Managers' perspective on continuous health education in a region of São Paulo State

OBJECTIVEAnalysing the concepts of Continuous Health Education - CHE (EPS - in Portuguese), operated by municipal managers and translated into official documents.METHODQualitative research with the use of official documents and semi-structured interviews with the Municipal Health Secretaries or Coordinators of Primary Health Care in the Northeast Region of São Paulo State, and thematic analysis of empirical material.RESULTSResults indicate difficulties in the municipalities problematizing their management practices, services and health care; EPS tools presented are insufficient and unsatisfactory for amending the array of problems raised and are still far from the routine of Primary Care services.CONCLUSIONDespite efforts to implement EPS actions for the strengthening of primary care, the process appears to be incipient.

Development of nursing management competencies: guidelines for continuous education services

Abstract OBJECTIVE Developing continuing education guidelines for the development of nursing management competencies along with the members of the Center of Nursing Continuing Education of Parana. METHOD A qualitative research outlined by the action research method, with a sample consisting of 16 nurses. Data collection was carried out in three stages and data were analyzed according to the thematic analysis technique. RESULTS It was possible to discuss the demands and difficulties in developing nursing management competencies in hospital organizations and to collectively design a guideline. CONCLUSION The action research contributed to the production of knowledge, confirming the need and the importance of changing the educational processes and evaluations, based on methodologies and instruments for professional development in accordance with human resource policies and contemporary organizational policies.

Continuous electroencephalography in the medical intensive care unit.

OBJECTIVES: To examine predictors and the prognostic value of electrographic seizures (ESZs) and periodic epileptiform discharges (PEDs) in medical intensive care unit (MICU) patients without a primary acute neurologic condition. DESIGN: Retrospective study. SETTING: MICU in a university hospital. PATIENTS: A total of 201 consecutive patients admitted to the MICU between July 2004 and January 2007 without known acute neurologic injury and who underwent continuous electroencephalography monitoring (cEEG) for investigation of possible seizures or changes in mental status. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: Median time from intensive care unit (ICU) admission to cEEG was 1 day (interquartile range 1-4). The majority of patients (60%) had sepsis as the primary admission diagnosis and 48% were comatose at the time of cEEG. Ten percent (n = 21) of patients had ESZs, 17% (n = 34) had PEDs, 5% (n = 10) had both, and 22% (n = 45) had either ESZs or PEDs. Seizures during cEEG were purely electrographic (no detectable clinical correlate) in the majority (67%) of patients. Patients with sepsis had a higher rate of ESZs or PEDs than those without sepsis (32% vs. 9%, p < 0.001). On multivariable analysis, sepsis at ICU admission was the only significant predictor of ESZs or PEDs (odds ratio 4.6, 95% confidence interval 1.9-12.7, p = 0.002). After controlling for age, coma, and organ dysfunction, the presence of ESZs or PEDs was associated with death or severe disability at hospital discharge (89% with ESZs or PEDs, vs. 39% if not; odds ratio 19.1, 95% confidence interval 6.3-74.6, p < 0.001). CONCLUSION: In this retrospective study of MICU patients monitored with cEEG, ESZs and PEDs were frequent, predominantly in patients with sepsis. Seizures were mainly nonconvulsive. Both seizures and periodic discharges were associated with poor outcome. Prospective studies are warranted to determine more precisely the frequency and clinical impact of nonconvulsive seizures and periodic discharges, particularly in septic patients.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Nocturnal hypoglycaemias in type 1 diabetic patients: what can we learn with continuous glucose monitoring?

AIM: In type 1 diabetic patients (T1DM), nocturnal hypoglycaemias (NH) are a serious complication of T1DM treatment; self-monitoring of blood glucose (SMBG) is recommended to detect them. However, the majority of NH remains undetected on an occasional SMBG done during the night. An alternative strategy is the Continuous glucose monitoring (CGMS), which retrospectively shows the glycaemic profile. The aims of this retrospective study were to evaluate the true incidence of NH in T1DM, the best SMBG time to predict NH, the relationship between morning hyperglycaemia and NH (Somogyi phenomenon) and the utility of CGMS to reduce NH. METHODS: Eighty-eight T1DM who underwent a CGMS exam were included. Indications for CGMS evaluation, hypoglycaemias and correlation with morning hyperglycaemias were recorded. The efficiency of CGMS to reduce the suspected NH was evaluated after 6-9 months. RESULTS: The prevalence of NH was 67% (32% of them unsuspected). A measured hypoglycaemia at bedtime (22-24 h) had a sensitivity of 37% to detect NH (OR=2.37, P=0.001), while a single measure < or =4 mmol/l at 3-hour had a sensitivity of 43% (OR=4.60, P<0.001). NH were not associated with morning hyperglycaemias but with morning hypoglycaemias (OR=3.95, P<0.001). After 6-9 months, suspicions of NH decreased from 60 to 14% (P<0.001). CONCLUSION: NH were highly prevalent and often undetected. SMBG at bedtime, which detected hypoglycaemia had sensitivity almost equal to that of 3-hour and should be preferred because it is easier to perform. Somogyi phenomenon was not observed. CGMS is useful to reduce the risk of NH in 75% of patients.

Parallel scheduling of multiclass M/M/m queues: Approximate and heavy-traffic optimization of achievable performance

We address the problem of scheduling a multiclass $M/M/m$ queue with Bernoulli feedback on $m$ parallel servers to minimize time-average linear holding costs. We analyze the performance of a heuristic priority-index rule, which extends Klimov's optimal solution to the single-server case: servers select preemptively customers with larger Klimov indices. We present closed-form suboptimality bounds (approximate optimality) for Klimov's rule, which imply that its suboptimality gap is uniformly bounded above with respect to (i) external arrival rates, as long as they stay within system capacity;and (ii) the number of servers. It follows that its relativesuboptimality gap vanishes in a heavy-traffic limit, as external arrival rates approach system capacity (heavy-traffic optimality). We obtain simpler expressions for the special no-feedback case, where the heuristic reduces to the classical $c \mu$ rule. Our analysis is based on comparing the expected cost of Klimov's ruleto the value of a strong linear programming (LP) relaxation of the system's region of achievable performance of mean queue lengths. In order to obtain this relaxation, we derive and exploit a new set ofwork decomposition laws for the parallel-server system. We further report on the results of a computational study on the quality of the $c \mu$ rule for parallel scheduling.

Single-metal deposition: optimization of this fingermark enhancement technique

Following the introduction of single-metal deposition (SMD), a simplified fingermark detection technique based on multimetal deposition, optimization studies were conducted. The different parameters of the original formula were tested and the results were evaluated based on the contrast and overall aspect of the enhanced fingermarks. The new formula for SMD was found based on the most optimized parameters. Interestingly, it was found that important variations from the base parameters did not significantly affect the outcome of the enhancement, thus demonstrating that SMD is a very robust technique. Finally, a comparison of the optimized SMD with multi-metal deposition (MMD) was carried out on different surfaces. It was demonstrated that SMD produces comparable results to MMD, thus validating the technique.

Beyond intracranial pressure: optimization of cerebral blood flow, oxygen, and substrate delivery after traumatic brain injury.

Monitoring and management of intracranial pressure (ICP) and cerebral perfusion pressure (CPP) is a standard of care after traumatic brain injury (TBI). However, the pathophysiology of so-called secondary brain injury, i.e., the cascade of potentially deleterious events that occur in the early phase following initial cerebral insult-after TBI, is complex, involving a subtle interplay between cerebral blood flow (CBF), oxygen delivery and utilization, and supply of main cerebral energy substrates (glucose) to the injured brain. Regulation of this interplay depends on the type of injury and may vary individually and over time. In this setting, patient management can be a challenging task, where standard ICP/CPP monitoring may become insufficient to prevent secondary brain injury. Growing clinical evidence demonstrates that so-called multimodal brain monitoring, including brain tissue oxygen (PbtO2), cerebral microdialysis and transcranial Doppler among others, might help to optimize CBF and the delivery of oxygen/energy substrate at the bedside, thereby improving the management of secondary brain injury. Looking beyond ICP and CPP, and applying a multimodal therapeutic approach for the optimization of CBF, oxygen delivery, and brain energy supply may eventually improve overall care of patients with head injury. This review summarizes some of the important pathophysiological determinants of secondary cerebral damage after TBI and discusses novel approaches to optimize CBF and provide adequate oxygen and energy supply to the injured brain using multimodal brain monitoring.

Solving higher-dimensional continuous time stochastic control problems by value function regression

The paper develops a method to solve higher-dimensional stochasticcontrol problems in continuous time. A finite difference typeapproximation scheme is used on a coarse grid of low discrepancypoints, while the value function at intermediate points is obtainedby regression. The stability properties of the method are discussed,and applications are given to test problems of up to 10 dimensions.Accurate solutions to these problems can be obtained on a personalcomputer.

Optimization of multiclass queueing networks with changeover times via the achievable region approach: Part I, the single-station case

We address the performance optimization problem in a single-stationmulticlass queueing network with changeover times by means of theachievable region approach. This approach seeks to obtainperformance bounds and scheduling policies from the solution of amathematical program over a relaxation of the system's performanceregion. Relaxed formulations (including linear, convex, nonconvexand positive semidefinite constraints) of this region are developedby formulating equilibrium relations satisfied by the system, withthe help of Palm calculus. Our contributions include: (1) newconstraints formulating equilibrium relations on server dynamics;(2) a flow conservation interpretation of the constraintspreviously derived by the potential function method; (3) newpositive semidefinite constraints; (4) new work decomposition lawsfor single-station multiclass queueing networks, which yield newconvex constraints; (5) a unified buffer occupancy method ofperformance analysis obtained from the constraints; (6) heuristicscheduling policies from the solution of the relaxations.

Optimization of multiclass queueing networks with changeover times via the achievable region method: Part II, the multi-station case

We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.

Diversity of Calliphoridae and Sarcophagidae (Diptera, Oestroidea) in continuous forest and gaps at different stages of regeneration in the Urucu oilfield in western Brazilian Amazonia

Diversity of Calliphoridae and Sarcophagidae (Diptera, Oestroidea) in continuous forest and gaps at different stages of regeneration in the Urucu oilfield in western Brazilian Amazonia. The diversity of Calliphoridae and Sarcophagidae in continuous forest and gaps at different stages of regeneration was studied in the Urucu river basin, in Coari, state of Amazonas, Brazil. The flies were collected at 16 sampling points, 12 in gaps at different stages of regeneration (early _ C1, mid- C2 and late successional _ C3) and four in continuous forest _ MT. The diversity of blowflies was similar in the two less regenerated habitats (C1 and C2), and lower than that in the late successional (C3) and continuous forests (MT). By contrast, the diversity of flesh flies was much higher in all three types of gaps (C1, C2 and C3) in comparison with continuous forest (MT). Ordination (NMDS) and similarity (ANOSIM) analyses revealed that the blowflies communities were grouped by habitat type, which affected species composition more than diversity. Analysis of the flesh flies revealed two main groupings, gaps (C1, C2 and C3) and continuous forest (MT), with no evidence of any influence of successional stage on the diversity of the community.

Variability of resting energy expenditure in healthy volunteers during fasting and continuous enteral feeding.

The magnitude of variability in resting energy expenditure (REE) during the day was assessed in nine healthy young subjects under two nutritional conditions: 1) mixed nutrient (53% carbohydrate, 30% fat, 17% protein) enteral feeding at an energy level corresponding to 1.44 REE; and 2) enteral fasting, with only water allowed. In each subject, six 30-min measurements of REE were performed using indirect calorimetry (hood system) at 90-min intervals from 9 AM to 5 PM. The mean REE and respiratory quotient were significantly (p less than .01) greater during feeding than during fasting (1.08 +/- 0.07 [SEM] vs. 1.00 +/- 0.06 kcal/min and 0.874 +/- 0.007 vs. 0.829 +/- 0.008 kcal/min, respectively). Mean postprandial thermogenesis was 4.9 +/- 0.4% of metabolizable energy administered. The intraindividual variability of REE throughout the day, expressed as the coefficient of variation, ranged from 0.7% to 2.0% in the fasting condition and from 1.2% to 4.1% in the feeding condition. There was no significant difference between the REE measured in the morning and that determined in the afternoon.

Ignoring information in binary choice with continuous variables: When is less 'more'?

When can a single variable be more accurate in binary choice than multiple sources of information? We derive analytically the probability that a single variable (SV) will correctly predict one of two choices when both criterion and predictor are continuous variables. We further provide analogous derivations for multiple regression (MR) and equal weighting (EW) and specify the conditions under which the models differ in expected predictive ability. Key factors include variability in cue validities, intercorrelation between predictors, and the ratio of predictors to observations in MR. Theory and simulations are used to illustrate the differential effects of these factors. Results directly address why and when one-reason decision making can be more effective than analyses that use more information. We thus provide analytical backing to intriguing empirical results that, to date, have lacked theoretical justification. There are predictable conditions for which one should expect less to be more.

Continuous arterial spin labeling of mouse cerebral blood flow using an actively-detuned two-coil system at 9.4T.

Among numerous magnetic resonance imaging (MRI) techniques, perfusion MRI provides insight into the passage of blood through the brain's vascular network non-invasively. Studying disease models and transgenic mice would intrinsically help understanding the underlying brain functions, cerebrovascular disease and brain disorders. This study evaluates the feasibility of performing continuous arterial spin labeling (CASL) on all cranial arteries for mapping murine cerebral blood flow at 9.4 T. We showed that with an active-detuned two-coil system, a labeling efficiency of 0.82 ± 0.03 was achieved with minimal magnetization transfer residuals in brain. The resulting cerebral blood flow of healthy mouse was 99 ± 26 mL/100g/min, in excellent agreement with other techniques. In conclusion, high magnetic fields deliver high sensitivity and allowing not only CASL but also other MR techniques, i.e. (1)H MRS and diffusion MRI etc, in studying murine brains.