An empirical evaluation of the impact scenario of pooling bodies of evidence from randomized controlled trials and cohort studies in medical research

Are e-Health Interventions Effective in Reducing Diabetes-Related Distress and Depression in Patients with Type 2 Diabetes? A Systematic Review with Meta-Analysis

Background: e-Health refers to any health care service delivered through the internet or related technologies, to improve quality of life. Despite the increasing use of e-health interventions to manage type 2 diabetes (T2D), there is a lack of evidence about the effectiveness on diabetes distress and depression, which are common issues in those living with T2D. Purpose: To synthesize and determine the effects of e-health interventions on diabetes distress and depression among patients with T2D. Methods: We systematically searched PubMed, Scopus, Cochrane CENTRAL, and Web of Science for randomized controlled trials (RCTs), non-RCTs and observational cohort studies for the effects of e-health interventions on diabetes distress and depression in patients with T2D up to September 14, 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 recommendations were followed. The risk of bias was assessed according to the Risk-of-Bias 2 tool (RCTs), the Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I) (non-RCTs) and the National Institute of Health tool (observational). The standardized mean difference (SMD) and its related 95% confidence intervals (CIs) were estimated with the DerSimonian-Laird method through random-effect models. A pooled raw mean difference (MD) meta-analysis was conducted for RCTs comparing the effects of e-health versus control on diabetes distress screening to display the clinical impact. Results: A total of 41 studies (24 RCTs, 14 non-RCTs, and 3 observational) involving 8,667 individuals were included. The pooled SMD for the effect of e-health versus the control group on diabetes distress was -0.14 (95% CI = -0.24 to -0.04; I2 = 23.9%; n = 10 studies), being -0.06 (95% CI = -0.15 to 0.02; I2 = 7.8%; n = 16 studies) for depression. The pooled raw MD on diabetes distress screening showed a reduction of -0.54 points (95% CI = -0.81 to -0.27; I2 = 85.1%; n = 7 studies). Conclusion: e-Health interventions are effective in diminishing diabetes distress among adults with T2D, inducing clinically meaningful reductions.

Impact of different surgical and non-surgical interventions on health-related quality of life after thoracolumbar burst fractures without neurological deficit: protocol for a comprehensive systematic review with network meta-analysis

INTRODUCTION

There is no international consensus on how to treat thoracolumbar burst fractures (TLBFs) without neurological deficits. The planned systematic review with network meta-analyses (NMA) aims to compare the effects on treatment outcomes, focusing on midterm health-related quality of life (HRQoL).

METHODS AND ANALYSIS

We will conduct a comprehensive and systematic literature search, identifying studies comparing two or more treatment modalities. We will search MEDLINE, EMBASE, Google Scholar, Scopus and Web of Science from January 2000 until July 2023 for publications. We will include (randomised and non-randomised) controlled clinical trials assessing surgical and non-surgical treatment methods for adults with TLBF. Screening of references, data extraction and risk of bias (RoB) assessment will be done independently by two reviewers. We will extract relevant studies, participants and intervention characteristics. The RoB will be assessed using the revised Cochrane RoB V.2.0 tool for randomised trials and the Newcastle-Ottawa Scale for controlled trials. The OR for dichotomous data and standardised mean differences for continuous data will be presented with their respective 95% CIs. We will conduct a random-effects NMA to assess the treatments and determine the superiority of the therapeutic approaches. Our primary outcomes will be midterm (6 months to 2 years after injury) overall HRQoL and pain. Secondary outcomes will include radiological or clinical findings. We will present network graphs, forest plots and relative rankings on plotted rankograms corresponding to the treatment rank probabilities. The ranking results will be represented by the area under the cumulative ranking curve. Analyses will be performed in Stata V.16.1 and R. The quality of the evidence will be evaluated according to the Grading of Recommendations, Assessment, Development and Evaluations framework.

ETHICS AND DISSEMINATION

Ethical approval is not required. The research will be published in a peer-reviewed journal.

Evaluating the impact of including non-randomised studies of interventions in meta-analysis of randomised controlled trials: a protocol for a meta-epidemiological study

INTRODUCTION

Although interest in including non-randomised studies of interventions (NRSIs) in meta-analysis of randomised controlled trials (RCTs) is growing, estimates of effectiveness obtained from NRSIs are vulnerable to greater bias than RCTs. The objectives of this study are to: (1) explore how NRSIs can be integrated into a meta-analysis of RCTs; (2) assess concordance of the evidence from non-randomised and randomised trials and explore factors associated with agreement; and (3) investigate the impact on estimates of pooled bodies of evidence when NRSIs are included.

METHODS AND ANALYSIS

We will conduct a systematic survey of 210 systematic reviews that include both RCTs and NRSIs, published from 2017 to 2022. We will randomly select reviews, stratified in a 1:1 ratio by Core vs non-Core clinical journals, as defined by the National Library of Medicine. Teams of paired reviewers will independently determine eligibility and abstract data using standardised, pilot-tested forms. The concordance of the evidence will be assessed by exploring agreement in the relative effect reported by NRSIs and RCT addressing the same clinical question, defined as similarity of the population, intervention/exposure, control and outcomes. We will conduct univariable and multivariable logistic regression analyses to examine the association of prespecified study characteristics with agreement in the estimates between NRSIs and RCTs. We will calculate the ratio of the relative effect estimate from NRSIs over that from RCTs, along with the corresponding 95% CI. We will use a bias-corrected meta-analysis model to investigate the influence on pooled estimates when NRSIs are included in the evidence synthesis.

ETHICS AND DISSEMINATION

Ethics approval is not required. The findings of this study will be disseminated through peer-reviewed publications, conference presentations and condensed summaries for clinicians, health policymakers and guideline developers regarding the design, conduct, analysis, and interpretation of meta-analysis that integrate RCTs and NRSIs.

Editorial Commentary: Autologous and Synthetic Bone Fillers for Medial Open-Wedge High Tibial Osteotomy Have No Effect on Clinical Outcomes But Autologous Graft Promotes Complete Bony Union

In contrast to closed-wedge high tibial osteotomy, medial based open-wedge high tibial osteotomy produces gaps of various sizes. Synthetic bone void fillers are an attractive option to close these gaps, potentially increase bone union, decrease time to union, and improve clinical outcomes. Autologous bone grafts are the accepted standard and result in reliable and reproducible outcomes. However, harvesting of autologous bone requires an additional procedure and is associated with potential complications. The use of synthetic bone void fillers could theoretically avoid these issues and reduce operating times. The current evidence suggests that autologous bone grafting has higher union rates but is not associated with better clinical and functional outcomes. Unfortunately, the certainty of evidence to support the use of bone void fillers is low, and the question of whether bone grafting of the gap should be performed in medial based open-wedge high tibial osteotomies cannot be answered with confidence.

Effectiveness, quality and implementation of pain, sedation, delirium, and iatrogenic withdrawal syndrome algorithms in pediatric intensive care: a systematic review and meta-analysis

Background

Pain, sedation, delirium, and iatrogenic withdrawal syndrome are conditions that often coexist, algorithms can be used to assist healthcare professionals in decision making. However, a comprehensive review is lacking. This systematic review aimed to assess the effectiveness, quality, and implementation of algorithms for the management of pain, sedation, delirium, and iatrogenic withdrawal syndrome in all pediatric intensive care settings.

Methods

A literature search was conducted on November 29, 2022, in PubMed, Embase, CINAHL and Cochrane Library, ProQuest Dissertations & Theses, and Google Scholar to identify algorithms implemented in pediatric intensive care and published since 2005. Three reviewers independently screened the records for inclusion, verified and extracted data. Included studies were assessed for risk of bias using the JBI checklists, and algorithm quality was assessed using the PROFILE tool (higher % = higher quality). Meta-analyses were performed to compare algorithms to usual care on various outcomes (length of stay, duration and cumulative dose of analgesics and sedatives, length of mechanical ventilation, and incidence of withdrawal).

Results

From 6,779 records, 32 studies, including 28 algorithms, were included. The majority of algorithms (68%) focused on sedation in combination with other conditions. Risk of bias was low in 28 studies. The average overall quality score of the algorithm was 54%, with 11 (39%) scoring as high quality. Four algorithms used clinical practice guidelines during development. The use of algorithms was found to be effective in reducing length of stay (intensive care and hospital), length of mechanical ventilation, duration of analgesic and sedative medications, cumulative dose of analgesics and sedatives, and incidence of withdrawal. Implementation strategies included education and distribution of materials (95%). Supportive determinants of algorithm implementation included leadership support and buy-in, staff training, and integration into electronic health records. The fidelity to algorithm varied from 8.2% to 100%.

Conclusions

The review suggests that algorithm-based management of pain, sedation and withdrawal is more effective than usual care in pediatric intensive care settings. There is a need for more rigorous use of evidence in the development of algorithms and the provision of details on the implementation process.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021276053, PROSPERO [CRD42021276053].