly pragmatic trial. We comment on a study by Forbes et al., who assessed the applicability of the PRECIS-2 tool. The tool will prove particularly useful when implemented in the process of trial design. However, it is yet unclear how e.g., possible dependencies between PRECIS domains, or conducting a pragmatic trial within an existing data registry (e.g., electronic health records) affect the applicability of the tool