Hemolytic transfusion reactions after administration of intravenous immune (gamma) globulin: a case series analysis

BACKGROUND: This case series summarizes our observations of hemolytic reactions after the administration of large amounts of intravenous immune (gamma) globulin (IVIG). STUDY DESIGN AND METHODS: Cases of hemolysis were identified by a decrease in hemoglobin not otherwise explained following IVIG administration. RESULTS: Sixteen cases were identified over a 2 1/2-year period at the Ottawa Hospital of approximately 1000 patients receiving IVIG (1.6%). Characteristics of these patients include a large dose of IVIG, female sex, non-O blood group, and underlying inflammatory state. CONCLUSIONS: Significant hemolysis may occur after the administration of large doses of IVIG. A two-step mechanism of hemolysis is proposed, sensitization by ABO isohemagglutinins followed by phagocytosis by activated macrophages. A simple protocol to facilitate the early detection of such cases is presented.     

Serotonin and Dopamine: Unifying Affective, Activational, and Decision Functions

Serotonin, like dopamine (DA), has long been implicated in adaptive behavior, including decision making and reinforcement learning. However, although the two neuromodulators are tightly related and have a similar degree of functional importance, compared with DA, we have a much less specific understanding about the mechanisms by which serotonin affects behavior. Here, we draw on recent work on computational models of dopaminergic function to suggest a framework by which many of the seemingly diverse functions associated with both DA and serotonin—comprising both affective and activational ones, as well as a number of other functions not overtly related to either—can be seen as consequences of a single root mechanism.     

Validity and reliability of the Geriatric Anxiety Inventory in Parkinson's disease*†

Aim: To examine the psychometric properties of a novel anxiety rating scale, the Geriatric Anxiety Inventory (GAI) in Parkinson's disease (PD). Method: The predictive validity of the GAI was tested against the presence of any DSM‐IV anxiety disorders in 58 PD patients using receiver operating curve analysis. The concurrent validity of this scale was also studied against the state half of the Spielberger State Trait Anxiety Inventory (STAI). The internal consistency and test–retest reliability of the GAI were also examined. Results: The GAI displayed good concurrent validity against the STAI and the DSM‐IV. It also showed good internal consistency and test–retest reliability. Conclusions: This study suggested that the GAI is an appropriate scale to use in non‐demented PD patients.     

Natriuretic Peptides in Chronic Kidney Disease

Background and objectives: B-type natriuretic peptide (BNP) and amino-terminal pro-B-type natriuretic peptide (NT-proBNP) are biomarkers of cardiovascular disease that is common in patients with chronic kidney disease (CKD). Conflicting data on the influence of glomerular filtration rate (GFR) on BNP and NT-proBNP levels in CKD may stem from failure to account fully for the effects of coexistent cardiac disease, dysfunction, and volume overload.Design, setting, participants, & measurements: Prospective head-to-head comparison of plasma BNP and NT-proBNP in ambulatory euvolemic CKD patients with normal LV ejection fraction and no manifest cardiac or vascular disease. GFR was estimated by the Modification of Diet in Renal Disease formula, BNP and NT-proBNP measured using Abbott AxSYM and Roche Elecsys assays, respectively, and cardiac morphology and function assessed by transthoracic echocardiography.Results: In 142 patients (42% female) of mean age 60 ± 11 yr, mean left ventricular ejection fraction was 71% ± 6%, GFR 38 ± 14 ml/min per 1.73 m², and median BNP and NT-proBNP level 59 and 311 pg/ml, respectively. Multivariate predictors of NT-proBNP level were GFR, β-blocker usage, LV mass index, and hemoglobin level. Plasma BNP was independently predicted by LV mass index and β-blocker usage but not GFR. In the 74 patients without diastolic dysfunction, there was a significant rise in NT-proBNP but not BNP as GFR declined.Conclusions: Unlike NT-proBNP, plasma BNP level is relatively independent of GFR. BNP may therefore be the more appropriate biomarker to screen for cardiac dysfunction in CKD.Patients with chronic kidney disease (CKD) are at increased risk of cardiovascular disease. Natriuretic peptides (NPs), biomarkers of myocardial dysfunction (1), offer the potential for early detection and risk stratification of cardiac disease, as evident in emergency department (2) and community (3,4) settings. This screening utility could be extended to CKD patients asymptomatic of cardiovascular disease.However, the precise influence of CKD on circulating levels of B-type natriuretic peptide (BNP) and amino-terminal pro-B-type natriuretic peptide (NT-proBNP), the two commonly used NPs in clinical practice, continues to be debated. Dependence of plasma BNP on glomerular filtration rate (GFR) has been reported among patients with and without heart failure (HF) (5,6), but this relationship may not be independent of cardiac or volume-related factors (7,8). The data on NT-proBNP in renal dysfunction are more concordant but were derived from populations that included patients with myocardial infarction, reduced left ventricular (LV) ejection fraction (LVEF), or HF (9,10). Indeed, most studies examining the impact of renal dysfunction on NPs uniformly included such patients (5,6,8–10). Recent Doppler myocardial imaging studies have shown that even HF patients with normal LVEF have reduced LV contractility compared with controls (11,12).To limit confounding by cardiac dysfunction or volume overload, we prospectively constituted a clinically euvolemic CKD cohort without symptoms or history of cardiac disease and normal LVEF and regional function. We measured circulating levels of both NPs, hypothesizing that, in these patients, BNP can be shown to be relatively independent of GFR compared with NT-proBNP if cardiac and loading factors can be comprehensively accounted for.     

Patients with osteosarcoma with a single pulmonary nodule on computed tomography: a single-institution experience

Background/PurposeThe purpose of this study is to determine if patients with osteosarcoma (OS) with metachronous metastatic pulmonary disease presenting with a single pulmonary nodule (SPN) on computed tomography (CT) were found to have other lesions at the time of thoracotomy.MethodsData were collected retrospectively on consecutive patients with OS treated at our institution from 1982 to 2007. Patients with no evidence of disease at the end of initial therapy who subsequently relapsed in the lung were identified.ResultsIn our study, 16 (8%) of 198 patients with OS with metachronous metastatic pulmonary disease presented with a SPN on CT scan. In all patients, only 1 metastatic nodule for OS was found at the time of thoracotomy. The median time between diagnosis and first lung relapse was 23.8 months (range, 4-80 months). Eleven patients (68.7%) subsequently had a second lung relapse, but only 3 patients had involvement of the ipsilateral lung (mean time interval between first and second pulmonary relapses of 17 months; range, 2-44 months). Five-year overall survival from diagnosis was 56.2%. Seven patients (43.8%) died of disease progression.ConclusionsIn our experience, patients with OS with metachronous metastatic pulmonary disease presenting with a SPN on CT were not found to have additional malignant lesions at the time of thoracotomy. Consideration should be given in this group of selected patients to use a minimally invasive approach to nodule removal with image-guided localization, if needed, rather than open thoracotomy because ipsilateral metastases are not likely to be found.     

Working-memory capacity protects model-based learning from stress

Accounts of decision-making have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental advances suggest that this classic distinction between habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning, called model-free and model-based learning. Popular neurocomputational accounts of reward processing emphasize the involvement of the dopaminergic system in model-free learning and prefrontal, central executive–dependent control systems in model-based choice. Here we hypothesized that the hypothalamic-pituitary-adrenal (HPA) axis stress response—believed to have detrimental effects on prefrontal cortex function—should selectively attenuate model-based contributions to behavior. To test this, we paired an acute stressor with a sequential decision-making task that affords distinguishing the relative contributions of the two learning strategies. We assessed baseline working-memory (WM) capacity and used salivary cortisol levels to measure HPA axis stress response. We found that stress response attenuates the contribution of model-based, but not model-free, contributions to behavior. Moreover, stress-induced behavioral changes were modulated by individual WM capacity, such that low-WM-capacity individuals were more susceptible to detrimental stress effects than high-WM-capacity individuals. These results enrich existing accounts of the interplay between acute stress, working memory, and prefrontal function and suggest that executive function may be protective against the deleterious effects of acute stress.A number of accounts of human and animal decision-making posit the coexistence of separate valuation systems that control choice (1–4), which, broadly speaking, represent automatic or habitual vs. deliberative or controlled modes. The circumstances under which one system may dominate over the other and thereby exert control over behavior has been a question of interest in both neuroscience and psychology, in part because of the implications of such differential control for disorders of compulsion such as drug abuse (5, 6). Acute stress may afford unique leverage in isolating the properties of these systems, because it is believed to prompt a shift from more cognitive or deliberative processes to more automatic processes presumed to be underpinned by phylogenetically older brain structures (7).Accordingly, a spate of recent work suggests that acute stress—indexed by changes in levels of cortisol, a neuroendocrine marker of stress response—engenders reliance on putative habitual and/or automatic processes in human decision-making (8–13), consistent with the assumption that the physiological stress response impairs central executive functions subserving more deliberative choice. However, distinguishing such processes is both experimentally and theoretically fraught, because in dual process theories, which system controls a particular behavior is typically ambiguous, and can only be recognized by characteristics (such as reaction times or conscious access) associated in different theories with either sort of control, and often only in the comparison between different tasks that promote either mode. Here we leverage a more operational version of this distinction based on reinforcement learning (RL) theory (1), which proposes that deliberative and automatic modes of decision-making arise from two distinct computationally precise and neurobiologically grounded learning strategies for evaluating actions from previous experiences. This approach allows us to characterize more precisely and within a single task the impact of physiological stress response upon trial-by-trial learning dynamics of either sort.This RL framework (1) posits that choice behavior arises from a combination of two value learning systems that operate in parallel and whose fundamental difference is whether they rely on an “internal model” of task contingencies for evaluating choices. The model-based system is computationally sophisticated and learns a model of the environment to plan candidate courses of action prospectively. In contrast, the model-free system eschews this model and merely prescribes that previously rewarded actions are repeated, akin to the Law of Effect and to prominent theories in which dopaminergic prediction error responses drive learning about action preferences at target areas such as the striatum (14, 15). Because these hypothesized modes of choice are defined quantitatively as arising from different trial-by-trial learning rules, they make clear and divergent predictions about subjects’ trial-by-trial adjustment of decision preferences in response to feedback, enabling the contributions of both approaches to be dissociated experimentally. In fact, many laboratory choice tasks cannot differentiate between the contributions of the learning strategies, because when each action is paired with a single reward, the two sorts of value learning reduce to the same learning rule. However, the strategies differ appreciably in sequentially structured choice tasks. Recent work, informed by this approach, reveals that under normal circumstances, human learning in such tasks exhibits contributions of both putative systems (16–18). The grounding of these theories in neurocomputational models (19) and work on animal learning (4) also provides a unique perspective on dual process architectures, complementary to a set of views whose roots lie more in human cognitive neuroscience.In line with the considerable computational requirements of model-based evaluation (1, 20), and with evidence that this process relies on the prefrontal cortex (PFC, 4), recent work suggests that the model-based system imposes considerable demands on central executive resources. In particular, depletion of working-memory (WM) resources abolishes model-based contributions to learning behavior but spares model-free contributions (21). At the same time, a different line of work examining central executive function under acute stress reveals how neurophysiological stress response engenders WM capacity impairment (22, 23) and reduction of WM-related activity in the PFC as assessed by neuroimaging (24).On the basis of these two lines of work, an intuitive prediction emerges: stress response—as it deleteriously impacts the PFC-dependent executive resources—should selectively reduce model-based learning, but simultaneously spare model-free learning. Closely supporting this prediction, previous investigations reveal that acute stress engenders reliance on habitual behaviors, at the expense of flexible, goal-directed responding. However, because the two forms of choice were differentiated by posttraining probe trials—testing flexible sensitivity to reinforcer devaluation (25) or to a conjunction of spatial cues (26)—it remains to be investigated how and whether stress affects either of the two sorts of trial-by-trial learning dynamics that have been hypothesized to give rise to the endpoint behaviors probed there (1).A complimentary possibility is suggested by findings that acute stress can increase firing rates of dopaminergic neurons (27) and extracellular dopamine levels in the neural structures putatively underpinning model-free RL (28). We might thus expect, alternately or additionally, that stress would modulate or even strengthen model-free learning. There is indeed recent evidence for effects of stress on probabilistic reward learning (29, 30). However, the task used does not permit differentiating model-based from model-free contributions to learning.Here we elucidate the impact of hypothalamic-pituitary-adrenal (HPA) axis stress response on the expression of model-based and model-free contributions to sequential choice behavior. In the RL task we use (16) model-based and model-free learning strategies—distinguished, respectively, by their utilization and ignorance of the full environment structure—that give rise to distinct and quantifiable behavioral signatures. Our results reveal how the physiological stress response attenuates the influence of model-based (but not model-free) learning, underlining the distinct and separable contributions of these theorized valuation systems.Further, in line with the central-executive–dependent nature of the model-based system, we shed light on how individual differences in WM capacity (often taken as a general measure of executive function and fluid intelligence, 31), modulate the effect of physiological stress response on model-based choice. Specifically, we demonstrate that subjects with more executive resources to spare find themselves less susceptible to the behavioral changes brought about by stress response, elucidating the interplay between acute stress, executive function, and dual-system accounts of decision-making.