scholarly journals Application of Standardised Effect Sizes to Hospital Discharge Outcomes for People with Diabetes

2020 ◽  
Author(s):  
Tim David Robbins ◽  
Sarah N. Lim Choi Keung ◽  
Sailesh Sankar ◽  
Harpal Randeva ◽  
Theodoros N. Arvanitis
Keyword(s):  
Risk Factors ◽  
Risk Stratification ◽  
Prediction Models ◽  
Significant Risk ◽  
Research Literature ◽  
Effect Sizes ◽  
Tertiary Referral Centre ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
Discharge From Hospital

Abstract Background: Patients with diabetes are at an increased risk of readmission and mortality when discharged from hospital. Existing research identifies statistically significant risk factors that are thought to underpin these outcomes. Increasingly, these risk factors are being used to create risk prediction models, and target risk modifying interventions. These risk factors are typically reported in the literature accompanied by unstandardized effect sizes, which makes comparisons difficult. We demonstrate an assessment of variation between standardised effect sizes for such risk factors across care outcomes and patient cohorts. Such an approach will support development of more rigorous risk stratification tools and better targeting of intervention measures. Methods: Data was extracted from the electronic health record of a major tertiary referral centre, over a 3-year period, for all patients discharged from hospital with a concurrent diagnosis of diabetes mellitus. Risk factors selected for extraction were pre-specified according to a systematic review of the research literature. Standardised effect sizes were calculated for all statistically significant risk factors, and compared across patient cohorts and both readmission & mortality outcome measures. Results: Data was extracted for 46,357 distinct admissions patients, creating a large dataset of approximately 10,281,400 data points. The calculation of standardized effect size measures allowed direct comparison. Effect sizes were noted to be larger for mortality compared to readmission, as well as for being larger for surgical and type 1 diabetes cohorts of patients. Conclusions: The calculation of standardised effect sizes is an important step in evaluating risk factors for healthcare events. This will improve our understanding of risk and support the development of more effective risk stratification tools to support patients to make better informed decisions at discharge from hospital.

scholarly journals Application of Standardised Effect Sizes to Hospital Discharge Outcomes for People with Diabetes

2019 ◽  
Author(s):  
Tim David Robbins ◽  
Sarah N. Lim Choi Keung ◽  
Sailesh Sankar ◽  
Harpal Randeva ◽  
Theodoros N. Arvanitis
Keyword(s):  
Risk Factors ◽  
Prediction Models ◽  
Significant Risk ◽  
Research Literature ◽  
Effect Sizes ◽  
Tertiary Referral Centre ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
Discharge From Hospital ◽  
Diabetes Mellitus Risk

Abstract Background: Patients with diabetes are at an increased risk of readmission and mortality when discharged from hospital. Existing research identifies statistically significant risk factors that are thought to underpin these outcomes. Increasingly, these risk factors are being used to create risk prediction models, and target risk modifying interventions. These risk factors are typically reported in the literature accompanied by unstandardized effect sizes, which makes comparisons difficult. We demonstrate an assessment of variation between standardised effect sizes for such risk factors across care outcomes and patient cohorts. Such an approach will support development of more rigorous risks stratification tools and better targeting of intervention measures. Methods: Data was extracted from the electronic health record of a major tertiary referral centre, over a 3-year period, for all patients discharged from hospital with a concurrent diagnosis of diabetes mellitus. Risk factors selected for extraction were pre-specified according to a systematic review of the research literature. Standardised effect sizes were calculated for all statistically significant risk factors, and compared across patient cohorts and both readmission & mortality outcome measures. Results: Data was extracted for 46,357 distinct admissions patients, creating a large dataset of 10,281,406 risk factors. The calculation of standardized effect size measures allowed direct comparison. Effect sizes were noted to be larger for mortality compared to readmission, as well as for being larger for surgical and type 1 diabetes cohorts of patients. Conclusions: The calculation of standardised effect sizes is an important step in evaluating risk factors for healthcare events. This will improve our understanding of risk and support the development of more effective risk stratification tools to support patients to make better informed decisions at discharge from hospital.

Risk prediction models and scores in hypertrophic cardiomyopathy

2021 ◽  
Vol 27 ◽  
Author(s):  
Thomas D. Gossios ◽  
Konstantinos Savvatis ◽  
Thomas Zegkos ◽  
Despina Parcharidou ◽  
Haralambos I Karvounis ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hypertrophic Cardiomyopathy ◽  
Risk Stratification ◽  
Prediction Models ◽  
Risk Category ◽  
Predictive Capacity ◽  
European Guidelines ◽  
Device Implantation ◽  
Increased Risk ◽  
Risk Stratum

: Hypertrophic cardiomyopathy (HCM) has historically been linked with sudden cardiac death (SCD). Currently, it is well established that only a subset of patients is at the highest risk stratum for such a catastrophic event. Detection of patients belonging to this high-risk category can allow for timely defibrillator implantation, changing the natural history of HCM. Inversely, device implantation in patients deemed at low risk leads to an unnecessary burden of device complications with no apparent protective benefit. Previous studies have identified a series of markers, now considered as established risk factors, with genetic testing and newer imaging allowing for the detection of novel, highly promising indices of increased risk for SCD. Despite the identification of a number of risk factors, there is noticeable discrepancy on the utility of such factors for risk stratification between the current American and European guidelines. We sought to systematically review the data available on these two approaches, presenting their rationale and respective predictive capacity, also discussing the potential of novel markers to augment the precision of currently used risk stratification models for SCD in HCM.

Post-Bariatric Abdominoplasty: Analysis of 406 Cases With Focus on Risk Factors and Complications

2020 ◽  
Vol 41 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Torsten Schlosshauer ◽  
Marcus Kiehlmann ◽  
Diana Jung ◽  
Robert Sader ◽  
Ulrich M Rieger
Keyword(s):  
Risk Factors ◽  
Wound Healing ◽  
Surgical Technique ◽  
Significant Risk ◽  
Level Of Evidence ◽  
Increased Risk ◽  
Potential Risk Factors ◽  
Wound Healing Problems ◽  
Bariatric Patients

Abstract Background Post-bariatric patients present a surgical challenge within abdominoplasty because of residual obesity and major comorbidities. In this study, we analyzed complications following abdominoplasty in post-bariatric patients and evaluated potential risk factors associated with these complications. Objectives The authors sought to determine the complications and risk factors following abdominoplasty in post-bariatric patients. Methods A retrospective study of patients who underwent abdominoplasty was performed from January 2009 to December 2018 at our institution. Variables analyzed were sex, age, body mass index (BMI), smoking, surgical technique, operative time, resection weight, drain output, and complications. Results A total of 406 patients were included in this study (320 female and 86 male) with a mean age of 44.4 years and a BMI of 30.6 kg/m2. Abdominoplasty techniques consisted of traditional (64.3%), fleur-de-lis technique (27.3%), and panniculectomy without umbilical displacement (8.4%). Overall complications recorded were 41.9%, the majority of these being wound-healing problems (32%). Minor and major complications were found in 29.1% and 12.8% of patients, respectively. A BMI value of ≥30 kg/m2 was associated with an increased risk for wound-healing problems (P = 0.001). The frequency of total complications was significantly related to age (P = 0.007), BMI (P = 0.004), and resection weight (P = 0.001). Abdominoplasty technique tended to influence total complications. Conclusions This study demonstrates in a fairly large sample of post-bariatric patients (n = 406) that abdominoplasty alone can be performed safely, with an acceptable complication rate. Age, BMI, and resection weight are shown to be significant risk factors for total complications. The role of surgical technique needs to be evaluated further. Level of Evidence: 4

Post-thyroidectomy bleeding: analysis of risk factors from a national registry

2021 ◽  
Author(s):  
H E Doran ◽  
S M Wiseman ◽  
F F Palazzo ◽  
D Chadwick ◽  
S Aspinall
Keyword(s):  
Risk Factors ◽  
Total Thyroidectomy ◽  
Thyroid Surgery ◽  
Multivariable Analysis ◽  
Significant Risk ◽  
Bleeding Risk ◽  
Redo Surgery ◽  
Day Case ◽  
Increased Risk ◽  
Male Sex

Abstract Background Post-thyroidectomy haemorrhage occurs in 1–2 per cent of patients, one-quarter requiring bedside clot evacuation. Owing to the risk of life-threatening haemorrhage, previous British Association of Endocrine and Thyroid Surgeons (BAETS) guidance has been that day-case thyroidectomy could not be endorsed. This study aimed to review the best currently available UK data to evaluate a recent change in this recommendation. Methods The UK Registry of Endocrine and Thyroid Surgery was analysed to determine the incidence of and risk factors for post-thyroidectomy haemorrhage from 2004 to 2018. Results Reoperation for bleeding occurred in 1.2 per cent (449 of 39 014) of all thyroidectomies. In multivariable analysis male sex, increasing age, redo surgery, retrosternal goitre and total thyroidectomy were significantly correlated with an increased risk of reoperation for bleeding, and surgeon monthly thyroidectomy rate correlated with a decreased risk. Estimation of variation in bleeding risk from these predictors gave low pseudo-R2 values, suggesting that bleeding is unpredictable. Reoperation for bleeding occurred in 0.9 per cent (217 of 24 700) of hemithyroidectomies, with male sex, increasing age, decreasing surgeon volume and redo surgery being risk factors. The mortality rate following thyroidectomy was 0.1 per cent (23 of 38 740). In a multivariable model including reoperation for bleeding node dissection and age were significant risk factors for mortality. Conclusion The highest risk for bleeding occurred following total thyroidectomy in men, but overall bleeding was unpredictable. In hemithyroidectomy increasing surgeon thyroidectomy volume reduces bleeding risk. This analysis supports the revised BAETS recommendation to restrict day-case thyroid surgery to hemithyroidectomy performed by high-volume surgeons, with caution in the elderly, men, patients with retrosternal goitres, and those undergoing redo surgery.

scholarly journals Combining Carcinoembryonic Antigen and Platelet to Lymphocyte Ratio to Predict Brain Metastasis of Resected Lung Adenocarcinoma Patients

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Wei Wang ◽  
Chao Bian ◽  
Di Xia ◽  
Jin-Xi He ◽  
Ping Hai ◽  
...  
Keyword(s):  
Risk Factors ◽  
Brain Metastasis ◽  
Lung Adenocarcinoma ◽  
Carcinoembryonic Antigen ◽  
Roc Curve ◽  
Univariate Analysis ◽  
Significant Risk ◽  
Platelet To Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Increased Risk

We aimed to evaluate the role of pretreatment carcinoembryonic antigen (CEA) and platelet to lymphocyte ratio (PLR) in predicting brain metastasis after radical surgery for lung adenocarcinoma patients. The records of 103 patients with completely resected lung adenocarcinoma between 2013 and 2014 were reviewed. Clinicopathologic characteristics of these patients were assessed in the Cox proportional hazards regression model. Brain metastasis occurred in 12 patients (11.6%). On univariate analysis, N2 stage (P = 0.013), stage III (P = 0.016), increased CEA level (P = 0.006), and higher PLR value (P = 0.020) before treatment were associated with an increased risk of developing brain metastasis. In multivariate model analysis, CEA above 5.2 ng/mL (P = 0.014) and PLR ≥ 120 (P = 0.036) remained as the risk factors for brain metastasis. The combination of CEA and PLR was superior to CEA or PLR alone in predicting brain metastasis according to the receiver operating characteristic (ROC) curve analysis (area under ROC curve, AUC 0.872 versus 0.784 versus 0.704). Pretreatment CEA and PLR are independent and significant risk factors for occurrence of brain metastasis in resected lung adenocarcinoma patients. Combining these two factors may improve the predictability of brain metastasis.

Features of the course of coronavirus infection in patients with diabetes mellitus

2022 ◽  
pp. 18-21
Author(s):  
Vladimir Anatolievich Klimov ◽  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Human Population ◽  
Fatal Outcome ◽  
Significant Risk ◽  
Adverse Outcomes ◽  
Concomitant Disease ◽  
Patients With Diabetes ◽  
Coronavirus Infection ◽  
Population Mortality

Diabetesmellitus, overweight and the age of a patient over 65 years old are identified by clinicians as themain factors that can complicate the course of the coronavirus infection and increase the likelihood of fatal outcome. Although in the general human population mortality from coronavirus fluctuateswithin 3–5 %, sometimes very significantly differing in individual countries, this level can reach 15–25 % among patientswith diabetes, especially for those receiving insulin therapy. Diabetes mellitus as a concomitant disease in COVID-19 is considered one of the most significant risk factors for the development of adverse outcomes due to a more severe course of infection in conditions of hyperglycemia and other aggravating factors.

scholarly journals Relationship between childhood obesity and dietary behavior in selected school-going children from Dhaka city, Bangladesh

2020 ◽  
Vol 7 (7) ◽  
pp. 2469
Author(s):  
Mohammad Rahanur Alam ◽  
Mohammad Asadul Habib ◽  
A. K. Obidul Huq ◽  
Sumaiya Mamun ◽  
Sompa Reza ◽  
...  
Keyword(s):  
Risk Factors ◽  
Fast Food ◽  
Primary Schools ◽  
Significant Risk ◽  
Dietary Behavior ◽  
Communicable Diseases ◽  
Overweight And Obesity ◽  
Dhaka City ◽  
Non Communicable Diseases ◽  
Increased Risk

Background: The prevalence of non-communicable diseases is rising in Dhaka City, Bangladesh. Obesity is one of the significant risk factors for many non-communicable diseases. This research aimed to investigate the current prevalence of overweight and obesity among children in selected schools in Dhaka City through anthropometric evaluation, as well as to assess the correlation of various environmental determinants such as physical activity, dietary behavior, lifestyle habits, are associated with increased risk of obesity in children.Methods: This school-based cross-sectional study was conducted among 106 participants (50 male and 56 female participants) aged 6-14 years selected by convenience sampling from four randomly selected primary schools of different regions of Dhaka city. A pre-tested questionnaire was used to collect data.Results: The prevalence of overweight and obesity among school-going children 24.5%, 68% respectively. Factors associated with being obese included type of game (χ2=34.036; p=0.001), total playtime (χ2=17.788; p=0.000), TV and computer watch time (χ2=27.321; p=0.007), spend money to buy fast food (χ2=26.451; p=0.002), eating days fast food in a week (χ2=24.825; p=0.003), type of tiffin (χ2=19.757; p=0.072).Conclusions: Less playtime, longer watching TV and computer, and eating more fast food are major risk factors for overweight and obesity among school-going children in Dhaka city. Interventions are needed to increase awareness of child overweight weight and obesity risk factors to decrease the prevalence of overweight and obesity.

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.

Primary Graft Dysfunction

2021 ◽  
Vol 42 (03) ◽  
pp. 368-379
Author(s):  
Jake G. Natalini ◽  
Joshua M. Diamond
Keyword(s):  
Risk Factors ◽  
Lung Transplantation ◽  
Ex Vivo ◽  
Significant Risk ◽  
Subsequent Development ◽  
Primary Graft Dysfunction ◽  
Graft Dysfunction ◽  
Donor Pool ◽  
Ex Vivo Lung Perfusion ◽  
Increased Risk

AbstractPrimary graft dysfunction (PGD) is a form of acute lung injury after transplantation characterized by hypoxemia and the development of alveolar infiltrates on chest radiograph that occurs within 72 hours of reperfusion. PGD is among the most common early complications following lung transplantation and significantly contributes to increased short-term morbidity and mortality. In addition, severe PGD has been associated with higher 90-day and 1-year mortality rates compared with absent or less severe PGD and is a significant risk factor for the subsequent development of chronic lung allograft dysfunction. The International Society for Heart and Lung Transplantation released updated consensus guidelines in 2017, defining grade 3 PGD, the most severe form, by the presence of alveolar infiltrates and a ratio of PaO2:FiO2 less than 200. Multiple donor-related, recipient-related, and perioperative risk factors for PGD have been identified, many of which are potentially modifiable. Consistently identified risk factors include donor tobacco and alcohol use; increased recipient body mass index; recipient history of pulmonary hypertension, sarcoidosis, or pulmonary fibrosis; single lung transplantation; and use of cardiopulmonary bypass, among others. Several cellular pathways have been implicated in the pathogenesis of PGD, thus presenting several possible therapeutic targets for preventing and treating PGD. Notably, use of ex vivo lung perfusion (EVLP) has become more widespread and offers a potential platform to safely investigate novel PGD treatments while expanding the lung donor pool. Even in the presence of significantly prolonged ischemic times, EVLP has not been associated with an increased risk for PGD.

Comorbid Conditions and GFR Predict Nonvertebral Fractures in Patients With Diabetes in an Ethnic-Specific Manner

2020 ◽  
Vol 105 (6) ◽  
pp. e2168-e2175
Author(s):  
Rajesh K Jain ◽  
Mark G Weiner ◽  
Huaqing Zhao ◽  
Tamara Vokes
Keyword(s):  
Risk Factors ◽  
Osteoporotic Fractures ◽  
Comorbid Conditions ◽  
Risk Of Fracture ◽  
Increased Risk ◽  
Major Osteoporotic Fractures ◽  
Specific Manner ◽  
Patients With Diabetes ◽  
Race Ethnicity ◽  
Insulin Use

Abstract Context Diabetes mellitus (DM) is associated with an increased risk of fracture, but it is not clear which diabetes and nondiabetes risk factors may be most important. Objective The aim of the study was to evaluate risk factors for incident major osteoporotic fractures (MOFs) of the hip, wrist, and humerus in African American (AA), Hispanic (HIS), and Caucasian (CA) subjects with DM. Methods This was a retrospective cohort study of 18 210 subjects with DM (7298 CA, 7009 AA and 3903 HIS) at least 40 years of age, being followed at a large healthcare system in Philadelphia, Pennsylvania. Results In a global model in CA with DM, MOF were associated with dementia (HR 4.16; 95% CI, 2.13-8.12), OSA (HR 3.35; 95% CI, 1.78-6.29), COPD (HR 2.43; 95% CI, 1.51-3.92), and diabetic neuropathy (HR 2.52; 95% CI, 1.41-4.50). In AA, MOF were associated with prior MOF (HR 13.67; 95% CI, 5.48-34.1), dementia (HR 3.10; 95% CI, 1.07-8.98), glomerular filtration rate (GFR) less than 45 (HR 2.05; 95% CI, 1.11-3.79), thiazide use (HR 0.54; 95% CI, 0.31-0.93), metformin use (HR 0.59; 95% CI, 0.36-0.97), and chronic steroid use (HR 5.03; 95% CI, 1.51-16.7). In HIS, liver disease (HR 3.06; 95% CI, 1.38-6.79) and insulin use (HR 2.93; 95% CI, 1.76-4.87) were associated with MOF. Conclusion In patients with diabetes, the risk of fracture is related to both diabetes-specific variables and comorbid conditions, but these relationships vary by race/ethnicity.

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