Long-term effects on clinical event, mental health, and related outcomes of CPAP for obstructive sleep apnea: a systematic review.

STUDY OBJECTIVES: Systematic review of long-term health outcomes of continuous positive airway pressure (CPAP) use in adults with obstructive sleep apnea. METHODS: We updated prior systematic reviews with searches in multiple databases through January 3, 2023. We included randomized controlled trials (RCTs) and adjusted nonrandomized comparative studies (NRCSs) that reported specified long-term (mostly >1 year) health outcomes. We assessed risk of bias, conducted meta-analyses, and evaluated strength of evidence. RESULTS: We found 38 eligible studies (16 trials, 28 observational). All conclusions were of low strength of evidence given study and data limitations. RCTs found no evidence of effect of CPAP on mortality (summary effect size [ES] 0.89; 95% CI 0.66, 1.21); inclusion of adjusted NRCSs yields an association with reduced risk of death (ES 0.57; 95% CI 0.44, 0.73). RCTs found no evidence of effects of CPAP for cardiovascular death (ES 0.99; 95% CI 0.64, 1.53), stroke (ES 0.99; 95% CI 0.73, 1.35), myocardial infarction (ES 1.05; 95% CI 0.78, 1.41), incident atrial fibrillation (ES 0.89; 95% CI 0.48, 1.63), and composite cardiovascular outcomes (all statistically nonsignificant). RCTs found no evidence of effects for incident diabetes (ES 1.02; 95% CI 0.69, 1.51) and accidents (all nonsignificant), and no clinically significant effects on depressive symptoms, anxiety symptoms, or cognitive function. CONCLUSIONS: Whether CPAP use for obstructive sleep apnea affects long-term health outcomes remains largely unanswered. RCTs and NRCSs are inconsistent regarding the effect of CPAP on mortality. Current studies are underpowered, with relatively short duration follow-up and methodological limitations.

Protocols to reduce seclusion in inpatient mental health units.

The use of seclusion to manage conflict behaviours in psychiatric inpatient settings is increasingly viewed as an intervention of last resort. Many protocols have, thus, been developed to reduce the practice. We conducted a systematic review to determine the effectiveness of protocols to reduce seclusion on process outcomes (e.g., seclusion, restraint), patient outcomes (e.g., injuries, aggressive incidents, satisfaction), and staff outcomes (e.g., injuries, satisfaction). We searched Medline, Embase, the Cochrane Register of Clinical Trials, PsycINFO, CINAHL, cairn.info, and ClinicalTrials.gov for protocols to reduce seclusion practices for adult patients on inpatient mental health units (from inception to September 6, 2022). We summarised and categorised reported elements of the protocols designed to reduce seclusion using the Behaviour Change Wheel Intervention Functions and resources needed to implement the protocol in psychiatric units. We assessed risk of bias and determined certainty of evidence using GRADE. Forty-eight reports addressed five approaches to reduce seclusion: hospital/unit restructuring (N = 4), staff education/training (N = 3), sensory modulation rooms (N = 7), risk assessment and management protocols (N = 7), and comprehensive/mixed interventions (N = 22; N = 6 without empirical data). The relationship between the various protocols and outcomes was mixed. Psychiatric units that implement architecturally positive designs, sensory rooms, the Brøset Violence Checklist, and various multi-component comprehensive interventions may reduce seclusion events, though our certainty in these findings is low due to studies' methodological limitations. Future research and practice may benefit from standardised reporting of process and outcome measures and analyses that account for confounders.

Evidence Synthesis for Complex Interventions Using Meta-Regression Models.

A goal of evidence synthesis for trials of complex interventions is to inform the design or implementation of novel versions of complex interventions by predicting expected outcomes with each intervention version. Conventional aggregate data meta-analyses of studies comparing complex interventions have limited ability to provide such information. We argue that evidence synthesis for trials of complex interventions should forgo aspirations of estimating causal effects and instead model the response surface of study results to 1) summarize the available evidence and 2) predict the average outcomes of future studies or in new settings. We illustrate this modeling approach using data from a systematic review of diabetes quality improvement (QI) interventions involving at least 1 of 12 QI strategy components. We specify a series of meta-regression models to assess the association of specific components with the posttreatment outcome mean and compare the results to conventional meta-analysis approaches. Compared with conventional approaches, modeling the response surface of study results can better reflect the associations between intervention components and study characteristics with the posttreatment outcome mean. Modeling study results using a response surface approach offers a useful and feasible goal for evidence synthesis of complex interventions that rely on aggregate data.

Efficacy and safety of ketamine-assisted electroconvulsive therapy in major depressive episode: a systematic review and network meta-analysis.

OBJECTIVE: To meta-analyze clinical efficacy and safety of ketamine compared with other anesthetic agents in the course of electroconvulsive therapy (ECT) in major depressive episode (MDE). METHODS: PubMed/MEDLINE, Cochrane Library, Embase, GoogleScholar, and US and European trial registries were searched from inception through May 23, 2023, with no language limits. We included RCTs with (1) a diagnosis of MDE; (2) ECT intervention with ketamine and/or other anesthetic agents; and (3) measures included: depressive symptoms, cognitive performance, remission or response rates, and serious adverse events. Network meta-analysis (NMA) was performed to compare ketamine and 7 other anesthetic agents. Hedges' g standardized mean differences (SMDs) were used for continuous measures, and relative risks (RRs) were used for other binary outcomes using random-effects models. RESULTS: Twenty-two studies were included in the systematic review. A total of 2322 patients from 17 RCTs were included in the NMA. The overall pooled SMD of ketamine, as compared with propofol as a reference group, was -2.21 (95% confidence interval [CI], -3.79 to -0.64) in depressive symptoms, indicating that ketamine had better antidepressant efficacy than propofol. In a sensitivity analysis, however, ketamine-treated patients had a worse outcome in cognitive performance than propofol-treated patients (SMD, -0.18; 95% CI, -0.28 to -0.09). No other statistically significant differences were found. CONCLUSIONS: Ketamine-assisted ECT is tolerable and may be efficacious in improving depressive symptoms, but a relative adverse impact on cognition may be an important clinical consideration. Anesthetic agents should be considered based on patient profiles and/or preferences to improve effectiveness and safety of ECT use.

Approaches to developing de novo cancer population models to examine questions about cancer and race in bladder, gastric, and endometrial cancer and multiple myeloma: the Cancer Intervention and Surveillance Modeling Network incubator program.

BACKGROUND: We are developing 10 de novo population-level mathematical models in 4 malignancies (multiple myeloma and bladder, gastric, and uterine cancers). Each of these sites has documented disparities in outcome that are believed to be downstream effects of systemic racism. METHODS: Ten models are being independently developed as part of the Cancer Intervention and Surveillance Modeling Network incubator program. These models simulate trends in cancer incidence, early diagnosis, treatment, and mortality for the general population and are stratified by racial subgroup. Model inputs are based on large population datasets, clinical trials, and observational studies. Some core parameters are shared, and other parameters are model specific. All models are microsimulation models that use self-reported race to stratify model inputs. They can simulate the distribution of relevant risk factors (eg, smoking, obesity) and insurance status (for multiple myeloma and uterine cancer) in US birth cohorts and population. DISCUSSION: The models aim to refine approaches in prevention, detection, and management of 4 cancers given uncertainties and constraints. They will help explore whether the observed racial disparities are explainable by inequities, assess the effects of existing and potential cancer prevention and control policies on health equity and disparities, and identify policies that balance efficiency and fairness in decreasing cancer mortality.

Efficacy and Safety of Ketamine-assisted Electroconvulsive Therapy in Major Depressive Episode: A Systematic Review and Network Meta-Analysis.

Objective: To meta-analyze clinical efficacy and safety of ketamine compared with other anesthetic agents in the course of electroconvulsive therapy (ECT) in major depressive episode (MDE). Methods: PubMed/MEDLINE, Cochrane Library, Embase, GoogleScholar, and US and European trial registries were searched from inception through May 23, 2023, with no language limits. We included RCTs with (1) a diagnosis of MDE; (2) ECT intervention with ketamine and/or other anesthetic agents; and (3) measures included: depressive symptoms, cognitive performance, remission or response rates, and serious adverse events. Network meta-analysis (NMA) was performed to compare ketamine and 7 other anesthetic agents. Hedges' g standardized mean differences (SMDs) were used for continuous measures, and relative risks (RRs) were used for other binary outcomes using random-effects models. Results: Twenty-two studies were included in the systematic review. A total of 2,322 patients from 17 RCTs were included in the NMA. The overall pooled SMD of ketamine, as compared with a propofol reference group, was -2.21 (95% confidence interval [CI], -3.79 to -0.64) in depressive symptoms, indicating that ketamine had better antidepressant efficacy than propofol. In a sensitivity analysis, however, ketamine-treated patients had a worse outcome in cognitive performance than propofol-treated patients (SMD, -0.18; 95% CI, -0.28 to -0.09). No other statistically significant differences were found. Conclusions: Ketamine-assisted ECT is tolerable and may be efficacious in improving depressive symptoms, but a relative adverse impact on cognition may be an important clinical consideration. Anesthetic agents should be considered based on patient profiles and/or preferences to improve effectiveness and safety of ECT use.

Multi-state network meta-analysis of progression and survival data.

Multiple randomized controlled trials, each comparing a subset of competing interventions, can be synthesized by means of a network meta-analysis to estimate relative treatment effects between all interventions in the evidence base. Here we focus on estimating relative treatment effects for time-to-event outcomes. Cancer treatment effectiveness is frequently quantified by analyzing overall survival (OS) and progression-free survival (PFS). We introduce a method for the joint network meta-analysis of PFS and OS that is based on a time-inhomogeneous tri-state (stable, progression, and death) Markov model where time-varying transition rates and relative treatment effects are modeled with parametric survival functions or fractional polynomials. The data needed to run these analyses can be extracted directly from published survival curves. We demonstrate use by applying the methodology to a network of trials for the treatment of non-small-cell lung cancer. The proposed approach allows the joint synthesis of OS and PFS, relaxes the proportional hazards assumption, extends to a network of more than two treatments, and simplifies the parameterization of decision and cost-effectiveness analyses.

Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes.

BACKGROUND: There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations. OBJECTIVES: To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care. SEARCH METHODS: We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section. SELECTION CRITERIA: We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy. DATA COLLECTION AND ANALYSIS: We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors.  Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available. MAIN RESULTS: We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted.  Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three.  Combinations of the three most effective QI strategies were estimated to lead to the below effects:  - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%;  - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg;  - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other). AUTHORS' CONCLUSIONS: There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.

Vitamin D and Risk for Type 2 Diabetes in People With Prediabetes : A Systematic Review and Meta-analysis of Individual Participant Data From 3 Randomized Clinical Trials.

BACKGROUND: The role of vitamin D in people who are at risk for type 2 diabetes remains unclear. PURPOSE: To evaluate whether administration of vitamin D decreases risk for diabetes among people with prediabetes. DATA SOURCES: PubMed, Embase, and ClinicalTrials.gov from database inception through 9 December 2022. STUDY SELECTION: Eligible trials that were specifically designed and conducted to test the effects of oral vitamin D versus placebo on new-onset diabetes in adults with prediabetes. DATA EXTRACTION: The primary outcome was time to event for new-onset diabetes. Secondary outcomes were regression to normal glucose regulation and adverse events. Prespecified analyses (both unadjusted and adjusted for key baseline variables) were conducted according to the intention-to-treat principle. DATA SYNTHESIS: Three randomized trials were included, which tested cholecalciferol, 20 000 IU (500 mcg) weekly; cholecalciferol, 4000 IU (100 mcg) daily; or eldecalcitol, 0.75 mcg daily, versus matching placebos. Trials were at low risk of bias. Vitamin D reduced risk for diabetes by 15% (hazard ratio, 0.85 [95% CI, 0.75 to 0.96]) in adjusted analyses, with a 3-year absolute risk reduction of 3.3% (CI, 0.6% to 6.0%). The effect of vitamin D did not differ in prespecified subgroups. Among participants assigned to the vitamin D group who maintained an intratrial mean serum 25-hydroxyvitamin D level of at least 125 nmol/L (≥50 ng/mL) compared with 50 to 74 nmol/L (20 to 29 ng/mL) during follow-up, cholecalciferol reduced risk for diabetes by 76% (hazard ratio, 0.24 [CI, 0.16 to 0.36]), with a 3-year absolute risk reduction of 18.1% (CI, 11.7% to 24.6%). Vitamin D increased the likelihood of regression to normal glucose regulation by 30% (rate ratio, 1.30 [CI, 1.16 to 1.46]). There was no evidence of difference in the rate ratios for adverse events (kidney stones: 1.17 [CI, 0.69 to 1.99]; hypercalcemia: 2.34 [CI, 0.83 to 6.66]; hypercalciuria: 1.65 [CI, 0.83 to 3.28]; death: 0.85 [CI, 0.31 to 2.36]). LIMITATIONS: Studies of people with prediabetes do not apply to the general population. Trials may not have been powered for safety outcomes. CONCLUSION: In adults with prediabetes, vitamin D was effective in decreasing risk for diabetes. PRIMARY FUNDING SOURCE: None. (PROSPERO: CRD42020163522).

Patient-centred outcomes of imaging tests: recommendations for patients, clinicians and researchers.

BACKGROUND: Imaging tests are one of the most frequently used diagnostic modalities in healthcare, but the benefits of their direct impacts on clinical decision-making have been countered by concerns that they can be overused. Assessing the relative value of imaging tests has largely focused on measures of test accuracy, which overlooks more comprehensive benefits and risks of imaging tests, particularly their impact on patient-centred outcomes (PCOs). We present the findings of the Patient Reported Outcomes of Diagnostics (PROD) research study in response to a methodological gap in the area of diagnostic test comparative effectiveness research. METHODS: Over a 3-year period, the PROD Study engaged with multiple stakeholders to identify existing conceptual models related to PCOs for imaging testing, conducted primary research and evidence synthesis, and developed consensus recommendations to describe and categorise PCOs related to imaging testing. RESULTS: The PROD framework categorises PCOs from imaging studies within four main domains: information or knowledge yielded, physical impact, emotional outcomes and test burden. PCOs interact with each other and influence effects across domains, and can be modified by factors related to the patient, clinical situation, healthcare team and the testing environment. CONCLUSIONS: Using PCOs to inform healthcare decision-making will require ways of collating and presenting information on PCOs in ways that can inform patient-provider decision-making, and developing methods to determine the relative importance of outcomes (including test accuracy) to one another.

Comparison of Low-Value Care Among Commercial and Medicaid Enrollees.

BACKGROUND: Low-value healthcare is costly and inefficient and may adversely affect patient outcomes. Despite increases in low-value service use, little is known about how the receipt of low-value care differs across payers. OBJECTIVE: To evaluate differences in the use of low-value care between patients with commercial versus Medicaid coverage. DESIGN: Retrospective observational analysis of the 2017 Rhode Island All-payer Claims Database, estimating the probability of receiving each of 14 low-value services between commercial and Medicaid enrollees, adjusting for patient sociodemographic and clinical characteristics. Ensemble machine learning minimized the possibility of model misspecification. PARTICIPANTS: Medicaid and commercial enrollees aged 18-64 with continuous coverage and an encounter at which they were at risk of receiving a low-value service. INTERVENTION: Enrollment in Medicaid or Commercial insurance. MAIN MEASURES: Use of one of 14 validated measures of low-value care. KEY RESULTS: Among 110,609 patients, Medicaid enrollees were younger, had more comorbidities, and were more likely to be female than commercial enrollees. Medicaid enrollees had higher rates of use for 7 low-value care measures, and those with commercial coverage had higher rates for 5 measures. Across all measures of low-value care, commercial enrollees received more (risk difference [RD] 6.8 percentage points; CI: 6.6 to 7.0) low-value services than their counterparts with Medicaid. Commercial enrollees were also more likely to receive low-value services typically performed in the emergency room (RD 11.4 percentage points; CI: 10.7 to 12.2) and services that were less expensive (RD 15.3 percentage points; CI 14.6 to 16.0). CONCLUSION: Differences in the provision of low-value care varied across measures, though average use was slightly higher among commercial than Medicaid enrollees. This difference was more pronounced for less expensive services indicating that financial incentives may not be the sole driver of low-value care.

In a pilot study, automated real-time systematic review updates were feasible, accurate, and work-saving.

OBJECTIVES: The aim of this study is to describe and pilot a novel method for continuously identifying newly published trials relevant to a systematic review, enabled by combining artificial intelligence (AI) with human expertise. STUDY DESIGN AND SETTING: We used RobotReviewer LIVE to keep a review of COVID-19 vaccination trials updated from February to August 2021. We compared the papers identified by the system with those found by the conventional manual process by the review team. RESULTS: The manual update searches (last search date July 2021) retrieved 135 abstracts, of which 31 were included after screening (23% precision, 100% recall). By the same date, the automated system retrieved 56 abstracts, of which 31 were included after manual screening (55% precision, 100% recall). Key limitations of the system include that it is limited to searches of PubMed/MEDLINE, and considers only randomized controlled trial reports. We aim to address these limitations in future. The system is available as open-source software for further piloting and evaluation. CONCLUSION: Our system identified all relevant studies, reduced manual screening work, and enabled rolling updates on publication of new primary research.

Scientific Inference Does Not Rest on Statistical Testing.

The Strategic Timing of AntiRetroviral Treatment (START) trial found that in patients with HIV and CD4+ cell counts above 500 cells/mm3 who had not previously received treatment, immediate initiation of antiretroviral therapy reduced the risk of serious adverse outcomes compared with delaying treatment initiation only when the CD4+ cell count fell below 350 cells/mm3.1 After the trial's completion, people with HIV not receiving therapy were offered the opportunity to start it without regard to their CD4+ cell count. In this issue of NEJM Evidence, the START group reports data from an additional 5 years of follow-up.2.

Intensive Care Based Interventions to Reduce Family Member Stress Disorders: A Systematic Review of the Literature.

Background: Increasing awareness of the emotional impact of an Intensive Care Unit (ICU) hospitalization on patients and their families has led to a rise in studies seeking to mitigate Post Intensive Care Syndrome (PICS) for both groups. In efforts to decrease symptoms of anxiety and depression, ICUs have implemented a variety of programs to reduce family distress. Methods: We conducted a systematic review of experimental studies which aimed to reduce stress related disorders in family members after the experience of having a patient admitted to the ICU. Multiple databases were searched for randomized controlled trials or nonrandomized comparative trials which targeted family members or surrogate decision makers. A total of 17 studies were identified for inclusion in the review representing 3471 participants. Results: We describe those interventions which we qualitatively assigned as "not passive," or those which actively engaged the family to express themselves, as more likely to be successful in both the available pediatric and adult literature than interventions which we identified as "passive." Studies which described active engagement of family members demonstrated comparative improvements in symptoms of depression, anxiety, and PTSD, as well as reduced hospital costs in the case of two studies. Discussion: This review may serve to aid in the development of future interventions targeted at reducing family stress and PICS following an ICU hospitalization.

Multivariate meta-analysis of multiple outcomes: characteristics and predictors of borrowing of strength from Cochrane reviews.

OBJECTIVES: Multivariate meta-analysis allows the joint synthesis of multiple outcomes accounting for their correlation. This enables borrowing of strength (BoS) across outcomes, which may lead to greater efficiency and even different conclusions compared to separate univariate meta-analyses. However, multivariate meta-analysis is complex to apply, so guidance is needed to flag (in advance of analysis) when the approach is most useful. STUDY DESIGN AND SETTING: We use 43 Cochrane intervention reviews to empirically investigate the characteristics of meta-analysis datasets that are associated with a larger BoS statistic (from 0 to 100%) when applying a bivariate meta-analysis of binary outcomes. RESULTS: Four characteristics were identified as strongly associated with BoS: the total number of studies, the number of studies with the outcome of interest, the percentage of studies missing the outcome of interest, and the largest absolute within-study correlation. Using these characteristics, we then develop a model for predicting BoS in a new dataset, which is shown to have good performance (an adjusted R2 of 50%). Applied examples are used to illustrate the use of the BoS prediction model. CONCLUSIONS: Cochrane reviewers mainly use univariate meta-analysis methods, but the identified characteristics associated with BoS and our subsequent prediction model for BoS help to flag when a multivariate meta-analysis may also be beneficial in Cochrane reviews with multiple binary outcomes. Extension to non-Cochrane reviews and other outcome types is still required.

A novel tool that allows interactive screening of PubMed citations showed promise for the semi-automation of identification of Biomedical Literature.

BACKGROUND AND OBJECTIVES: Systematic reviews form the basis of evidence-based medicine, but are expensive and time-consuming to produce. To address this burden, we have developed a literature identification system (Pythia) that combines the query formulation and citation screening steps. METHODS: Pythia incorporates a set of natural-language questions with machine-learning algorithms to rank all PubMed citations based on relevance, returning the 100 top-ranked citations for human screening. The tagged citations are iteratively exploited by Pythia to refine the search and re-rank the citations. RESULTS: Across seven systematic reviews, the ability of Pythia to identify the relevant citations (sensitivity) ranged from 0.09 to 0.58. The number of abstracts reviewed per relevant abstract number needed to read (NNR) was lower than in the manually screened project in four reviews, higher in two, and had mixed results in one. The reviews that had greater overall sensitivity retrieved more relevant citations in early batches, but retrieval was generally unaffected by other aspects, such as study design, study size, and specific key question. CONCLUSION: Due to its low sensitivity, Pythia is not ready for widespread use. Future research should explore ways to encode domain knowledge in query formulation to better enrich the questions used in the search.

Assessments of the Value of New Interventions Should Include Health Equity Impact.

A formal evaluation of the health equity impact of a new intervention is hardly ever performed as part of a health technology assessment to understand its value. This should change, in our view. An evidence-based quantitative assessment of the health equity impact can help decision makers develop coverage policies, programme designs, and quality initiatives focused on optimizing both total health and health equity given the treatment options available. We outline the conceptual basis of how a new intervention can impact health equity and adopt distributional cost-effectiveness analysis based on decision-analytic models to assess this quantitatively, using a newly US FDA-approved drug for Alzheimer's disease (aducanumab) as an example. We argue that gaps in the evidence base for the new intervention, for example, due to limited clinical research participation among racial and ethnic minority groups, do not preclude such an evaluation. Understanding these uncertainties has implications for fair pricing, decision making, and future research. If we are serious about population-level decision making that not only is focused on improving total health but also aims to improve health equity, we should consider routinely assessing the health equity impact of new interventions.

Self-Repetition in Abstractive Neural Summarizers.

We provide a quantitative and qualitative analysis of self-repetition in the output of neural summarizers. We measure self-repetition as the number of n-grams of length four or longer that appear in multiple outputs of the same system. We analyze the behavior of three popular architectures (BART, T5 and Pegasus), fine-tuned on five datasets. In a regression analysis, we find that the three architectures have different propensities for repeating content across output summaries for inputs, with BART being particularly prone to self-repetition. Fine-tuning on more abstractive data, and on data featuring formulaic language, is associated with a higher rate of self-repetition. In qualitative analysis we find systems produce artefacts such as ads and disclaimers unrelated to the content being summarized, as well as formulaic phrases common in the fine-tuning domain. Our approach to corpus level analysis of self-repetition may help practitioners clean up training data for summarizers and ultimately support methods for minimizing the amount of self-repetition.