基层医务人员隐性缺勤现状及影响因素研究

目的了解基层医务人员隐性缺勤现状及影响因素。方法多阶段整群抽取陕西省汉中市9所乡镇医院及其下属村卫生室580名医务人员,采用斯坦福隐性缺勤量表进行调查。结果基层医务人员隐性缺勤得分中位数为15,高隐性缺勤率为49.4%;Logistic回归分析显示,性别、文化程度、职称、所属机构、是否倒班是隐性缺勤的影响因素(P<0.05,P<0.01)。结论基层医务人员隐性缺勤程度较高,应根据不同医务人员的个人特征开展干预研究,同时合理配置医疗资源,改善基层医疗工作状态,以降低隐性缺勤。     

Unifying account of visual motion and position perception

Despite growing evidence for perceptual interactions between motion and position, no unifying framework exists to account for these two key features of our visual experience. We show that percepts of both object position and motion derive from a common object-tracking system—a system that optimally integrates sensory signals with a realistic model of motion dynamics, effectively inferring their generative causes. The object-tracking model provides an excellent fit to both position and motion judgments in simple stimuli. With no changes in model parameters, the same model also accounts for subjects’ novel illusory percepts in more complex moving stimuli. The resulting framework is characterized by a strong bidirectional coupling between position and motion estimates and provides a rational, unifying account of a number of motion and position phenomena that are currently thought to arise from independent mechanisms. This includes motion-induced shifts in perceived position, perceptual slow-speed biases, slowing of motions shown in visual periphery, and the well-known curveball illusion. These results reveal that motion perception cannot be isolated from position signals. Even in the simplest displays with no changes in object position, our perception is driven by the output of an object-tracking system that rationally infers different generative causes of motion signals. Taken together, we show that object tracking plays a fundamental role in perception of visual motion and position.Research into the basic mechanisms of visual motion processing has largely focused on simple cases in which motion signals are fixed in space and constant over time (e.g., moving patterns presented in static windows) (1). Although this approach has resulted in considerable advances in our understanding of low-level motion mechanisms, it leaves open the question of how the brain integrates changing motion and position signals; when objects move in the world, motion generally co-occurs with changes in object position. The process of generating coherent estimates of object motion and position is known in the engineering and computer vision literature as “tracking” (e.g., as used by the Global Positioning System) (2). Conceptualizing motion and position perception in the broader context of object tracking suggests an alternative conceptual framework—one that we show provides a unifying account for a number of perceptual phenomena.An optimal tracking system would integrate incoming position and motion signals with predictive information from the recent past to continuously update perceptual estimates of both an object’s position and its motion. Were such a system to underlie perception, position and motion should be perceptually coupled in predictable ways. Signatures of such a coupling appear in a number of known phenomena. On one hand, local motion signals can predictively bias position percepts (3–8). On the other hand, we can perceive motion solely from changes in object position (9–12). For example, motion can be perceived in stimuli with no directional motion signal by tracking position changes along a specific direction (10). These phenomena, however, are currently regarded as arising from independent mechanisms (11–14).Given the interdependency of motion and position and the inherent noisiness of sensory signals, it is advantageous for vision to exploit the redundancy between motion and position signals and integrate them into coupled perceptual estimates. This is complicated by the fact that local motion signals can result from a combination of motions (of which object translations are only one) (15, 16). A flying, rotating soccer ball provides a prototypical example of this problem (Fig. 1A). Because the ball rotates as it flies through the air, the local retinal motion signals created by ball texture are sums of two world motions: translation and rotation of the ball. Relating local motion signals to object motion requires the solution of the “source attribution” problem (17, 18)—determining what part of a local retinal motion pattern is due to object translation and what part is due to object-relative motion of the texture pattern. To solve this attribution problem, the brain can exploit the redundant information provided by the changing stimulus position. Moreover, integrating motion and position information over time with an internal model of motion dynamics can mitigate both the uncertainty created by ubiquitous sensory noise (19) and that created by the motion source attribution problem. Although object-relative pattern motion is not a property of all moving objects, understanding how pattern motion interacts with object motion and position can help elucidate how the brain integrates motion and position signals into coherent perceptual estimates—a problem associated with all moving objects.Open in a separate windowFig. 1.Schematic illustration of the object-tracking model and its behavior. (A) An example of an object with both object boundary motion and pattern motion. (B) A generative model of the Bayesian observer. White nodes indicate hidden variables and gray nodes indicate observable variables that are noisy measurements of the connected hidden variables. Arrows indicate causal links. (C) Model behavior for a typical MIPS stimulus containing a moving pattern within a static envelope. The steady-state estimates of the three object states (position, object velocity, and pattern velocity) are plotted for different positional uncertainties. At low positional uncertainty, most of the retinal texture motion is correctly attributed to the pattern motion. Consequently, illusory object motion and MIPS are negligible. At high positional uncertainty, much of the texture motion is attributed to object motion (reflecting a prior that object motion is more likely than pattern motion). This results in relatively low estimated pattern velocity and large MIPS.Here, we propose and test a computational framework in which motion and position perception derive from a common mechanism that integrates sensory signals over time to track objects and infer their generative causes. The consequence of this process is a strong, bidirectional coupling between motion and position perception that provides a unifying account for a range of perceptual phenomena. These include motion-induced shifts in perceived position (3–6), perceptual speed biases (20), slowing of motions shown in visual periphery (21, 22), and the curveball illusion (16). The presented model also makes novel predictions about interactions between position and motion perception—predictions confirmed here. Importantly, we do not fit the model to each experiment, but fit the parameters to data from experiment 1 and show that the resulting model accurately predicts subjects’ performance in qualitatively different and more complex tasks (experiments 2 and 3).     

The National Trend in Arthroplasty Surgery Location and the Economic Impact on Surgeons,Hospitals and ASCs

BackgroundWe sought to understand the magnitude of the shift in care settings (hospital inpatient, hospital outpatient, or ambulatory surgery center) for primary total joint arthroplasty (TJA) and its economic impact on surgeons and hospitals.MethodsWe measured the shift in care settings for primary TJAs using national 100% sample Medicare fee-for-service (FFS) claims data from January 2017 through March 2021. We also measured the percent of case being discharged the same day over time. We calculated the national average hospital payment rate by setting and the weighted average hospital payment rates based on the mix of inpatient and outpatient cases over time. We compared average facility and physician payment rate changes over time across common types of surgeries.ResultsBy the first quarter of 2021, 29% of Medicare FFS primary TJAs were performed hospital inpatient (down from 100% in 2017), 64% were performed hospital outpatient, and about 7% in an ambulatory surgery center. The percent of hospital-based primary TJAs that were discharged the same day increased from less than 2% in the first quarter of 2018 to over 18% in the first quarter of 2021. Medicare increased its payment rates for both inpatient and outpatient TJAs, which offset the impact of TJAs shifting from being performed inpatient to outpatient. The average Medicare payment rates for TJAs declined by more than they did for most other major procedures.ConclusionThere was a significant shift in care setting from hospital inpatient to hospital outpatient for Medicare primary TJAs. This shift led to lower average TJA payment rates to hospitals; however, the impact was attenuated due to the increasing Medicare reimbursement rates in each setting, particularly for outpatient cases.     

Enzymes with lid-gated active sites must operate by an induced fit mechanism instead of conformational selection

The induced fit and conformational selection/population shift models are two extreme cases of a continuum aimed at understanding the mechanism by which the final key-lock or active enzyme conformation is achieved upon formation of the correctly ligated enzyme. Structures of complexes representing the Michaelis and enolate intermediate complexes of the reaction catalyzed by phosphoenolpyruvate carboxykinase provide direct structural evidence for the encounter complex that is intrinsic to the induced fit model and not required by the conformational selection model. In addition, the structural data demonstrate that the conformational selection model is not sufficient to explain the correlation between dynamics and catalysis in phosphoenolpyruvate carboxykinase and other enzymes in which the transition between the uninduced and the induced conformations occludes the active site from the solvent. The structural data are consistent with a model in that the energy input from substrate association results in changes in the free energy landscape for the protein, allowing for structural transitions along an induced fit pathway.     

实施整体护理中改进护士排班的做法

目的　通过改进护士排班方法 ,充分挖掘现有护理人力资源的潜力 ,使整体护理各项程序得以落实。方法　采用护理人员相对固定的排班方式。结果　保证了责任护士护理工作的连续性、系统性 ,为责任护士给患者提供良好的护理服务奠定了基础。同时 ,职责明确 ,加强了护士的责任心 ,增强了护士竞争意识和主动服务意识。结论　护士乐于接受 ,护理服务的满意度提高 ,相对缓解了护理人员不足的问题     

Improved encoding strategy for CPMG-based Bloch-Siegert B(1)(+) mapping

Bloch-Siegert (BS) based B(1)(+) mapping methods use off-resonant pulses to encode quantitative B(1)(+) information into the signal phase. It was recently shown that the principle behind BS-based B(1)(+) mapping can be expanded from spin echo (BS-SE) and gradient-echo (BS-FLASH) based BS B(1)(+) mapping to methods such as Carr, Purcell, Meiboom, Gill (CPMG)-based turbo-spin echo (BS-CPMG-TSE) and multi-spin echo (BS-CPMG-MSE) imaging. If CPMG conditions are preserved, BS-CPMG-TSE allows fast acquisition of the B(1)(+) information and BS-CPMG-MSE enables simultaneous mapping of B(1)(+), M(0), and T(2). To date, however, two separate MRI experiments must be performed to enable the calculation of B(1)(+) maps. This study investigated a modified encoding strategy for CPMG BS-based methods to overcome this limitation. By applying a "bipolar" off-resonant BS pulse before the refocusing pulse train, the needed phase information was able to be encoded into different echo images of one echo train. Thus, this technique allowed simultaneous B(1)(+) and T(2) mapping in a single BS-CPMG-MSE experiment. To allow single-shot B(1)(+) mapping, this method was also applied to turbo-spin echo imaging. Furthermore, the presented modification intrinsically minimizes phase-based image artifacts in BS-CPMG-TSE experiments.     

Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI

We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three-dimensional echo-planar imaging volumetric navigators are embedded in a long three-dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subject's location in the scanner at a cost of less than 500 ms, ~ 1% change in contrast, and ~3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion-corrected sequence with no extra time required. We also demonstrate motion-driven selective reacquisition of k-space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high-throughput environments.