Do patients with diabetes have an increased risk of impaired fracture healing? A systematic review and meta‐analysis

2020 ◽  
Vol 90 (7-8) ◽  
pp. 1259-1264
Author(s):  
Zi‐chuan Ding ◽  
Wei‐nan Zeng ◽  
Xiao Rong ◽  
Zhi‐min Liang ◽  
Zong‐ke Zhou
Keyword(s):  
Systematic Review ◽  
Fracture Healing ◽  
Meta Analysis ◽  
Increased Risk ◽  
Patients With Diabetes

scholarly journals Association of myocardial fibrosis detected by late gadolinium-enhanced MRI with clinical outcomes in patients with diabetes: a systematic review and meta-analysis

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e055374
Author(s):  
Zhi Yang ◽  
Rong Xu ◽  
Jia-rong Wang ◽  
Hua-yan Xu ◽  
Hang Fu ◽  
...  
Keyword(s):  
Systematic Review ◽  
Risk Stratification ◽  
Myocardial Fibrosis ◽  
Meta Analysis ◽  
Imaging Biomarker ◽  
Cardiac Events ◽  
Prognostic Information ◽  
Increased Risk ◽  
Patients With Diabetes

ObjectiveThis meta-analysis assessed the associations of myocardial fibrosis detected by late gadolinium-enhanced (LGE)-MRI with the risk of major adverse cardiac and cerebrovascular events (MACCEs) and major adverse cardiac events (MACEs) in patients with diabetes.DesignSystematic review and meta-analysis reported in accordance with the guidelines of the Meta-analysis of Observational Studies in Epidemiology statement.Data sourcesWe searched the Medline, Embase and Cochrane by Ovid databases for studies published up to 27 August 2021.Eligibility criteriaProspective or respective cohort studies were included if they reported the HR and 95% CIs for MACCEs/MACEs in patients with either type 1 or 2 diabetes and LGE-MRI-detected myocardial fibrosis compared with patients without LGE-MRI-detected myocardial fibrosis and if the articles were published in the English language.Data extraction and synthesisTwo review authors independently extracted data and assessed the quality of the included studies. Pooled HRs and 95% CIs were analysed using a random effects model. Heterogeneity was assessed using forest plots and I2 statistics.ResultsEight studies with 1121 patients with type 1 or type 2 diabetes were included in this meta-analysis, and the follow-up ranged from 17 to 70 months. The presence of myocardial fibrosis detected by LGE-MRI was associated with an increased risk for MACCEs (HR: 2.58; 95% CI 1.42 to 4.71; p=0.002) and MACEs (HR: 5.28; 95% CI 3.20 to 8.70; p<0.001) in patients with diabetes. Subgroup analysis revealed that ischaemic fibrosis detected by LGE was associated with MACCEs (HR 3.80, 95% CI 2.38 to 6.07; p<0.001) in patients with diabetes.ConclusionsThis study demonstrated that ischaemic myocardial fibrosis detected by LGE-MRI was associated with an increased risk of MACCEs/MACEs in patients with diabetes and may be an imaging biomarker for risk stratification. Whether LGE-MRI provides incremental prognostic information with respect to MACCEs/MACEs over risk stratification by conventional cardiovascular risk factors requires further study.

Significantly Increased Risk of Cancer in Patients with Diabetes Mellitus: A Systematic Review and Meta-Analysis

2011 ◽  
Vol 17 (4) ◽  
pp. 616-628 ◽  
Author(s):  
Hiroshi Noto ◽  
Tetsuro Tsujimoto ◽  
Takehiko Sasazuki ◽  
Mitsuhiko Noda
Keyword(s):  
Diabetes Mellitus ◽  
Systematic Review ◽  
Meta Analysis ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
Risk Of Cancer

Abstract 17138: Are Patients With Diabetes Mellitus at Increased Risk for Adverse Outcomes After Left Ventricular Assist Device Implantation? A Systematic Review and Meta-Analysis

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_1) ◽  
Author(s):  
Muhammad S Khan ◽  
Paolo C Colombo ◽  
Noman Lateef ◽  
Muhammad S Usman ◽  
Safi U Khan ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Systematic Review ◽  
Hemorrhagic Stroke ◽  
Meta Analysis ◽  
Left Ventricular ◽  
Assist Device ◽  
Ventricular Assist ◽  
Increased Risk ◽  
Left Ventricular Assist ◽  
Patients With Diabetes

Background: Patients with diabetes mellitus (DM) are known to have reduced life expectancy and be at increased risk for multiple morbidities including serious infection. However, published data on DM outcomes after left ventricular assist device (LVAD) implantation are sparse, inconsistent and individual studies are small with limited power. We conducted a systematic review and meta-analysis to compare survival and adverse events post-LVAD in DM versus non-DM (NDM) patients. Methods: Medline, Scopus and Cochrane Central databases were searched for studies comparing outcomes in DM and NDM patients undergoing LVAD implantation for advanced heart failure (HF) from inception-February 2018. Outcomes included all-cause mortality (30-day and one-year), device-related infection, ischemic stroke, hemorrhagic stroke and major bleeding. Results were reported as random effect risk ratios (RR) with 95 % confidence intervals. Results: We identified 5 retrospective cohort studies, at low risk of bias, reporting on 1,351 patients (n=488 DM). There was a borderline significant, increased 30-day mortality (RR: 1.57 [1.00, 2.47]; p=0.05; I 2 =0%) among DM vs. NDM. The DM and NDM groups did not differ significantly in terms of 1-year mortality (RR: 1.15 [0.98, 1.35]; p=0.08; I 2 =39%), device-related infection (RR: 1.05 [0.92, 1.19]; p=0.88; I 2 =0%), ischemic stroke (RR: 1.29 [0.91, 1.83]; p=0.69; I 2 =0%), hemorrhagic stroke (RR: 1.10 [0.42, 2.83]; p=0.85; I 2 =69%), and bleeding (RR: 1.06 [0.80, 1.40]; p=0.70; I 2 =27%). Conclusion: Following LVAD implantation, patients with DM, versus patients without, have a modestly elevated 30-day mortality rate. However, 1-year mortality rates, device related infection, and bleeding rates were not different.

scholarly journals Predicting the risk of stroke among patients with type 2 diabetes: a systematic review and meta-analysis of C-statistics

BMJ Open ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. e025579 ◽  
Author(s):  
Mohammad Ziaul Islam Chowdhury ◽  
Fahmida Yeasmin ◽  
Doreen M Rabi ◽  
Paul E Ronksley ◽  
Tanvir C Turin
Keyword(s):  
Systematic Review ◽  
Prediction Models ◽  
Data Extraction ◽  
Meta Analysis ◽  
External Validation ◽  
Predictive Performance ◽  
Eligibility Criteria ◽  
C Statistic ◽  
Increased Risk ◽  
Patients With Diabetes

ObjectiveStroke is a major cause of disability and death worldwide. People with diabetes are at a twofold to fivefold increased risk for stroke compared with people without diabetes. This study systematically reviews the literature on available stroke prediction models specifically developed or validated in patients with diabetes and assesses their predictive performance through meta-analysis.DesignSystematic review and meta-analysis.Data sourcesA detailed search was performed in MEDLINE, PubMed and EMBASE (from inception to 22 April 2019) to identify studies describing stroke prediction models.Eligibility criteriaAll studies that developed stroke prediction models in populations with diabetes were included.Data extraction and synthesisTwo reviewers independently identified eligible articles and extracted data. Random effects meta-analysis was used to obtain a pooled C-statistic.ResultsOur search retrieved 26 202 relevant papers and finally yielded 38 stroke prediction models, of which 34 were specifically developed for patients with diabetes and 4 were developed in general populations but validated in patients with diabetes. Among the models developed in those with diabetes, 9 reported their outcome as stroke, 23 reported their outcome as composite cardiovascular disease (CVD) where stroke was a component of the outcome and 2 did not report stroke initially as their outcome but later were validated for stroke as the outcome in other studies. C-statistics varied from 0.60 to 0.92 with a median C-statistic of 0.71 (for stroke as the outcome) and 0.70 (for stroke as part of a composite CVD outcome). Seventeen models were externally validated in diabetes populations with a pooled C-statistic of 0.68.ConclusionsOverall, the performance of these diabetes-specific stroke prediction models was not satisfactory. Research is needed to identify and incorporate new risk factors into the model to improve models’ predictive ability and further external validation of the existing models in diverse population to improve generalisability.

scholarly journals Association of diabetes with atrial fibrillation types: a systematic review and meta-analysis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Fadi Alijla ◽  
Chepkoech Buttia ◽  
Tobias Reichlin ◽  
Salman Razvi ◽  
Beatrice Minder ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Systematic Review ◽  
Meta Analysis ◽  
Population Sample ◽  
Positive Association ◽  
Cross Sectional ◽  
Random Effects Models ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
The Impact

Abstract Background Atrial fibrillation (AF) is a common arrhythmia classified as paroxysmal and non-paroxysmal. Non-paroxysmal AF is associated with an increased risk of complications. Diabetes contributes to AF initiation, yet its role in AF maintenance is unclear. We conducted a systematic review and meta-analysis to summarize the evidence regarding the association of diabetes with AF types. Methods We searched 5 databases for observational studies investigating the association of diabetes with the likelihood of an AF type (vs another type) in humans. Study quality was evaluated using the Newcastle–Ottawa Scale. Studies classifying AF types as paroxysmal (reference) and non-paroxysmal were pooled in a meta-analysis using random effects models. Results Of 1997 articles we identified, 20 were included in our systematic review. The population sample size ranged from 64 to 9816 participants with mean age ranging from 40 to 75 years and percentage of women from 24.8 to 100%. The quality of studies varied from poor (60%) to fair (5%) to good (35%). In the systematic review, 8 studies among patients with AF investigated the cross-sectional association of diabetes with non-paroxysmal AF (vs paroxysmal) of which 6 showed a positive association and 2 showed no association. Fourteen studies investigated the longitudinal association of diabetes with “more sustained” AF types (vs “less sustained”) of which 2 showed a positive association and 12 showed no association. In the meta-analysis of cross-sectional studies, patients with AF and diabetes were 1.31-times more likely to have non-paroxysmal AF than those without diabetes [8 studies; pooled OR (95% CI), 1.31 (1.13–1.51), I2 = 82.6%]. The meta-analysis of longitudinal studies showed that for patients with paroxysmal AF, diabetes is associated with 1.32-times increased likelihood of progression to non-paroxysmal AF [five studies; pooled OR (95% CI), 1.32 (1.07–1.62); I2 = 0%]. Conclusions Our findings suggest that diabetes is associated with an increased likelihood of non-paroxysmal AF rather than paroxysmal AF. However, further high quality studies are needed to replicate these findings, adjust for potential confounders, elucidate mechanisms linking diabetes to non-paroxysmal AF, and assess the impact of antidiabetic medications on AF types. These strategies could eventually help decrease the risk of non-paroxysmal AF among patients with diabetes.

Effects of wearable technology on patients with diabetes: A systematic review and meta-analysis (Preprint)

2020 ◽  
Author(s):  
Dongjun Wu ◽  
Nicholas Buys ◽  
Guandong Xu ◽  
Jing Sun
Keyword(s):  
Systematic Review ◽  
Blood Pressure ◽  
Relapse Prevention ◽  
Diabetes Management ◽  
Meta Analysis ◽  
Intervention Group ◽  
Wearable Technologies ◽  
Patients With Diabetes ◽  
Hba1c Levels

UNSTRUCTURED Aims: This systematic review and meta-analysis aimed to evaluate the effects of wearable technologies on HbA1c, blood pressure, body mass index (BMI), and fastening blood glucose (FBG) in patients with diabetes. Methods: We searched PubMed, Scopus, Embase, the Cochrane database, and the Chinese CNKI database from last 15 years until August 2021. The quality of the 16 included studies was assessed using the PEDro scale, and random effect models were used to estimate outcomes, with I2 used for heterogeneity testing. Results: A significant reduction in HbA1c (-0.475% [95% CI -0.692 to -0.257, P<0.001]) was found following telemonitoring. However, the results of the meta-analysis did not show significant changes in blood pressure, BMI, and glucose, in the intervention group (P>0.05), although the effect size for systolic blood pressure (0.389) and diastolic blood pressure may indicate a significant effect. Subgroup analysis revealed statistically significant effects of wearable technologies on HbA1c when supported by dietetic interventions (P<0.001), medication monitoring (P<0.001), and relapse prevention (P<0.001). Online messages and telephone interventions significantly affected HbA1c levels (P<0.001). Trials with additional online face-to-face interventions showed greater reductions in HbA1c levels. Remote interventions including dietetic advice (P<0.001), medication (P<0.001), and relapse prevention (P<0.001) during telemonitoring showed a significant effect on HbA1c, particularly in patients attending ten or more intervention sessions (P<0.001). Conclusion: Wearable technologies can improve diabetes management by simplifying self-monitoring, allowing patients to upload their live measurement results frequently and thereby improving the quality of telemedicine. Wearable technologies also facilitate remote medication management, dietetic interventions, and relapse prevention.

scholarly journals EXPRESS: Stroke risk following traumatic brain injury: systematic review and meta-analysis

2021 ◽  
pp. 174749302110042
Author(s):  
Grace Mary Turner ◽  
Christel McMullan ◽  
Olalekan Lee Aiyegbusi ◽  
Danai Bem ◽  
Tom Marshall ◽  
...  
Keyword(s):  
Systematic Review ◽  
Stroke Risk ◽  
Meta Analysis ◽  
Vitamin K Antagonists ◽  
Cochrane Library ◽  
Control Group ◽  
Large Sample Size ◽  
Hazard Ratios ◽  
Increased Risk ◽  
The Cochrane Library

Aims To investigate the association between TBI and stroke risk. Summary of review We undertook a systematic review of MEDLINE, EMBASE, CINAHL, and The Cochrane Library from inception to 4th December 2020. We used random-effects meta-analysis to pool hazard ratios (HR) for studies which reported stroke risk post-TBI compared to controls. Searches identified 10,501 records; 58 full texts were assessed for eligibility and 18 met the inclusion criteria. The review included a large sample size of 2,606,379 participants from four countries. Six studies included a non-TBI control group, all found TBI patients had significantly increased risk of stroke compared to controls (pooled HR 1.86; 95% CI 1.46-2.37). Findings suggest stroke risk may be highest in the first four months post-TBI, but remains significant up to five years post-TBI. TBI appears to be associated with increased stroke risk regardless of severity or subtype of TBI. There was some evidence to suggest an association between reduced stroke risk post-TBI and Vitamin K antagonists and statins, but increased stroke risk with certain classes of antidepressants. Conclusion TBI is an independent risk factor for stroke, regardless of TBI severity or type. Post-TBI review and management of risk factors for stroke may be warranted.

Prognostic role of Krebs von den Lungen-6 (KL-6) measurement in idiopathic pulmonary fibrosis: a systematic review and meta-analysis

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Elena Aloisio ◽  
Federica Braga ◽  
Chiara Puricelli ◽  
Mauro Panteghini
Keyword(s):  
Systematic Review ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Binary Data ◽  
Meta Analysis ◽  
Mortality Prediction ◽  
Asian Populations ◽  
Increased Risk ◽  
Using Data ◽  
Patient Prognosis

Abstract Objectives Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial disease with limited therapeutic options. The measurement of Krebs von den Lungen-6 (KL-6) glycoprotein has been proposed for evaluating the risk of IPF progression and predicting patient prognosis, but the robustness of available evidence is unclear. Methods We searched Medline and Embase databases for peer-reviewed literature from inception to April 2020. Original articles investigating KL-6 as prognostic marker for IPF were retrieved. Considered outcomes were the risk of developing acute exacerbation (AE) and patient survival. Meta-analysis of selected studies was conducted, and quantitative data were uniformed as odds ratio (OR) or hazard ratio (HR) estimates, with corresponding 95% confidence intervals (CI). Results Twenty-six studies were included in the systematic review and 14 were finally meta-analysed. For AE development, the pooled OR (seven studies) for KL-6 was 2.72 (CI 1.22–6.06; p=0.015). However, a high degree of heterogeneity (I2=85.6%) was found among selected studies. Using data from three studies reporting binary data, a pooled sensitivity of 72% (CI 60–82%) and a specificity of 60% (CI 52–68%) were found for KL-6 measurement in detecting insurgence of AE in IPF patients. Pooled HR (seven studies) for mortality prediction was 1.009 (CI 0.983–1.036; p=0.505). Conclusions Although our meta-analysis suggested that IPF patients with increased KL-6 concentrations had a significant increased risk of developing AE, the detection power of the evaluated biomarker is limited. Furthermore, no relationship between biomarker concentrations and mortality was found. Caution is also needed when extending obtained results to non-Asian populations.

scholarly journals The incidence and prevalence of cardiovascular diseases in gout: a systematic review and meta-analysis

2021 ◽  
Author(s):  
Peter Cox ◽  
Sonal Gupta ◽  
Sizheng Steven Zhao ◽  
David M. Hughes
Keyword(s):  
Systematic Review ◽  
Cardiovascular Disease ◽  
Cardiovascular Risk ◽  
Cardiovascular Diseases ◽  
Small Sample Size ◽  
Meta Analysis ◽  
Random Effect ◽  
Small Sample ◽  
Future Research ◽  
Increased Risk

AbstractThe aims of this systematic review and meta-analysis were to describe prevalence of cardiovascular disease in gout, compare these results with non-gout controls and consider whether there were differences according to geography. PubMed, Scopus and Web of Science were systematically searched for studies reporting prevalence of any cardiovascular disease in a gout population. Studies with non-representative sampling, where a cohort had been used in another study, small sample size (< 100) and where gout could not be distinguished from other rheumatic conditions were excluded, as were reviews, editorials and comments. Where possible meta-analysis was performed using random-effect models. Twenty-six studies comprising 949,773 gout patients were included in the review. Pooled prevalence estimates were calculated for five cardiovascular diseases: myocardial infarction (2.8%; 95% confidence interval (CI)s 1.6, 5.0), heart failure (8.7%; 95% CI 2.9, 23.8), venous thromboembolism (2.1%; 95% CI 1.2, 3.4), cerebrovascular accident (4.3%; 95% CI 1.8, 9.7) and hypertension (63.9%; 95% CI 24.5, 90.6). Sixteen studies reported comparisons with non-gout controls, illustrating an increased risk in the gout group across all cardiovascular diseases. There were no identifiable reliable patterns when analysing the results by country. Cardiovascular diseases are more prevalent in patients with gout and should prompt vigilance from clinicians to the need to assess and stratify cardiovascular risk. Future research is needed to investigate the link between gout, hyperuricaemia and increased cardiovascular risk and also to establish a more thorough picture of prevalence for less common cardiovascular diseases.

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