Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.

BACKGROUND: Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). METHODS: We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. RESULTS: Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. CONCLUSIONS: Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

People living with type 2 diabetes (T2D) are more likely to develop problems with their heart or blood circulation, known as cardiovascular disease (CVD), than people who do not have T2D. However, it can be difficult to predict which people with T2D are most likely to develop CVD. This is because current approaches, such as blood tests, do not identify all people with T2D who are at an increased risk of CVD. In this study we reviewed published papers that investigated the differences between people with T2D who experienced CVD compared to those who did not. We found some indicators that could potentially be used to determine which people with T2D are most likely to develop CVD. More studies are needed to determine how useful these are. However, they could potentially be used to enable clinicians to provide targeted advice and treatment to those people with T2D at most risk of developing CVD.

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis.

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Initiation of the SGLT2 inhibitor canagliflozin to prevent kidney and heart failure outcomes guided by HbA1c, albuminuria, and predicted risk of kidney failure.

BACKGROUND: Sodium glucose co-transporter-2 (SGLT2) inhibitors reduce the risk of kidney and heart failure events independent of glycemic effects. We assessed whether initiation of the SGLT2 inhibitor canagliflozin guided by multivariable predicted risk based on clinical characteristics and novel biomarkers is more efficient to prevent clinical outcomes compared to a strategy guided by HbA1c or urinary-albumin-creatinine ratio (UACR) alone. METHODS: We performed a post-hoc analysis of the CANVAS trial including 3713 patients with available biomarker measurements. We compared the number of composite kidney (defined as a sustained 40% decline in eGFR, chronic dialysis, kidney transplantation, or kidney death) and composite heart failure outcomes (defined as heart failure hospitalization or cardiovascular (CV) death) prevented per 1000 patients treated for 5 years when canagliflozin was initiated in patients according to HbA1c ≥ 7.5%, UACR, or multivariable risk models consisting of: (1) clinical characteristics, or (2) clinical characteristics and novel biomarkers. Differences in the rates of events prevented between strategies were tested by Chi2-statistic. RESULTS: After a median follow-up of 6.1 years, 144 kidney events were recorded. The final clinical model included age, previous history of CV disease, systolic blood pressure, UACR, hemoglobin, body weight, albumin, estimated glomerular filtration rate, and randomized treatment assignment. The combined biomarkers model included all clinical characteristics, tumor necrosis factor receptor-1, kidney injury molecule-1, matrix metallopeptidase-7 and interleukin-6. Treating all patients with HbA1c ≥ 7.5% (n = 2809) would prevent 33.0 (95% CI 18.8 to 43.3 ) kidney events at a rate of 9.6 (95% CI 5.5 to 12.6) events prevented per 1000 patients treated for 5 years. The corresponding rates were 5.8 (95% CI 3.4 to 7.9), 16.6 (95% CI 9.5 to 22.0) (P < 0.001 versus HbA1c or UACR approach), and 17.5 (95% CI 10.0 to 23.0) (P < 0.001 versus HbA1c or UACR approach; P = 0.54 versus clinical model). Findings were similar for the heart failure outcome. CONCLUSION: Initiation of canagliflozin based on an estimated risk-based approach prevented more kidney and heart failure outcomes compared to a strategy based on HbA1c or UACR alone. There was no apparent gain from adding novel biomarkers to the clinical risk model. These findings support the use of risk-based assessment using clinical markers to guide initiation of SGLT2 inhibitors in patients with type 2 diabetes.

Prediction of the Effects of Liraglutide on Kidney and Cardiovascular Outcomes Based on Short-Term Changes in Multiple Risk Markers.

Aims: The LEADER trial demonstrated that the glucagon-like peptide-1 receptor agonist (GLP1-RA) liraglutide reduces kidney and cardiovascular (CV) risk in patients with type 2 diabetes. We previously developed a Parameter Response Efficacy (PRE) score that translates multiple short-term risk marker changes, from baseline to first available follow-up measurement, into a predicted long-term drug effect on clinical outcomes. The objective of this study was to assess the accuracy of the PRE score in predicting the efficacy of liraglutide in reducing the risk of kidney and CV outcomes. Methods: Short-term changes in glycated hemoglobin (HbA1c), systolic blood pressure (BP), urinary-albumin-creatinine-ratio (UACR), hemoglobin, body weight, high-density-lipoprotein (HDL) cholesterol, low-density-lipoprotein (LDL) cholesterol, and potassium were monitored in the LEADER trial. Associations between risk markers and kidney or CV outcomes were established using a multivariable Cox proportional hazards model in a separate pooled database of 6,355 patients with type 2 diabetes. The regression coefficients were then applied to the short-term risk markers in the LEADER trial to predict the effects of liraglutide on kidney (defined as a composite of doubling of serum creatinine or end-stage kidney disease) and CV (defined as a composite of non-fatal myocardial infarction, non-fatal stroke, and CV death) outcomes. Results: Liraglutide compared to placebo reduced HbA1c (1.4%), systolic BP (3.0 mmHg), UACR (13.2%), body weight (2.3 kg), hemoglobin (2.6 g/L), and increased HDL-cholesterol (0.01 mmol/L) (all p-values <0.01). Integrating multiple risk marker changes in the PRE score resulted in a predicted relative risk reduction (RRR) of 16.2% (95% CI 13.7-18.6) on kidney outcomes which was close to the observed RRR of 15.5% (95% CI -9.0-34.6). For the CV outcome, the PRE score predicted a 7.6% (95% CI 6.8-8.3) RRR, which was less than the observed 13.2% (95% CI 3.2-22.2) RRR. Conclusion: Integrating multiple short-term risk markers using the PRE score adequately predicted the effect of liraglutide on the composite kidney outcome. However, the PRE score underestimated the effect of liraglutide for the composite CV outcome, suggesting that the risk markers included in the PRE score do not fully capture the CV benefit of liraglutide.

Association of diuretic use with increased risk for long-term post-transplantation diabetes mellitus in kidney transplant recipients.

BACKGROUND: Post-transplantation diabetes mellitus (PTDM) is a major clinical problem in kidney transplant recipients (KTRs). Diuretic-induced hyperglycaemia and diabetes have been described in the general population. We aimed to investigate whether diuretics also increase PTDM risk in KTRs. METHODS: We included 486 stable outpatient KTRs (with a functioning graft ≥1 year) without diabetes from a prospective cohort study. Participants were classified as diuretic users and non-users based on their medication use verified by medical records. RESULTS: At the baseline study, 168 (35%) KTRs used a diuretic (thiazide, n = 74; loop diuretic, n = 76; others, n = 18) and 318 KTRs did not use a diuretic. After 5.2 years [interquartile range (IQR) 4.0‒5.9] of follow up, 54 (11%) KTRs developed PTDM. In Cox regression analyses, diuretic use was associated with incident PTDM, independent of age, sex, fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) {hazard ratio [HR] 3.28 [95% confidence interval (CI) 1.84-5.83]; P <0.001}. Further adjustment for potential confounders, including lifestyle, family history of cardiovascular disease, use of other medication, kidney function, transplantation-specific parameters, BMI, lipids and blood pressure did not materially change the association. Moreover, in Cox regression analyses, both thiazide and loop diuretics associated with the development of PTDM, independent of age, sex, FPG and HbA1c [HR 2.70 (95% CI 1.24-5.29); P = 0.012 and HR 5.08 (95% CI 2.49-10.34); P <0.001), respectively]. CONCLUSIONS: This study demonstrates that diuretics overall are associated with an increased risk of developing PTDM in KTRs, independent of established risk factors for PTDM development. The association was present for both thiazide and loop diuretics.

Precision medicine approaches for diabetic kidney disease: opportunities and challenges.

The prevalence of end-stage kidney disease (ESKD) continuously increases worldwide. The increasing prevalence parallels the growth in the number of people with diabetes, which is the leading cause of ESKD. Early diagnosis of chronic kidney disease (CKD) in patients with diabetes and appropriate intervention is important to delay the progression of kidney function decline and prevent ESKD. Rate of CKD progression and response to treatment varies among patients with diabetes, highlighting the need to tailor individual treatment. In this review, we describe recent advances and areas for future studies with respect to precision medicine in diabetic kidney disease (DKD). DKD is a multi-factorial disease that is subject in part to genetic heritability, but is also influenced by various exogenous mediators, such as environmental or dietary factors. Genetic testing so far has limited utility to facilitate early diagnosis, classify progression or evaluate response to therapy. Various biomarker-based approaches are currently explored to identify patients at high risk of ESKD and to facilitate decision-making for targeted therapy. These studies have led to discovery and validation of a couple of inflammatory proteins such as circulating tumour necrosis factor receptors, which are strong predictors of kidney disease progression. Moreover, risk and drug-response scores based on multiple biomarkers are developed to predict kidney disease progression and long-term drug efficacy. These findings, if implemented in clinical practice, will pave the way to move from a one-size-fits-all to a one-fit-for-everyone approach.

A novel drug response score more accurately predicts renoprotective drug effects than existing renal risk scores.

BACKGROUND: Risk factor-based equations are used to predict risk of kidney disease progression in patients with type 2 diabetes order to guide treatment decisions. It is, however, unknown whether these models can also be used to predict the effects of drugs on clinical outcomes. METHODS: The previously developed Parameter Response Efficacy (PRE) score, which integrates multiple short-term drug effects, was first compared with the existing risk scores, Kidney Failure Risk Equation (KFRE) and The Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) renal risk score, in its performance to predict end-stage renal disease (ESRD; KFRE) and doubling of serum creatinine or ESRD (ADVANCE). Second, changes in the risk scores were compared after 6 months' treatment to predict the long-term effects of losartan on these renal outcomes in patients with type 2 diabetes and chronic kidney disease. RESULTS: The KFRE, ADVANCE and PRE scores showed similarly good performance in predicting renal risk. However, for prediction of the effect of losartan, the KFRE risk score predicted a relative risk change in the occurrence of ESRD of 3.1% [95% confidence interval (CI) -5 to 12], whereas the observed risk change was -28.8% (95% CI -42.0 to -11.5). For the composite endpoint of doubling of serum creatinine or ESRD, the ADVANCE score predicted a risk change of -12.4% (95% CI -17 to -7), which underestimated the observed risk change -21.8% (95% CI -34 to -6). The PRE score predicted renal risk changes that were close to the observed risk changes with losartan treatment [-24.0% (95% CI -30 to -17) and -22.6% (95% CI -23 to -16) for ESRD and the composite renal outcome, respectively]. CONCLUSION: A drug response score such as the PRE score may assist in improving clinical decision making and implement precision medicine strategies.

Prediction of the Effects of Empagliflozin on Cardiovascular and Kidney Outcomes Based on Short-Term Changes in Multiple Risk Markers.

Aims: The EMPA-REG OUTCOME trial demonstrated that the sodium-glucose cotransporter-2 inhibitor (SGLT2) empagliflozin reduces the risk of cardiovascular (CV) and kidney outcomes in patients with type 2 diabetes. We previously developed the parameter response efficacy (PRE) score, which translates drug effects on multiple short-term risk markers into a predicted long-term treatment effect on clinical outcomes. The main objective of this study was to assess the accuracy of the PRE score in predicting the efficacy of empagliflozin in reducing the risk of CV and kidney outcomes. Methods: Short-term (baseline to 6-months) changes in glycated hemoglobin (HbA1c), systolic blood pressure (SBP), urinary-albumin-creatinine-ratio (UACR), hemoglobin, body weight, high-density-lipoprotein (HDL) cholesterol, low-density-lipoprotein (LDL) cholesterol, uric acid, and potassium were determined among 7020 patients with type 2 diabetes and established CV disease in the EMPA-REG OUTCOME trial. The beta-coefficients, derived from a Cox proportional hazards model in a pooled database consisting of 6355 patients with type 2 diabetes, were applied to the short-term risk markers in the EMPA-REG OUTCOME trial to predict the empagliflozin-induced impact on CV (defined as a composite of non-fatal myocardial infarction, non-fatal stroke, or CV death) and kidney (defined as a composite of doubling of serum creatinine or end-stage kidney disease) outcomes. Results: Empagliflozin compared to placebo reduced HbA1c (0.6%), SBP (4.2 mmHg), UACR (13.0%), body weight (2.1 kg), uric acid (20.4 µmol/L), and increased hemoglobin (6.6 g/L), LDL-cholesterol (0.1 mmol/L) and HDL-cholesterol (0.04 mmol/L) (all p<0.01). Integrating these effects in the PRE score resulted in a predicted relative risk reduction (RRR) for the CV outcome of 6.4% (95% CI 1.4-11.7), which was less than the observed 14.7% (95% CI 1.3-26.4%) RRR. For the kidney outcome, the PRE score predicted a RRR of 33.4% (95% CI 26.2-39.8); the observed RRR was 46.9% (95% CI 26.8-61.5). In a subgroup of 2,811 patients with UACR ≥30 mg/g at baseline, the PRE score predicted RRR was 40.8% (95% CI 31.2-49.1) vs. the observed RRR of 40.8% (95% CI 12.4-60.0) for the kidney outcome. Conclusions: Integrating multiple short-term risk marker changes in the PRE score underestimated the effect of empagliflozin on CV and kidney outcomes, suggesting that the currently used risk markers do not fully capture the effect of empagliflozin. In patients with increased albuminuria, the PRE score adequately predicted the effect of empagliflozin on kidney outcomes.

Comparison of nurses and general caregivers' knowledge, attitude, and practice on medication administration process and their distress level in long-term care facilities across Penang, Kuala Lumpur, and Selangor of Malaysia.

AIM: Comparing nurses and general caregivers' knowledge, attitude, and practices (KAP) on medication administration process in long-term care (LTC) setting and an assessment of their stress, anxiety, and depression (SAD) level. METHODS: A cross-sectional survey was conducted among nurses and general caregivers working in LTC using a validated questionnaire. Consisting of demographic characteristics (Section 1); 40 questions on KAP (Section 2); and assessment of Depression, Anxiety, and Stress Scale (DASS-21) (Section 3). RESULTS: 155 formally paid staffs in 26 LTC facilities were recruited. Nurses scored significantly higher in the knowledge section compared to caregivers (12.4 ± 1.7 vs. 4.5 ± 3.8; P < 0.001); better attitude (41.5 ± 4.8 vs. 30.8 ± 7.3; P < 0.001); and better practice (65.2 ± 8.5 vs. 40.3 ± 10.9; P < 0.001), respectively. SAD scores reveal that caregivers had significantly higher level of stress, anxiety, and depression compared to the nurses. DISCUSSION: General caregivers exhibit poorer knowledge on aspects pertaining to posology, appropriate methods of drug administration, and side effects of common drugs used by the elderly. Compared to nurses, the general caregivers also reported poorer medication administration practices; including not checking labels and expiry dates prior to administration, and not providing basic information about medication therapy to the residents. However, both nurses and general caregivers reported positive attitudes in their role as caregivers. They take pride and satisfaction in their occupation providing support to the elderly. CONCLUSION: General caregivers demonstrated lesser knowledge, poorer attitude, and practices towards medication administration processes, in addition to higher SAD score in LTC facilities.