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Background: Venous thromboembolism (VTE) is a common complication of cancer. This study aimed to evaluate immature platelet fraction (IPF), mean platelet volume (MPV), P-selectin, D-dimer, and thrombin generation (TG) as predictive biomarkers for VTE and further the improvement of existing risk assessment models (RAMs). Methods: A prospective, observational, exploratory study was conducted on ambulatory cancer patients with indication for systemic chemotherapy. Baseline RAMs included the Khorana-, Vienna Cancer, Thrombosis-, Protecht-, ONKOTEV-, and Catscore. IPF, MPV, P-selectin, D-dimer, and TG were analysed at baseline and 3-month follow-up. Results: We enrolled 100 patients, of whom 89 completed the follow-up. Frequent tumour types were breast (30%), gastric (14%), gynaecological (14%), and colorectal (14%) cancer. Ten of the 89 patients (11.2%) developed VTE. The highest VTE rate was observed in patients with cholangiocarcinoma (3/5; 60%). Baseline D-dimer levels but not IPF, MPV, or P-selectin were associated with the risk of developing VTE (HR 6.9; p = 0.021). None of the RAMs showed statistical significance in predicting VTE. Peak thrombin and endogenous thrombin potential were lower in patients who developed VTE. Biomarker changes between baseline and follow-up were not associated with VTE risk. Conclusions: VTE risk was well predicted by baseline D-dimer levels. Adding D-dimer could improve existing RAMs to better identify patients who may benefit from primary VTE prophylaxis. The VTE risk among patients with cholangiocarcinoma should be further evaluated.

To assess whether angiotensin-converting enzyme inhibitors and third-generation dihydropyridine calcium channel blockers ameliorate diabetic complications, we compared glomerular filtration rate (GFR; primary outcome), cardiovascular events, retinopathy, and neuropathy in 380 hypertensive type 2 diabetics with albuminuria 2 (IQR: 0.16–0.50 mL/min per 1.73 m 2 ) on combined therapy, 0.36 mL/min per 1.73 m 2 (IQR: 0.18–0.53 mL/min per 1.73 m 2 ) on delapril, and 0.30 mL/min per 1.73 m 2 (IQR: 0.12–0.50 mL/min per 1.73 m 2 ) on placebo ( P =0.87 and P =0.53 versus combined therapy or delapril, respectively). Similar findings were observed when baseline GFR values were not considered for slope analyses. Albuminuria was stable in the 3 treatment groups. The hazard ratio (95% CI) for major cardiovascular events between combined therapy and placebo was 0.17 (0.04–0.78; P =0.023). Among 192 subjects without retinopathy at inclusion, the hazard ratio for developing retinopathy between combined therapy and placebo was 0.27 (0.07–0.99; P =0.048). Among 200 subjects with centralized neurological evaluation, the odds ratios for peripheral neuropathy at 3 years between combined therapy or delapril and placebo were 0.45 (0.24–0.87; P =0.017) and 0.52 (0.27–0.99; P =0.048), respectively. Glucose disposal rate decreased from 5.8±2.4 to 5.3±1.9 mg/kg per min on placebo ( P =0.03) but did not change on combined or delapril therapy. Treatment was well tolerated. In hypertensive type 2 diabetic patients, combined manidipine and delapril therapy failed to slow GFR decline but safely ameliorated cardiovascular disease, retinopathy, and neuropathy and stabilized insulin sensitivity.

OBJECTIVE To describe the prevalence and determinants of hyperfiltration (glomerular filtration rate [GFR] ≥120 mL/min/1.73 m2), GFR decline, and nephropathy onset or progression in type 2 diabetic patients with normo- or microalbuminuria. RESEARCH DESIGN AND METHODS We longitudinally studied 600 hypertensive type 2 diabetic patients with albuminuria RESULTS Over a median (range) follow-up of 4.0 (1.7–8.1) years, GFR declined by 3.37 (5.71–1.31) mL/min/1.73 m2 per year. GFR change was bimodal over time: a larger reduction at 6 months significantly predicted slower subsequent decline (coefficient: −0.0054; SE: 0.0009), particularly among hyperfiltering patients. A total of 90 subjects (15%) were hyperfiltering at inclusion, and 11 of 47 (23.4%) patients with persistent hyperfiltration progressed to micro- or macroalbuminuria versus 53 (10.6%) of the 502 who had their hyperfiltration ameliorated at 6 months or were nonhyperfiltering since inclusion (hazard ratio 2.16 [95% CI 1.13–4.14]). Amelioration of hyperfiltration was independent of baseline characteristics or ACE inhibition. It was significantly associated with improved BP and metabolic control, amelioration of GDR, and slower long-term GFR decline on follow-up. CONCLUSIONS Despite intensified treatment, patients with type 2 diabetes have a fast GFR decline. Hyperfiltration affects a subgroup of patients and may contribute to renal function loss and nephropathy onset or progression. Whether amelioration of hyperfiltration is renoprotective is worth investigating.

There are no adequate studies that have formally tested the performance of different estimating formulas in patients with type 2 diabetes both with and without overt nephropathy. Here we evaluated the agreement between baseline GFRs, GFR changes at month 6, and long-term GFR decline measured by iohexol plasma clearance or estimated by 15 creatinine-based formulas in 600 type 2 diabetics followed for a median of 4.0 years. Ninety patients were hyperfiltering. The number of those identified by estimation formulas ranged from 0 to 24:58 were not identified by any formula. Baseline GFR was significantly underestimated and a 6-month GFR reduction was missed in hyperfiltering patients. Long-term GFR decline was also underestimated by all formulas in the whole study group and in hyper-, normo-, and hypofiltering patients considered separately. Five formulas generated positive slopes in hyperfiltering patients. Baseline concordance correlation coefficients and total deviation indexes ranged from 32.1% to 92.6% and from 0.21 to 0.53, respectively. Concordance correlation coefficients between estimated and measured long-term GFR decline ranged from -0.21 to 0.35. The agreement between estimated and measured values was also poor within each subgroup considered separately. Thus, our study questions the use of any estimation formula to identify hyperfiltering patients and monitor renal disease progression and response to treatment in type 2 diabetics without overt nephropathy.