Active chest tube clearance after aortic valve surgery did not influence amount residual pericardial fluid after aortic valve replacement in a randomised trial.

Objective. Evaluate if the use of active clearance of chest tubes after aortic valve surgery influenced bleeding and reduced postoperative residual pericardial effusion. Design. Prospective randomised trial comparing PleuraFlow® 32 F chest tube with FlowGlide™ active clearance to a standard Argyle® 32 F chest tube in 100 patients undergoing aortic valve surgery. Chest tube outputs and pericardial effusion measurements assessed by two-dimensional transthoracic echocardiography were recorded before hospital discharge. Results. Postoperative chest tube outputs per hour did not differ between the two groups. The median chest tube output was 400 mL for patients who had a PleuraFlow® chest tube vs. 490 mL for patients with an Argyle® chest tube (p = .08). Pericardial effusions ≥ 2 mm were detected in 76% vs. 68% of the patients (p = .50) and postoperative atrial fibrillation occurred in 42% vs. 34% (p = .54), respectively. Conclusions. Use of active clearance chest tubes, compared to standard chest tubes after aortic valve surgery did not differ significantly regarding postoperative bleeding or degree of pericardial effusion as measured by echocardiography prior to hospital discharge.

Main pancreatic duct dilation greater than 6 mm is associated with an increased risk of high-grade dysplasia and cancer in IPMN patients.

INTRODUCTION: IPMNs, considered precursor lesions of pancreatic adenocarcinoma (PDAC), might display histological alteration varying from low-grade dysplasia (LGD) to cancer. Nevertheless, the prevalence of PDAC is far below the prevalence of IPMN; therefore, not all of these precursor lesions finally progress to cancer. Preoperative features consistent with and finding at final histology of high-grade dysplasia (HGD) or cancer are currently lacking. The aim of this study is to correlate the presence of preoperative clinical features with the finding of advance lesions at final histology. METHODS: This is retrospective cohort analysis of patients who underwent surgery for histologically confirmed IPMNs at Karolinska University Hospital, from 2008 to 2015. RESULTS: MPD 6-9.9 mm and ≥ 10 mm were associated with an increased risk of HGD/cancer (respectively, OR 2.92, CI 1.38-6.20, p = 0.005 and OR 2.65, CI 1.12-6.25, p = 0.02). Preoperative high CA19.9 and jaundice were both associated with a higher risk of HGD/cancer at final histology (respectively, OR 4.15, CI 1.90-9.05, p = 0.0003 and OR 15.36, CI 1.94-121.22, p = 0.009). At sex- and age-adjusted multivariable logistic regression analysis, MPD between 6 and 9.9 mm (OR 2.64, CI 1.15-6.06, p = 0.02), jaundice (OR 12.43, CI 1.44-106.93, p = 0.02), and elevated CA19.9 (OR 3.71, CI 1.63-8.46, p = 0.001) remained associated with the occurrence of HGD/cancer. DISCUSSION: The presence of MPD dilation ≥ 6 mm, jaundice, and elevated CA19.9 in IPMN patients are consistent with the finding for HGD/cancer at final histology, thus representing possible markers of advanced lesions suitable for earlier or preventive curative surgical treatment.

Bioinformatory-assisted analysis of next-generation sequencing data for precision medicine in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a tumor with an extremely poor prognosis, predominantly as a result of chemotherapy resistance and numerous somatic mutations. Consequently, PDAC is a prime candidate for the use of sequencing to identify causative mutations, facilitating subsequent administration of targeted therapy. In a feasibility study, we retrospectively assessed the therapeutic recommendations of a novel, evidence-based software that analyzes next-generation sequencing (NGS) data using a large panel of pharmacogenomic biomarkers for efficacy and toxicity. Tissue from 14 patients with PDAC was sequenced using NGS with a 620 gene panel. FASTQ files were fed into treatmentmap. The results were compared with chemotherapy in the patients, including all side effects. No changes in therapy were made. Known driver mutations for PDAC were confirmed (e.g. KRAS, TP53). Software analysis revealed positive biomarkers for predicted effective and ineffective treatments in all patients. At least one biomarker associated with increased toxicity could be detected in all patients. Patients had been receiving one of the currently approved chemotherapy agents. In two patients, toxicity could have been correctly predicted by the software analysis. The results suggest that NGS, in combination with an evidence-based software, could be conducted within a 2-week period, thus being feasible for clinical routine. Therapy recommendations were principally off-label use. Based on the predominant KRAS mutations, other drugs were predicted to be ineffective. The pharmacogenomic biomarkers indicative of increased toxicity could be retrospectively linked to reported negative side effects in the respective patients. Finally, the occurrence of somatic and germline mutations in cancer syndrome-associated genes is noteworthy, despite a high frequency of these particular variants in the background population. These results suggest software-analysis of NGS data provides evidence-based information on effective, ineffective and toxic drugs, potentially forming the basis for precision cancer medicine in PDAC.

New-onset type 2 diabetes, elevated HbA1c, anti-diabetic medications, and risk of pancreatic cancer.

BACKGROUND: Associations between type 2 diabetes, anti-diabetic medications and pancreatic cancer are controversial. This study aims to clarify such associations with new-onset type 2 diabetes and repeated measurements of glycated haemoglobin (HbA1c) levels. METHODS: A nested case-control study was initiated from the Health Improvement Network (THIN) in UK from 1996 to 2010. Information of pancreatic cancer cases was retrieved electronically from the medical records and manually validated. Control subjects were randomly selected and frequency-matched to the cases on sex, age, and calendar years. Multivariable unconditional logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI), and adjusted for potential confounders. RESULTS: Among 1,574,768 person-years of follow-up, 529 pancreatic cancer cases and 5000 controls were identified. Type 2 diabetes, or changed HbA1c levels (rather than HbA1c levels at diabetes diagnosis) in diabetes patients (⩾4 mmol mol(-1) compared with <0 mmol mol(-1)) were followed by an increased OR of pancreatic cancer (OR, 2.16, 95% CI 1.72-2.72 and OR, 5.06, 95% CI 1.52-16.87, respectively). Among the anti-diabetic medications in diabetes patients, the OR for insulin users was 25.57 (95% CI 11.55-56.60), sulphonylureas 2.22 (95% CI 1.13, 4.40), and metformin users 1.46 (95% CI 0.85-2.52), compared with no use of any anti-diabetic medications. CONCLUSIONS: New-onset type 2 diabetes and, particularly, diabetes with rising HbA1c seem to be independent risk factors for pancreatic cancer. The relation between different anti-diabetic medications and pancreatic cancer seems to vary in strength, with the highest risk among users of insulin.