Relationship between intraoperative serum lactate and hemoglobin levels on postoperative renal function in patients undergoing elective cardiac surgery.

BACKGROUND AND AIM: We examined the relationship between serum lactate and hemoglobin levels on renal function and postoperative outcome in low-risk elective coronary artery bypass graft (CABG) patients. METHODS: Intraoperative hemoglobin and lactate levels were measured in elective isolated CABG patients. Patients with renal dysfunction (baseline creatinine>2 mg/dL) were excluded. Multivariate logistic regression was used to determine associations between lactate, hemoglobin, and acute kidney injury (AKI). RESULTS: A total of 375 patients met study requirements, and 56/375 (15%) developed AKI. Of the patients who developed AKI, 43/278 (15.5%) were males, 13/97 (13.4%) females, and 11/44 (25%) African-Americans. Bivariate analysis between AKI and non-AKI subgroups found significant differences in age, race, baseline estimated glomerular filtration rate, preoperative hemoglobin, peak serum lactate, initial hemoglobin, and nadir hemoglobin. A high peak Lactate level (odds ratio [OR] 1.44[1.15-1.82]), low hemoglobin (OR 0.69[0.49-0.96]), and African American race (OR 2.26[0.96-5.05]) were independently associated with acute kidney injury. A significant relationship between decreasing intraoperative hemoglobin and increasing intraoperative serum lactate levels was observed exclusively in patients who developed postoperative AKI. Serum creatinine levels peaked, on average, 48 h postoperatively in the AKI subset of patients. CONCLUSION: In this series, 15% of patients who underwent elective cardiopulmonary bypass developed transient acute renal dysfunction. High lactate levels and low hemoglobin levels during cardiopulmonary bypass were associated with an increased risk of kidney injury.

Case Report: Unmasked Inherited Dysfibrinogenemia After Everolimus Therapy.

A previously hemostatically asymptomatic patient with common variable hypogammaglobulinemia was given everolimus to prevent growth of her liver. Within several months, the patient developed a severe bleeding disorder. The bleeding was due to fibrin polymerization defect that upon sequencing was shown to be dysfibrinogenemia Krakow III. Elimination of the mTor inhibitor ameliorated the clinical bleeding state.

Computer-aided diagnosis via model-based shape analysis: automated classification of wall motion abnormalities in echocardiograms.

RATIONALE AND OBJECTIVE: Shape analysis of endocardial contour sequences from echocardiograms can provide classification of wall motion abnormalities (WMA). MATERIALS AND METHODS: We previously reported on active appearance motion models (AAMM) for automated detection of endocardial contours in sequences of echocardiograms. The shape analysis of AAMM renders eigenvariations of shape/motion, including typical normal and pathologic endocardial contraction patterns. A set of stress echocardiograms (single-beat four-chamber and two-chamber sequences with expert-verified endocardial contours) of 129 infarct patients was split randomly into training (n = 65) and testing (n = 64) sets. AAMMs were generated from the training set and AAMM shape coefficients (ASCs) were extracted for all sequences and statistically related to regional/global visual wall motion scoring (VWMS) and volumetric parameters. RESULTS: Linear regression showed clear correlations between ASCs and VWMS. Discriminant analysis showed good prediction by ASCs of both segmental (74% correctness) and global WMA (90% correctness). Volumetric parameters correlated poorly to regional VWMS. CONCLUSION: 1) ASCs show promising accuracy for automated WMA classification. 2) VWMS and endocardial border motion are closely related; with accurate automated border detection, automated WMA classification should be feasible. 3) ASC shape analysis allows contour set evaluation by direct comparison to clinical parameters.

Biochemical and clinical aspects of the human flavin-containing monooxygenase form 3 (FMO3) related to trimethylaminuria.

Trimethylaminuria is a rare metabolic disorder that is associated with abnormal amounts of the dietary-derived trimethylamine. Excess unmetabolized trimethylamine in the urine, sweat and other body secretions confers a strong, foul body odor that can affect the individual's ability to work or engage in social activities. This review summarizes the biochemical aspects of the condition and the classification of the disorder into: 1) primary genetic form, 2) acquired form, 3) childhood forms, 4) transient form associated with menstruation, 5) precursor overload and 6) disease states. The genetic variability of the flavin-containing monooxygenase (form 3) that is responsible for detoxication and deodoration of trimethylamine is discussed and put in context with other variant forms of the flavin-containing monooxygenase (forms 1-5). The temporal-selective expression of flavin-containing monooxygenase forms 1 and 3 is discussed in terms of an explanation for childhood trimethylaminuria. Information as to whether variants of the flavin-containing monooxygenase form 3 contributes to hypertension and/or other diseases are presented. Discussion is provided outlining recent bioanalytical approaches to quantify urinary trimethylamine and trimethylamine N-oxide and plasma choline as well as data on self-reporting individuals tested for trimethylaminuria. Finally, trimethylaminuria treatment strategies and nutritional support are described including dietary sources of trimethylamine, vitamin supplementation and drug treatment and issues related to trimethylaminuria in pregnancy and lactation are discussed. The remarkable progress in the biochemical, genetic, clinical basis for understanding the trimethylaminuria condition is summarized and points to needs in the treatment of individuals suffering from trimethylaminuria.

Automatic segmentation of echocardiographic sequences by active appearance motion models.

A novel extension of active appearance models (AAMs) for automated border detection in echocardiographic image sequences is reported. The active appearance motion model (AAMM) technique allows fully automated robust and time-continuous delineation of left ventricular (LV) endocardial contours over the full heart cycle with good results. Nonlinear intensity normalization was developed and employed to accommodate ultrasound-specific intensity distributions. The method was trained and tested on 16-frame phase-normalized transthoracic four-chamber sequences of 129 unselected infarct patients, split randomly into a training set (n = 65) and a test set (n = 64). Borders were compared to expert drawn endocardial contours. On the test set, fully automated AAMM performed well in 97% of the cases (average distance between manual and automatic landmark points was 3.3 mm, comparable to human interobserver variabilities). The ultrasound-specific intensity normalization proved to be of great value for good results in echocardiograms. The AAMM was significantly more accurate than an equivalent set of two-dimensional AAMs.

3-D active appearance models: segmentation of cardiac MR and ultrasound images.

A model-based method for three-dimensional image segmentation was developed and its performance assessed in segmentation of volumetric cardiac magnetic resonance (MR) images and echocardiographic temporal image sequences. Comprehensive design of a three-dimensional (3-D) active appearance model (AAM) is reported for the first time as an involved extension of the AAM framework introduced by Cootes et al. The model's behavior is learned from manually traced segmentation examples during an automated training stage. Information about shape and image appearance of the cardiac structures is contained in a single model. This ensures a spatially and/or temporally consistent segmentation of three-dimensional cardiac images. The clinical potential of the 3-D AAM is demonstrated in short-axis cardiac MR images and four-chamber echocardiographic sequences. The method's performance was assessed by comparison with manually identified independent standards in 56 clinical MR and 64 clinical echo image sequences. The AAM method showed good agreement with the independent standard using quantitative indexes of border positioning errors, endo- and epicardial volumes, and left ventricular mass. In MR, the endocardial volumes, epicardial volumes, and left ventricular wall mass correlation coefficients between manual and AAM were R2 = 0.94, 0.97, 0.82, respectively. For echocardiographic analysis, the area correlation was R2 = 0.79. The AAM method shows high promise for successful application to MR and echocardiographic image analysis in a clinical setting.