scholarly journals Predicting recurrent atrial fibrillation after catheter ablation: a systematic review of prognostic models

EP Europace ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 748-760 ◽  
Author(s):  
Janine Dretzke ◽  
Naomi Chuchu ◽  
Ridhi Agarwal ◽  
Clare Herd ◽  
Winnie Chua ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Systematic Review ◽  
Catheter Ablation ◽  
Assessment Tool ◽  
Model Performance ◽  
Risk Of Bias ◽  
Prognostic Models ◽  
Risk Scores ◽  
Bibliographic Databases ◽  
Recurrent Atrial Fibrillation

Abstract Aims We assessed the performance of modelsf (risk scores) for predicting recurrence of atrial fibrillation (AF) in patients who have undergone catheter ablation. Methods and results Systematic searches of bibliographic databases were conducted (November 2018). Studies were eligible for inclusion if they reported the development, validation, or impact assessment of a model for predicting AF recurrence after ablation. Model performance (discrimination and calibration) measures were extracted. The Prediction Study Risk of Bias Assessment Tool (PROBAST) was used to assess risk of bias. Meta-analysis was not feasible due to clinical and methodological differences between studies, but c-statistics were presented in forest plots. Thirty-three studies developing or validating 13 models were included; eight studies compared two or more models. Common model variables were left atrial parameters, type of AF, and age. Model discriminatory ability was highly variable and no model had consistently poor or good performance. Most studies did not assess model calibration. The main risk of bias concern was the lack of internal validation which may have resulted in overly optimistic and/or biased model performance estimates. No model impact studies were identified. Conclusion Our systematic review suggests that clinical risk prediction of AF after ablation has potential, but there remains a need for robust evaluation of risk factors and development of risk scores.

scholarly journals Prognostic models for predicting in-hospital paediatric mortality in resource-limited countries: a systematic review

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e035045
Author(s):  
Morris Ogero ◽  
Rachel Jelagat Sarguta ◽  
Lucas Malla ◽  
Jalemba Aluvaala ◽  
Ambrose Agweyu ◽  
...  
Keyword(s):  
Systematic Review ◽  
Low Income ◽  
Assessment Tool ◽  
Data Extraction ◽  
Model Development ◽  
Risk Of Bias ◽  
Prognostic Models ◽  
Risk Scores ◽  
Eligibility Criteria ◽  
Bias Assessment

ObjectivesTo identify and appraise the methodological rigour of multivariable prognostic models predicting in-hospital paediatric mortality in low-income and middle-income countries (LMICs).DesignSystematic review of peer-reviewed journals.Data sourcesMEDLINE, CINAHL, Google Scholar and Web of Science electronic databases since inception to August 2019.Eligibility criteriaWe included model development studies predicting in-hospital paediatric mortality in LMIC.Data extraction and synthesisThis systematic review followed the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies framework. The risk of bias assessment was conducted using Prediction model Risk of Bias Assessment Tool (PROBAST). No quantitative summary was conducted due to substantial heterogeneity that was observed after assessing the studies included.ResultsOur search strategy identified a total of 4054 unique articles. Among these, 3545 articles were excluded after review of titles and abstracts as they covered non-relevant topics. Full texts of 509 articles were screened for eligibility, of which 15 studies reporting 21 models met the eligibility criteria. Based on the PROBAST tool, risk of bias was assessed in four domains; participant, predictors, outcome and analyses. The domain of statistical analyses was the main area of concern where none of the included models was judged to be of low risk of bias.ConclusionThis review identified 21 models predicting in-hospital paediatric mortality in LMIC. However, most reports characterising these models are of poor quality when judged against recent reporting standards due to a high risk of bias. Future studies should adhere to standardised methodological criteria and progress from identifying new risk scores to validating or adapting existing scores.PROSPERO registration numberCRD42018088599.

scholarly journals Prediction Models for Future High-Need High-Cost Healthcare Use: a Systematic Review

2022 ◽  
Author(s):  
Ursula W. de Ruijter ◽  
Z. L. Rana Kaplan ◽  
Wichor M. Bramer ◽  
Frank Eijkenaar ◽  
Daan Nieboer ◽  
...  
Keyword(s):  
Systematic Review ◽  
Care Management ◽  
Prediction Models ◽  
Assessment Tool ◽  
Meta Analysis ◽  
Model Performance ◽  
Case Finding ◽  
Risk Of Bias ◽  
Prognostic Models ◽  
Healthcare Use

Abstract Background In an effort to improve both quality of care and cost-effectiveness, various care-management programmes have been developed for high-need high-cost (HNHC) patients. Early identification of patients at risk of becoming HNHC (i.e. case finding) is crucial to a programme’s success. We aim to systematically identify prediction models predicting future HNHC healthcare use in adults, to describe their predictive performance and to assess their applicability. Methods Ovid MEDLINE® All, EMBASE, CINAHL, Web of Science and Google Scholar were systematically searched from inception through January 31, 2021. Risk of bias and methodological quality assessment was performed through the Prediction model Risk Of Bias Assessment Tool (PROBAST). Results Of 5890 studies, 60 studies met inclusion criteria. Within these studies, 313 unique models were presented using a median development cohort size of 20,248 patients (IQR 5601–174,242). Predictors were derived from a combination of data sources, most often claims data (n = 37; 62%) and patient survey data (n = 29; 48%). Most studies (n = 36; 60%) estimated patients’ risk to become part of some top percentage of the cost distribution (top-1–20%) within a mean time horizon of 16 months (range 12–60). Five studies (8%) predicted HNHC persistence over multiple years. Model validation was performed in 45 studies (76%). Model performance in terms of both calibration and discrimination was reported in 14 studies (23%). Overall risk of bias was rated as ‘high’ in 40 studies (67%), mostly due to a ‘high’ risk of bias in the subdomain ‘Analysis’ (n = 37; 62%). Discussion This is the first systematic review (PROSPERO CRD42020164734) of non-proprietary prognostic models predicting HNHC healthcare use. Meta-analysis was not possible due to heterogeneity. Most identified models estimated a patient’s risk to incur high healthcare expenditure during the subsequent year. However, case-finding strategies for HNHC care-management programmes are best informed by a model predicting HNHC persistence. Therefore, future studies should not only focus on validating and extending existing models, but also concentrate on clinical usefulness.

scholarly journals Predicting major adverse cardiovascular events for secondary prevention: protocol for a systematic review and meta-analysis of risk prediction models

BMJ Open ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. e034564
Author(s):  
Ralph K Akyea ◽  
Jo Leonardi-Bee ◽  
Folkert W Asselbergs ◽  
Riyaz S Patel ◽  
Paul Durrington ◽  
...  
Keyword(s):  
Secondary Prevention ◽  
Cardiovascular Events ◽  
Prediction Models ◽  
Assessment Tool ◽  
Meta Analysis ◽  
Risk Of Bias ◽  
Prognostic Models ◽  
Major Adverse Cardiovascular Events ◽  
Bibliographic Databases ◽  
Analysis Model

IntroductionCardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. With advances in early diagnosis and treatment of CVD and increasing life expectancy, more people are surviving initial CVD events. However, models for stratifying disease severity risk in patients with established CVD for effective secondary prevention strategies are inadequate. Multivariable prognostic models to stratify CVD risk may allow personalised treatment interventions. This review aims to systematically review the existing multivariable prognostic models for the recurrence of CVD or major adverse cardiovascular events in adults with established CVD diagnosis.Methods and analysisBibliographic databases (Ovid MEDLINE, EMBASE, PsycINFO and Web of Science) will be searched, from database inception to April 2020, using terms relating to the clinical area and prognosis. A hand search of the reference lists of included studies will also be done to identify additional published studies. No restrictions on language of publications will be applied. Eligible studies present multivariable models (derived or validated) of adults (aged 16 years and over) with an established diagnosis of CVD, reporting at least one of the components of the primary outcome of major adverse cardiovascular events (defined as either coronary heart disease, stroke, peripheral artery disease, heart failure or CVD-related mortality). Reviewing will be done by two reviewers independently using the pre-defined criteria. Data will be extracted for included full-text articles. Risk of bias will be assessed using the Prediction model study Risk Of Bias ASsessment Tool (PROBAST). Prognostic models will be summarised narratively. If a model is tested in multiple validation studies, the predictive performance will be summarised using a random-effects meta-analysis model to account for any between-study heterogeneity.Ethics and disseminationEthics approval is not required. The results of this study will be submitted to relevant conferences for presentation and a peer-reviewed journal for publication.PROSPERO registration numberCRD42019149111.

scholarly journals Prognostic Models in Adults Undergoing Physical Therapy for Rotator Cuff Disorders: Systematic Review

2016 ◽  
Vol 96 (7) ◽  
pp. 961-971 ◽  
Author(s):  
Cordula Braun ◽  
Nigel C. Hanchard ◽  
Alan M. Batterham ◽  
Helen H. Handoll ◽  
Andreas Betthäuser
Keyword(s):  
Systematic Review ◽  
Clinical Practice ◽  
Physical Therapy ◽  
Rotator Cuff ◽  
Assessment Tool ◽  
Treatment Options ◽  
Risk Of Bias ◽  
World Health ◽  
Prognostic Models ◽  
Study Selection

Abstract Background Rotator cuff–related disorders represent the largest subgroup of shoulder complaints. Despite the availability of various conservative and surgical treatment options, the precise indications for these options remain unclear. Purpose The purpose of this systematic review was to synthesize the available research on prognostic models for predicting outcomes in adults undergoing physical therapy for painful rotator cuff disorders. Data Sources The MEDLINE, EMBASE, CINAHL, Cochrane CENTRAL, and PEDro databases and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) up to October 2015 were searched. Study Selection The review included primary studies exploring prognostic models in adults undergoing physical therapy, with or without other conservative measures, for painful rotator cuff disorders. Primary outcomes were pain, disability, and adverse events. Inclusion was limited to prospective investigations of prognostic factors elicited at the baseline assessment. Study selection was independently performed by 2 reviewers. Data Extraction A pilot-tested form was used to extract data on key aspects of study design, characteristics, analyses, and results. Risk of bias and applicability were independently assessed by 2 reviewers using the Prediction Study Risk of Bias Assessment tool (PROBAST). Data Synthesis Five studies were included in the review. These studies were extremely heterogeneous in many aspects of design, conduct, and analysis. The findings were analyzed narratively. Limitations All included studies were rated as at high risk of bias, and none of the resulting prognostic models was found to be usable in clinical practice. Conclusions There are no prognostic models ready to inform clinical practice in the context of the review question, highlighting the need for further research on prognostic models for predicting outcomes in adults who undergo physical therapy for painful rotator cuff disorders. The design and conduct of future studies should be receptive to developing methods.

scholarly journals Prognostic models for predicting incident or recurrent atrial fibrillation: protocol for a systematic review

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Janine Dretzke ◽  
Naomi Chuchu ◽  
Winnie Chua ◽  
Larissa Fabritz ◽  
Susan Bayliss ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Systematic Review ◽  
Prognostic Models ◽  
Recurrent Atrial Fibrillation

scholarly journals FINDRISC in Latin America: a systematic review of diagnosis and prognosis models

2020 ◽  
Vol 8 (1) ◽  
pp. e001169 ◽  
Author(s):  
Rodrigo M Carrillo-Larco ◽  
Diego J Aparcana-Granda ◽  
Jhonatan R Mejia ◽  
Antonio Bernabé-Ortiz
Keyword(s):  
Systematic Review ◽  
Latin America ◽  
Assessment Tool ◽  
Data Extraction ◽  
External Validation ◽  
Population Based ◽  
Risk Of Bias ◽  
Prognostic Models ◽  
Receiver Operating Curve ◽  
Modelling Studies

This review aimed to assess whether the FINDRISC, a risk score for type 2 diabetes mellitus (T2DM), has been externally validated in Latin America and the Caribbean (LAC). We conducted a systematic review following the CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) framework. Reports were included if they validated or re-estimated the FINDRISC in population-based samples, health facilities or administrative data. Reports were excluded if they only studied patients or at-risk individuals. The search was conducted in Medline, Embase, Global Health, Scopus and LILACS. Risk of bias was assessed with the PROBAST (Prediction model Risk of Bias ASsessment Tool) tool. From 1582 titles and abstracts, 4 (n=7502) reports were included for qualitative summary. All reports were from South America; there were slightly more women, and the mean age ranged from 29.5 to 49.7 years. Undiagnosed T2DM prevalence ranged from 2.6% to 5.1%. None of the studies conducted an independent external validation of the FINDRISC; conversely, they used the same (or very similar) predictors to fit a new model. None of the studies reported calibration metrics. The area under the receiver operating curve was consistently above 65.0%. All studies had high risk of bias. There has not been any external validation of the FINDRISC model in LAC. Selected reports re-estimated the FINDRISC, although they have several methodological limitations. There is a need for big data to develop—or improve—T2DM diagnostic and prognostic models in LAC. This could benefit T2DM screening and early diagnosis.

scholarly journals A Systematic Review on Bleeding Risk Scores’ Accuracy after Percutaneous Coronary Interventions in Acute and Elective Settings

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 148
Author(s):  
Crischentian Brinza ◽  
Alexandru Burlacu ◽  
Grigore Tinica ◽  
Adrian Covic ◽  
Liviu Macovei
Keyword(s):  
Systematic Review ◽  
Assessment Tool ◽  
Bleeding Risk ◽  
Risk Of Bias ◽  
Risk Scores ◽  
Bleeding Events ◽  
P2y12 Inhibitors ◽  
C Statistic ◽  
Hemorrhagic Event ◽  
Percutaneous Coronary

Dual antiplatelet therapy (DAT) is recommended for all patients undergoing percutaneous coronary intervention (PCI), as it significantly reduces the ischemic risk at the cost of increasing the incidence of bleeding events. Several clinical predictive models were developed to better stratify the bleeding risk associated with DAT. This systematic review aims to perform a literature survey of both standard and emerging bleeding risk scores and report their performance on predicting hemorrhagic events, especially in the era of second-generation drug-eluting stents and more potent P2Y12 inhibitors. We searched PubMed, ScienceDirect, and Cochrane databases for full-text studies that developed or validated bleeding risk scores in adult patients undergoing PCI with subsequent DAT. The risk of bias for each study was assessed using the prediction model risk of bias assessment tool (PROBAST). Eighteen studies were included in the present systematic review. Bleeding risk scores showed a modest to good discriminatory power with c-statistic ranging from 0.49 (95% CI, 0.45–0.53) to 0.82 (95% CI, 0.80–0.85). Clinical models that predict in-hospital bleeding events had a relatively good predictive performance, with c-statistic ranging from 0.70 (95% CI, 0.67–0.72) to 0.80 (95% CI, 0.73–0.87), depending on the risk scores and major hemorrhagic event definition used. The knowledge and utilization of the current bleeding risk scores in appropriate clinical contexts could improve the prediction of bleeding events.

scholarly journals Complications of Catheter Ablation of Atrial Fibrillation: A Systematic Review

2013 ◽  
Vol 22 ◽  
pp. S108
Author(s):  
A. Gupta ◽  
T. Perera ◽  
A. Ganesan ◽  
T. Sullivan ◽  
D. Lau ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Systematic Review ◽  
Catheter Ablation

Repeat Catheter Ablation for Recurrent Atrial Fibrillation: Electrophysiologic Findings and Clinical Outcomes

2021 ◽  
Author(s):  
Usama A. Daimee ◽  
Tauseef Akhtar ◽  
Thomas A. Boyle ◽  
Leah Jager ◽  
Armin Arbab‐Zadeh ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Catheter Ablation ◽  
Clinical Outcomes ◽  
Recurrent Atrial Fibrillation

scholarly journals The effect of dietary phytochemicals on nuclear factor erythroid 2-related factor 2 (Nrf2) activation: a systematic review of human intervention trials

2021 ◽  
Author(s):  
Tom Clifford ◽  
Jarred P. Acton ◽  
Stuart P. Cocksedge ◽  
Kelly A. Bowden Davies ◽  
Stephen J. Bailey
Keyword(s):  
Systematic Review ◽  
Assessment Tool ◽  
Cochrane Collaboration ◽  
Risk Of Bias ◽  
Related Factor ◽  
Human Intervention ◽  
Nrf2 Activation ◽  
Dietary Phytochemicals ◽  
Intervention Trials

AbstractWe conducted a systematic review of human trials examining the effects of dietary phytochemicals on Nrf2 activation. In accordance with the PRISMA guidelines, Medline, Embase and CAB abstracts were searched for articles from inception until March 2020. Studies in adult humans that measured Nrf2 activation (gene or protein expression changes) following ingestion of a phytochemical, either alone or in combination were included. The study was pre-registered on the Prospero database (Registration Number: CRD42020176121). Twenty-nine full-texts were retrieved and reviewed for analysis; of these, eighteen were included in the systematic review. Most of the included participants were healthy, obese or type 2 diabetics. Study quality was assessed using the Cochrane Collaboration Risk of Bias Assessment tool. Twelve different compounds were examined in the included studies: curcumin, resveratrol and sulforaphane were the most common (n = 3 each). Approximately half of the studies reported increases in Nrf2 activation (n = 10); however, many were of poor quality and had an unclear or high risk of bias. There is currently limited evidence that phytochemicals activate Nrf2 in humans. Well controlled human intervention trials are needed to corroborate the findings from in vitro and animal studies.

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