The mean corpuscular volume and hydroxyurea in brazilian patients with sickle cell anemia: a surrogate marker of compliance

The suppression of erythropoiesis by Hydroxyurea (HU) therapy is associated with increase in mean corpuscular volume, in addition to the increase in Hb F. Monitoring the mean corpuscular volume values and the presence of macrocytosis are effective tools of adherence to the treatment with HU in patients with sickle cell anemia. The aim of this study is to monitor the mean corpuscular volume values after starting treatment with HU to determine if macrocytosis can be used as a surrogate marker of compliance with therapy. We conducted a prospective cohort study over one year with measurements of blood counts and mean corpuscular volume after starting therapy with HU in 95 patients with sickle cell anemia who were regularly followed in our ambulatory outpatient unit. In one-year of successful use of HU the mean value of the mean corpuscular volume increased significantly. The Andersen and Gill model demonstrated that the increase of one unit of MCV implies a 5% reduction in the risk of visiting the emergency room. Monitoring mean corpuscular volume values after prescribing HU alerts the provider of noncompliance in order to counsel the patient in question for better adherence to the use of HU that could improve the quality of care and to reduce morbidity and the frequency of acute pain crises and associated healthcare costs.

Joint economic design of X̄ and R control charts for processes subject to two independent assignable causes

A model for the joint economic design of X̄ and R control charts is developed. This model assumes that the process is subject to two assignable causes. One assignable cause shifts the process mean; the other shifts the process variance. The occurrence of the assignable cause of one kind does not block the occurrence of the assignable cause of another kind. Consequently, a second process parameter can go out-of-control after the first process parameter has gone out-of-control. A numerical study of the cost surface to the model considered has revealed that it is convex, at least in the interest region.

Monitoring internal load parameters during simulated and official basketball matches

Moreira, A, McGuigan, MR, Arruda, AFS, Freitas, CG, and Aoki, MS. Monitoring internal load parameters during simulated and official basketball matches. J Strength Cond Res 26(3): 861-866, 2012-The purpose of this study was to compare the internal load responses (session rating of perceived exertion [RPE] and salivary cortisol) between simulated and official matches (SM and OM). Ten professional basketball players participated in 2 OMs and 2 SMs during the competition season. Subjects provided saliva samples 30 minutes before the prematch warm-up (PRE) and 10 minutes after the end of the match. Session RPE (CR-10 scale) was assessed 30 minutes after each match. The results from the 2-way analysis of variance showed significant differences for post-OM salivary cortisol as compared with pre-OM values (p < 0.05). No changes were observed for cortisol during the SM. Before the OM, a significant difference in salivary cortisol was observed as compared with pre-SM values (p < 0.05). Moreover, the OM session RPE was significantly greater than that of SM. There was a significant correlation between session RPE and cortisol changes (r = 0.75). In summary, the results of this study showed a greater magnitude of cortisol and session RPE responses after OM as compared with that after SM confirming the hypothesis that a real competition generates a greater stress response than a simulated condition does. The anticipatory effect was also observed in the OM. In addition, the results indicate that session RPE seems to be a viable tool in monitoring internal loads, and the results are useful in providing a better understanding of internal loads imposed by basketball training and competitions. The precise monitoring of these responses might help the coaches to plan appropriate loads maximizing recovery and performance.

Optimierung der Pharmakotherapie schizophrener Patienten durch objektive Symptomerfassung und Therapeutisches Drug Monitoring

Der Erfolg einer Schizophrenie-Behandlung ist zum größten Teil abhängig vom Ansprechen des Patienten auf seine antipsychotische Medikation. Welches Medikament und welche Dosis bei einem individuellen Patienten wirksam sind, kann derzeit erst nach mehrwöchiger Behandlung beurteilt werden. Ein Grund für variierendes Therapieansprechen sind variable Plasmakonzentrationen der Antipsychotika. Ziel dieser Arbeit war es, zu untersuchen, in wieweit der Therapieerfolg zu einem frühen Zeitpunkt der Behandlung durch objektive Symptomerfassung vorhersagbar ist und welche Faktoren die hohe Variabilität der Antipsychotikaspiegel im Blut beeinflussen. rnEine 18-monatige naturalistische klinische Studie an schizophrenen Patienten wurde durchgeführt, um folgende Fragen zu beantworten: Kann man das Therapieansprechen prädizieren und welche Instrumente sind dafür geeignet? Die Psychopathologie wurde anhand zweier Messskalen (Brief Psychiatric Rating Scale, BPRS und Clinical Global Impressions, CGI) wöchentlich ermittelt, um die Besserung der Krankheitssymptome im Verlauf von 8 Wochen zu bewerten. Therapiebegleitend wurden noch die Serum-Konzentrationen der Antipsychotika gemessen. Objektive Symptomerfassung durch BPRS oder CGI waren als Messinstrumente geeignet, Therapieansprechen vorherzusagen. Bezogen auf den Behandlungsbeginn war eine Verminderung der Symptome hoch prädiktiv für späteres Therapieversagen oder -ansprechen. Eine Verminderung um mehr als 36,5% auf der BPRS Skala in Woche 2 wurde als signifikanter Schwellenwert für Nichtansprechen ermittelt. Patienten, deren Symptombesserung unterhalb des Schwellenwertes lag, hatten eine 11,2-fach höhere Wahrscheinlichkeit, am Ende der Studie nicht auf ihre medikamentöse Therapie anzusprechen als die Patienten, die sich um mindestens 36,5% verbesserten. Andere Faktoren, wie Alter, Geschlecht, Dauer der Erkrankung oder Anzahl der stationären Aufenthalte hatten keinen Einfluss auf die Prädiktion des Therapieansprechens. Therapeutische Antipsychotika-Spiegel übten einen positiven Einfluss auf die Ansprechrate aus. Bei Patienten mit therapeutischen Spiegeln war das Ansprechen rascher und die Ansprechrate größer als unter denjenigen deren Spiegel außerhalb der therapeutisch üblichen Bereiche lag. rnEine wichtige Voraussetzung für den Einsatz von TDM ist das Vorhandensein einer präzisen, reproduzierbaren, zeit- und kostensparenden analytischen Methode zur quantitativen Bestimmung der untersuchten Substanzen. Die Entwicklung und Validierung einer solchen geeigneten Methode wurde für den Nachweis von Haloperidol vorgenommen. Eine HPLC-Methode mit Säulenschaltung erwies sich für TDM geeignet. rnBasierend auf den Ergebnissen der eigenen klinischen Studie zur Response Prädiktion wurde untersucht, welche Faktoren die Variabilität der Pharmakokinetik von Antipsychotika beeinflussen. Die Variabilität der Pharmakokinetik ist ein Grund für fehlendes oder unzureichendes Ansprechen. Es wurde zum einen der Einfluss der galenischen Formulierung auf die Freisetzung und zum anderen der Einfluss von entzündlichen Prozessen auf die Metabolisierung eines Antipsychotikums untersucht. Dazu wurden Patientendaten retrospektiv ausgewertet.rnDie Analyse von 247 Serumspiegeln von Patienten, die mit Paliperidon in OROS®Formulierung, einer neu eingeführten Retardform, behandelt wurden, zeigte, dass die intraindividuelle Variabilität der Talspiegel (Vk) von Paliperidon 35% betrug. Er war damit vergleichbar wie für nicht retardiertes Risperidon 32% (p=n.s.). Die Retardierung hatte demnach keinen Varianz mindernden Effekt auf die Talspiegel des Antipsychotikums. Der Wirkstoff-Konzentrations-Bereich lag bei 21-55 ng/ml und entsprach ebenfalls nahezu dem therapeutischen Bereich von Risperidon (20-60 ng/ml). rnEntzündliche Prozesse können die Metabolisierung von Medikamenten verändern. Dies wurde bisher für Medikamente nachgewiesen, die über CYP1A2 abgebaut werden. Durch die eigene Analyse von 84 Patienten-Serumspiegeln konnte festgestellt werden, dass die Metabolisierung von Quetiapin während eines entzündlichen Prozesses beeinträchtigt war, wahrscheinlich durch Hemmung von CYP3A4. Dies sprach dafür, dass auch Wirkstoffe, die über CYP3A4 abgebaut werden, während eines entzündlichen Prozesses im Körper in ihrer Pharmakokinetik beeinträchtigt sein können. Aus diesem Grund sollte während einer Infektion unter der Therapie mit Quetiapin besonders auf die Nebenwirkungen geachtet werden und der Serumspiegel sollte in dieser Zeit überwacht werden, um den Patienten vor eventuellen Nebenwirkungen oder sogar Intoxikationen zu schützen. rnDie Befunde dieser Arbeit zeigen, dass bei einer Behandlung schizophrener Patienten mit Antipsychotika die Messung der Psychopathologie zur Vorhersage des Therapieansprechens und die Messung der Blutspiegel zur Identifizierung von Faktoren, die die pharmakokinetische Variabilität bedingen, geeignet sind. Objektive Symptomerfassung und Therapeutisches Drug Monitoring sind demnach Instrumente, die für die Steuerung der antipsychotischen Pharmakotherapie genutzt werden sollten.rn

Why evolutionary biologists should get seriously involved in ecological monitoring and applied biodiversity assessment programs

While ecological monitoring and biodiversity assessment programs are widely implemented and relatively well developed to survey and monitor the structure and dynamics of populations and communities in many ecosystems, quantitative assessment and monitoring of genetic and phenotypic diversity that is important to understand evolutionary dynamics is only rarely integrated. As a consequence, monitoring programs often fail to detect changes in these key components of biodiversity until after major loss of diversity has occurred. The extensive efforts in ecological monitoring have generated large data sets of unique value to macro-scale and long-term ecological research, but the insights gained from such data sets could be multiplied by the inclusion of evolutionary biological approaches. We argue that the lack of process-based evolutionary thinking in ecological monitoring means a significant loss of opportunity for research and conservation. Assessment of genetic and phenotypic variation within and between species needs to be fully integrated to safeguard biodiversity and the ecological and evolutionary dynamics in natural ecosystems. We illustrate our case with examples from fishes and conclude with examples of ongoing monitoring programs and provide suggestions on how to improve future quantitative diversity surveys.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Assessing homogeneity in workplace exposure under stationary and non-stationary scenarios

In most epidemiological studies, historical monitoring data are scant and must be pooled to identify occupational groups with homogeneous exposures. Homogeneity of exposure is generally assessed in a group of workers who share a common job title or work in a common area. While published results suggest that the degree of homogeneity varies widely across job groups, less is known whether such variation differs across industrial sectors, classes of contaminants, or in the methods used to group workers. Relying upon a compilation of results presented in the literature, patterns of homogeneity among nearly 500 occupational groups of workers were evaluated on the basis of type of industry and agent. Additionally, effects of the characteristics of the sampling strategy on estimated indicators of homogeneity of exposure were assessed. ^ Exposure profiles for occupational groups of workers have typically been assessed under the assumption of stationarity, i.e., the mean exposure level and variance of the distribution that describes the underlying population of exposures are constant over time. Yet, the literature has shown that occupational exposures have declined in the last decades. This renders traditional methods for the description of exposure profiles inadequate. Thus, work was needed to develop appropriate methods to assess homogeneity for groups of workers whose exposures have changed over time. A study was carried out applying mixed effects models with a term for temporal trend to appropriately describe exposure profiles of groups of workers in the nickel-producing industry over a 20-year period. Using a sub-set of groups of nickel-exposed workers, another study was conducted to develop and apply a framework to evaluate the assumption of stationarity of the variances in the presence of systematic changes in exposure levels over time. ^