P1858Meta-analysis of performance of risks scores for predicting outcomes after percutaneous Mitraclip implantation

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
T K M Wang ◽  
M T M Wang
Keyword(s):  
Confidence Interval ◽  
Risk Stratification ◽  
Clinical Decision Making ◽  
Operative Mortality ◽  
Data Extraction ◽  
Meta Analysis ◽  
Critical Role ◽  
Clinical Decision ◽  
Risk Scores ◽  
Sts Score

Abstract Background The Mitraclip is the most established percutaneous mitral valve intervention indicated for severe mitral regurgitation at high or prohibitive surgical risk. Risk stratification plays a critical role in selecting the appropriate treatment modality in high risk valve disease patients but have been rarely studied in this setting. We compared the performance of risk scores at predicting mortality after Mitraclip in this meta-analysis. Methods MEDLINE, Embase and Cochrane databases from 1 January 1980 to 31 December 2018 were searched. Two authors reviewed studies which reported c-statistics of risk models to predict mortality after Mitraclip for inclusion, followed by data extraction and pooled analyses. Results Amongst 494 articles searched, 47 full-text articles were evaluated, and 4 studies totalling 879 Mitraclip cases were included for analyses. Operative mortality was reported at 3.3–7.4% in three studies, and 1-year mortality 11.2%-13.5% in two studies. C-statistics (95% confidence interval) for operative mortality were EuroSCORE 0.66 (0.57–0.75), EuroSCORE II 0.72 (0.60–0.85) and STS Score 0.64 (0.56–0.73). Respective Peto's odds ratios (95% confidence interval) to assess calibration were EuroSCORE 0.21 (0.14–0.31), EuroSCORE II 0.43 (0.24–0.76) and STS Score 0.36 (0.21–0.61). C-statistics (95% confidence interval) for 1-year mortality were EuroSCORE II 0.64 (0.57–0.70) and STS Score (0.58–0.64). Conclusion All scores over-estimated operative mortality, and EuroSCORE II had the best moderate discrimination while the other two scores were only modestly prognostic. Development of Mitraclip-specific scores may improve accuracy of risk stratification for this procedure to guide clinical decision-making.

scholarly journals The short- to midterm effectiveness of stemless prostheses compared to stemmed prostheses for patients who underwent total shoulder arthroplasty: a meta-analysis

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Wei Peng ◽  
Yufu Ou ◽  
Chenglong Wang ◽  
Jianxun Wei ◽  
Xiaoping Mu ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Shoulder Arthroplasty ◽  
Clinical Decision Making ◽  
Constant Score ◽  
Data Extraction ◽  
Meta Analysis ◽  
Total Shoulder Arthroplasty ◽  
Clinical Decision ◽  
Clinical Results ◽  
Cochrane Library

Abstract Background To systematically compare the short- to midterm effectiveness of stemless prostheses to that of stemmed prostheses for patients who underwent total shoulder arthroplasty (TSA) and to provide a guideline for clinical decision-making. Methods PubMed, the Cochrane Library, and Web of Science were searched with the given search terms until July 2019 to identify published articles evaluating the clinical outcomes for stemless prostheses compared with stemmed prostheses for patients who underwent TSA. Data extraction and the quality assessment of the included studies were independently performed by two authors. Stata software 14.0 was used to analyze and synthesize the data. Results Two randomized controlled trials and six case-controlled studies with a total of 347 shoulders were included in this meta-analysis. The results of this meta-analysis showed that there were no significant differences between the stemless and stemmed prostheses in terms of the Constant score, pain score, strength, activities of daily living, postoperative range of motion (ROM), and postoperative maximum active ROM. Conclusions This is the first meta-analysis reporting the clinical results of stemless TSA in the short- to midterm follow-up period. Both types of shoulder prostheses were similar in achieving satisfactory clinical outcomes.

scholarly journals Effect of Acupuncture on Cognitive Function of Insomnia Patients Compared with Drugs: A Protocol for Meta-analysis and Systematic Review

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Shan Qin ◽  
Jing Jiang ◽  
Wen-Zhong Wu ◽  
Xiao-Qiu Wang ◽  
Han-Qing Xi ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Clinical Decision Making ◽  
Data Extraction ◽  
Meta Analysis ◽  
Clinical Decision ◽  
Cochrane Library ◽  
China National Knowledge Infrastructure ◽  
Statistical Process ◽  
Assessment Development ◽  
Third Person

Insomnia, one of the most common sleep disorders, is thought to have an adverse effect on cognitive function. At the same time, people with cognitive dysfunction are more prone to insomnia. At present, pharmacotherapy is the main treatment for insomnia, but there are some shortcomings such as poor long-term efficacy and potential dependence. There is some evidence that acupuncture has some advantages in alleviating insomnia and improving cognitive function. This study is aimed at investigating the effects of acupuncture and drugs on cognitive function in patients with insomnia and evaluating the efficacy and safety of these two interventions, providing strong evidence for clinical decision-making. The study will retrieve eight major databases: China National Knowledge Infrastructure, Wanfang Database, VIP Database for Chinese Technical Periodicals, SinoMed, PubMed, Web of Science, Embase, and Cochrane Library. Dissertations, conference papers, and ongoing experiments will also be retrieved for supplement. Literature screening and data extraction will be completed by two authors independently (JJ and X-QW). If there were any disagreements, they would be discussed or referred to a third person for adjudication (W-ZW). Authors will use Cochrane risk of bias tool to assess the included studies. The Review Manager Statistical (RevMan) software is used to conduct the statistical process of meta-analysis, and funnel plot is used to evaluate reporting biases. The Grading of Recommendations Assessment Development and Evaluation (GRADE) Profiler can be used to be aware of the quality of evidence.

scholarly journals Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score

2020 ◽  
Author(s):  
Stephen R Knight ◽  
Antonia Ho ◽  
Riinu Pius ◽  
Iain Buchan ◽  
Gail Carson ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Predictive Value ◽  
Clinical Decision Making ◽  
Data Extraction ◽  
Clinical Decision ◽  
Validation Dataset ◽  
Peripheral Oxygen Saturation ◽  
Oxygen Saturation Level ◽  
Derivation Cohort ◽  
Risk Stratification Score

Objectives To develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19. Design Prospective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited between 21 May and 29 June 2020. Setting 260 hospitals across England, Scotland, and Wales. Participants Adult patients (≥18 years) admitted to hospital with covid-19 admitted at least four weeks before final data extraction. Main outcome measures In-hospital mortality. Results There were 34 692 patients included in the derivation dataset (mortality rate 31.7%) and 22 454 in the validation dataset (mortality 31.5%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea, and C-reactive protein (score range 0-21 points). The 4C risk stratification score demonstrated high discrimination for mortality (derivation cohort: AUROC 0.79; 95% CI 0.78 - 0.79; validation cohort 0.78, 0.77-0.79) with excellent calibration (slope = 1.0). Patients with a score ≥15 (n = 2310, 17.4%) had a 67% mortality (i.e., positive predictive value 67%) compared with 1.0% mortality for those with a score ≤3 (n = 918, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (AUROC range 0.60-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). Conclusions We have developed and validated an easy-to-use risk stratification score based on commonly available parameters at hospital presentation. This outperformed existing scores, demonstrated utility to directly inform clinical decision making, and can be used to stratify inpatients with covid-19 into different management groups. The 4C Mortality Score may help clinicians identify patients with covid-19 at high risk of dying during current and subsequent waves of the pandemic. Study registration ISRCTN66726260

Abstract P111: Comparative Efficacy Of Bisoprolol Compared To Other Selective Beta-1 Blockers In Patients With Hypertension - A Systematic Review And Meta-analysis Of Observational Studies

Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Uday M Jadhav ◽  
Tiny Nair ◽  
SANDEEP BANSAL ◽  
Saumitra Ray
Keyword(s):  
Lipid Profile ◽  
Observational Studies ◽  
Clinical Decision Making ◽  
Meta Analysis ◽  
Hdl Cholesterol ◽  
Clinical Decision ◽  
Cochrane Library ◽  
Favourable Effect ◽  
Pooled Data ◽  
Cholesterol Levels

Introduction: Selective beta-1 blockers (s-BBs) are used in the management of hypertension (HT) in specific subsets. Studies comparing the potency of blood pressure (BP) lowering with different s-BBs are sparse. The objective of this meta-analysis was to evaluate the efficacy of bisoprolol compared to other s-BBs (Atenolol, Betaxolol, Esmolol, Acebutolol, Metoprolol, Nebivolol) in HT patients by examining their effect on BP, heart rate (HR) and metabolic derangements, by examining the evidences reported in observational studies. Methods: Electronic databases like PubMed, EMBASE, Cochrane Library, Clinicaltrials.gov, Surveillance, Epidemiology and End Results Program and 12 PV databases were systematically searched from inception to October 2019. Observational studies that compared bisoprolol with other s-BBs in patients with HT were evaluated in accordance with the PRISMA guidelines. Pooled data were calculated using random-effects model for meta-analysis in terms of mean difference (MD) and 95% confidence interval (95% CI) for each outcome. Outcomes of interest were BP, HR and lipid profile. Results: Four observational studies which compared bisoprolol with other s-BBs (nebivolol and atenolol) were included in this meta-analysis. Significant reduction was observed in office diastolic BP [MD: -1.70; 95% CI: -2.68,-0.72; P <0.01] among arterial HT patients treated with bisoprolol for 26 weeks (w) compared to those treated with other s-BBs. HT patients treated with bisoprolol for 26 w showed significant reduction in HR [MD: -2.20; 95% CI: -3.57,-0.65; P <0.01] and office HR [MD: -2.55; 95% CI: -3.57,-1.53; P <0.01] than other s-BBs. HDL cholesterol levels increased significantly in essential HT patients treated with bisoprolol at 26 w [MD: 7.17; 95% CI: 1.90,12.45; P <0.01], 78 w [MD: 11.70; 95% CI: 4.49,18.91; P <0.01] and 104 w [MD: 10.20, 95% CI: 4.49,18.91; P <0.01] compared to other s-BBs. Conclusion: Our results suggests that bisoprolol is superior to other s-BBs in reducing BP and HR. Bisoprolol also had a favourable effect on lipid profile shown by increase in HDL cholesterol. This meta-analysis emphasizes the efficacy of bisoprolol over other s-BBs, which aids clinical decision making in treatment of patients with HT.

A meta-analysis of confidence and judgment accuracy in clinical decision making.

2015 ◽  
Vol 62 (4) ◽  
pp. 553-567 ◽  
Author(s):  
Deborah J. Miller ◽  
Elliot S. Spengler ◽  
Paul M. Spengler
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Meta Analysis ◽  
Clinical Decision ◽  
Judgment Accuracy

scholarly journals Factors Associated with Disease Severity and Mortality among Patients with Coronavirus Disease 2019: A Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Vignesh Chidambaram ◽  
Nyan Lynn Tun ◽  
Waqas Haque ◽  
Marie Gilbert Majella ◽  
Ranjith Kumar Sivakumar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Disease Severity ◽  
English Language ◽  
Clinical Decision Making ◽  
Clinical Laboratory ◽  
Data Extraction ◽  
Meta Analysis ◽  
Severe Disease ◽  
Factors Associated ◽  
Risk Of Mortality

Background: Understanding the factors associated with disease severity and mortality in Coronavirus disease (COVID19) is imperative to effectively triage patients. We performed a systematic review to determine the demographic, clinical, laboratory and radiological factors associated with severity and mortality in COVID-19. Methods: We searched PubMed, Embase and WHO database for English language articles from inception until May 8, 2020. We included Observational studies with direct comparison of clinical characteristics between a) patients who died and those who survived or b) patients with severe disease and those without severe disease. Data extraction and quality assessment were performed by two authors independently. Results: Among 15680 articles from the literature search, 109 articles were included in the analysis. The risk of mortality was higher in patients with increasing age, male gender (RR 1.45; 95%CI 1.23,1.71), dyspnea (RR 2.55; 95%CI 1.88,2.46), diabetes (RR 1.59; 95%CI 1.41,1.78), hypertension (RR 1.90; 95%CI 1.69,2.15). Congestive heart failure (OR 4.76; 95%CI 1.34,16.97), hilar lymphadenopathy (OR 8.34; 95%CI 2.57,27.08), bilateral lung involvement (OR 4.86; 95%CI 3.19,7.39) and reticular pattern (OR 5.54; 95%CI 1.24,24.67) were associated with severe disease. Clinically relevant cut-offs for leukocytosis(>10.0 x109/L), lymphopenia(< 1.1 x109/L), elevated C-reactive protein(>100mg/L), LDH(>250U/L) and D-dimer(>1mg/L) had higher odds of severe disease and greater risk of mortality. Conclusion: Knowledge of the factors associated of disease severity and mortality identified in our study may assist in clinical decision-making and critical-care resource allocation for patients with COVID-19.

scholarly journals Manipulative and Manual Therapies in the Management of Patients with Prior Lumbar Surgery: A Systematic Review

2020 ◽  
Author(s):  
Clinton J Daniels ◽  
Zachary A. Cupler ◽  
Jordan A Gliedt ◽  
Sheryl Walters ◽  
Alec L Schielke ◽  
...  
Keyword(s):  
Systematic Reviews ◽  
Clinical Decision Making ◽  
Case Reports ◽  
Data Extraction ◽  
Case Series ◽  
Clinical Decision ◽  
Manual Therapies ◽  
Lumbar Surgery ◽  
Pilot Studies ◽  
Surgical Interventions

Abstract BackgroundThe purpose was to identify, summarize, and rate scholarly literature that describes manipulative and manual therapy following lumbar surgery.MethodsThe review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and was registered with PROSPERO. PubMed, Cochrane Database of Systematic Reviews, ICL, CINAHL, and PEDro were searched through July 2019. Articles were screened independently by at least two reviewers for inclusion. Articles included described the practice, utilization, and/or clinical decision making to post surgical intervention with manipulative and/or manual therapies. Data extraction consisted of principal findings, pain and function/disability, patient satisfaction, opioid/medication consumption, and adverse events. Scottish Intercollegiate Guidelines Network critical appraisal checklists were utilized to assess study quality.ResultsLiterature search yielded 1916 articles, 348 duplicates were removed, 109 full-text articles were screened and 50 citations met inclusion criteria. There were 37 case reports/case series, 3 randomized controlled trials, 3 pilot studies, 5 systematic/scoping/narrative reviews, and 2 commentaries. ConclusionThe findings of this review may help inform practitioners who utilize manipulative and/or manual therapies regarding levels of evidence for patients with prior lumbar surgery. Following lumbar surgery, the evidence indicated inpatient neural mobilization does not improve outcomes. There is inconclusive evidence to recommend for or against most manual therapies after most surgical interventions.Trial registrationProspectively registered with PROSPERO (#CRD42020137314). Registered 24 January 2020.

scholarly journals Early Identification of Patients with Acute Gastrointestinal Bleeding using Electronic Health Record Phenotyping

2020 ◽  
Author(s):  
Dennis Shung ◽  
Cynthia Tsay ◽  
Loren Laine ◽  
Prem Thomas ◽  
Caitlin Partridge ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Gastrointestinal Bleeding ◽  
Real Time ◽  
Decision Rule ◽  
Language Processing ◽  
Clinical Decision Making ◽  
External Validation ◽  
Clinical Decision ◽  
Internal Validation ◽  
Electronic Health

Background and AimGuidelines recommend risk stratification scores in patients presenting with gastrointestinal bleeding (GIB), but such scores are uncommonly employed in practice. Automation and deployment of risk stratification scores in real time within electronic health records (EHRs) would overcome a major impediment. This requires an automated mechanism to accurately identify (“phenotype”) patients with GIB at the time of presentation. The goal is to identify patients with acute GIB by developing and evaluating EHR-based phenotyping algorithms for emergency department (ED) patients.MethodsWe specified criteria using structured data elements to create rules for identifying patients, and also developed a natural-language-processing (NLP)-based algorithm for automated phenotyping of patients, tested them with tenfold cross-validation (n=7144) and external validation (n=2988), and compared them with the standard method for encoding patient conditions in the EHR, Systematized Nomenclature of Medicine (SNOMED). The gold standard for GIB diagnosis was independent dual manual review of medical records. The primary outcome was positive predictive value (PPV).ResultsA decision rule using GIB-specific terms from ED triage and from ED review-of-systems assessment performed better than SNOMED on internal validation (PPV=91% [90%-93%] vs. 74% [71%-76%], P<0.001) and external validation (PPV=85% [84%-87%] vs. 69% [67%-71%], P<0.001). The NLP algorithm (external validation PPV=80% [79-82%]) was not superior to the structured-datafields decision rule.ConclusionsAn automated decision rule employing GIB-specific triage and review-of-systems terms can be used to trigger EHR-based deployment of risk stratification models to guide clinical decision-making in real time for patients with acute GIB presenting to the ED.

scholarly journals P071: Artificial intelligence in emergency medicine: A scoping review

CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S90-S90
Author(s):  
A. Kirubarajan ◽  
A. Taher ◽  
S. Khan ◽  
S. Masood
Keyword(s):  
Artificial Intelligence ◽  
Emergency Medicine ◽  
Language Processing ◽  
Scoping Review ◽  
Clinical Decision Making ◽  
Data Extraction ◽  
A Priori ◽  
Clinical Decision ◽  
Hospital Environment ◽  
Clinical Implementation

Introduction: The study of artificial intelligence (AI) in medicine has become increasingly popular over the last decade. The emergency department (ED) is uniquely situated to benefit from AI due to its power of diagnostic prediction, and its ability to continuously improve with time. However, there is a lack of understanding of the breadth and scope of AI applications in emergency medicine, and evidence supporting its use. Methods: Our scoping review was completed according to PRISMA-ScR guidelines and was published a priori on Open Science Forum. We systematically searched databases (Medline-OVID, EMBASE, CINAHL, and IEEE) for AI interventions relevant to the ED. Study selection and data extraction was performed independently by two investigators. We categorized studies based on type of AI model used, location of intervention, clinical focus, intervention sub-type, and type of comparator. Results: Of the 1483 original database citations, a total of 181 studies were included in the scoping review. Inter-rater reliability for study screening for titles and abstracts was 89.1%, and for full-text review was 77.8%. Overall, we found that 44 (24.3%) studies utilized supervised learning, 63 (34.8%) studies evaluated unsupervised learning, and 13 (7.2%) studies utilized natural language processing. 17 (9.4%) studies were conducted in the pre-hospital environment, with the remainder occurring either in the ED or the trauma bay. The majority of interventions centered around prediction (n = 73, 40.3%). 48 studies (25.5%) analyzed AI interventions for diagnosis. 23 (12.7%) interventions focused on diagnostic imaging. 89 (49.2%) studies did not have a comparator to their AI intervention. 63 (34.8%) studies used statistical models as a comparator, 19 (10.5%) of which were clinical decision making tools. 15 (8.3%) studies used humans as comparators, with 12 of the 15 (80%) studies showing superiority in favour of the AI intervention when compared to a human. Conclusion: AI-related research is rapidly increasing in emergency medicine. AI interventions are heterogeneous in both purpose and design, but primarily focus on predictive modeling. Most studies do not involve a human comparator and lack information on patient-oriented outcomes. While some studies show promising results for AI-based interventions, there remains uncertainty regarding their superiority over standard practice, and further research is needed prior to clinical implementation.

scholarly journals Prevalence, severity, and nature of preventable patient harm across medical care settings: systematic review and meta-analysis

BMJ ◽  
2019 ◽  
pp. l4185 ◽  
Author(s):  
Maria Panagioti ◽  
Kanza Khan ◽  
Richard N Keers ◽  
Aseel Abuzour ◽  
Denham Phipps ◽  
...  
Keyword(s):  
Systematic Review ◽  
Confidence Interval ◽  
Medical Care ◽  
Data Extraction ◽  
Meta Analysis ◽  
Cost Effective ◽  
Mitigation Strategies ◽  
Patient Harm ◽  
Pooled Prevalence ◽  
Preventable Harm

Abstract Objective To systematically quantify the prevalence, severity, and nature of preventable patient harm across a range of medical settings globally. Design Systematic review and meta-analysis. Data sources Medline, PubMed, PsycINFO, Cinahl and Embase, WHOLIS, Google Scholar, and SIGLE from January 2000 to January 2019. The reference lists of eligible studies and other relevant systematic reviews were also searched. Review methods Observational studies reporting preventable patient harm in medical care. The core outcomes were the prevalence, severity, and types of preventable patient harm reported as percentages and their 95% confidence intervals. Data extraction and critical appraisal were undertaken by two reviewers working independently. Random effects meta-analysis was employed followed by univariable and multivariable meta regression. Heterogeneity was quantified by using the I 2 statistic, and publication bias was evaluated. Results Of the 7313 records identified, 70 studies involving 337 025 patients were included in the meta-analysis. The pooled prevalence for preventable patient harm was 6% (95% confidence interval 5% to 7%). A pooled proportion of 12% (9% to 15%) of preventable patient harm was severe or led to death. Incidents related to drugs (25%, 95% confidence interval 16% to 34%) and other treatments (24%, 21% to 30%) accounted for the largest proportion of preventable patient harm. Compared with general hospitals (where most evidence originated), preventable patient harm was more prevalent in advanced specialties (intensive care or surgery; regression coefficient b=0.07, 95% confidence interval 0.04 to 0.10). Conclusions Around one in 20 patients are exposed to preventable harm in medical care. Although a focus on preventable patient harm has been encouraged by the international patient safety policy agenda, there are limited quality improvement practices specifically targeting incidents of preventable patient harm rather than overall patient harm (preventable and non-preventable). Developing and implementing evidence-based mitigation strategies specifically targeting preventable patient harm could lead to major service quality improvements in medical care which could also be more cost effective.

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