64排螺旋CT与选择性冠状动脉造影评价急性冠状动脉综合征患者易损斑块形态、成分及大小的价值对比研究

目的 探讨64排螺旋CT评价急性冠状动脉综合征(ACS)患者易损斑块形态、成分及大小的价值.方法 65例冠心病患者(其中ACS组32例,稳定性心绞痛组33例)行64排螺旋CT冠状动脉成像及选择性冠状动脉造影.对ACS组及稳定性心绞痛组的管腔狭窄程度、斑块最低密度值、钙化形态(点状钙化或大钙化)及斑块大小进行评价.计算64排MDCT对ACS易损斑块诊断的敏感性、特异性、阳性预测值、阴性预测值.采用SPSS 13.0统计软件进行ACS组与SAP两组之间特征的差异描述和分析,定性变量用卡方检验,定量变量采用两独立样本t检验,P ＜0.05为差异有显著性.结果 两组之间管腔的狭窄程度无差别.ACS组斑块的最低密度CT值[(39±78)HU]低于稳定性心绞痛组斑块的最低密度CT值[(103±114)HU],两组比较差异有统计学意义(P＜0.05,t=0.315).斑块的总体积两组比较无差异,软斑块体积比例＞40％的例数,ACS组较稳定性心绞痛组大,差异不具有统计学意义(P＞0.05).点状钙化在ACS组更频繁而稳定性心绞痛组大钙化更为常见,两组比较差异均有统计学意义(P＜0.01,t=0.221).斑块最小密度CT值＜35 HU的比例在ACS组较SAP组更频繁(P＜0.01,t=0.161).同时存在点状钙化及斑块最小CT值＜35 HU这两个特征对ACS诊断显示很高的阳性预测值,而缺少这两个特征阴性预测值很高.结论 ACS易损斑块CT特征包括:斑块低密度、点状钙化、软斑块体积所占比例较大的特点.冠状动脉粥样斑块同时具有CT值＜35 HU、点状钙化特征高度提示斑块的易损性.     

Use-dependent control of presynaptic calcium signalling at central synapses

Voltage-gated Ca(2+) channels activated by action potentials evoke Ca(2+) entry into presynaptic terminals thus briefly distorting the resting Ca(2+) concentration. When this happens, a number of processes are initiated to re-establish the Ca(2+) equilibrium. During the post-spike period, the increased Ca(2+) concentration could enhance the presynaptic Ca(2+) signalling. Some of the mechanisms contributing to presynaptic Ca(2+) dynamics involve endogenous Ca(2+) buffers, Ca(2+) stores, mitochondria, the sodium-calcium exchanger, extraterminal Ca(2+) depletion and presynaptic receptors. Additionally, subthreshold presynaptic depolarization has been proposed to have an effect on release of neurotransmitters through a mechanism involving changes in resting Ca(2+). Direct evidence for the role of any of these participants in shaping the presynaptic Ca(2+) dynamics comes from direct recordings of giant presynaptic terminals and from fluorescent Ca(2+) imaging of axonal boutons. Here, some of this evidence is presented and discussed.     

Developmental changes in odor-evoked activity in rat piriform cortex

In adult rats, odor-evoked Fos protein expression is found in rostrocaudally-oriented bands of cells in anterior piriform cortex (APC), likely indicating functionally distinct subregions, while activated cells in posterior piriform cortex (PPC) lack apparent spatial organization. To determine whether these patterns are present during early postnatal life, and whether they change during development, Fos expression was assessed following acute exposure to single aliphatic acid odors in developing rats beginning at postnatal day 3 (P3). In the olfactory bulb, Fos-immunoreactive cells were present in the granule cell, mitral cell and glomerular layers at the earliest ages examined. Cells immunopositive for Fos were clustered in areas previously reported as active in response to these odors. In piriform cortex, activation in layers II/III shared some features with that seen in the adult; in APC, rostro-caudally oriented bands of Fos-positive cells alternated with bands relatively free of label, while labeled cells were found dispersed throughout PPC. However, in P3-P7 animals, Fos-positive cells in APC were found in a central rostro-caudally oriented band that was flanked by two bands relatively free of Fos-positive cells. This contrasted with the adult pattern, a central cell-poor band flanked by cell-rich bands, which was observed beginning at P10. These results suggest that subregions of APC visualized by odor-evoked Fos expression are active and functionally distinct shortly after birth. Changes in activity within these subregions during early postnatal development coincide with a shift toward adult-like olfactory learning behavior in the second postnatal week, and may play a role in this behavioral shift.     

New Evaluation and Management Code Level Selection Trends in Hip and Knee Osteoarthritis Patients

BackgroundOn January 1, 2021, the American Medical Association implemented changes regarding the outpatient Evaluation and Management (E/M) criteria dictating Current Procedural Terminology code level selection to help diminish administrative burden and emphasize medical decision-making as the primary determinant in E/M level of service (EML). The goal of this study was to describe EML coding trends in outpatient visits for hip and knee osteoarthritis after the 2021 Centers for Medicare and Medicaid Services changes to the E/M system.MethodsAll outpatient visits for primary hip and knee osteoarthritis within the divisions of Joint Replacement, Operative Sports Medicine, and Nonoperative Sports Medicine at a single orthopaedic practice were retrospectively analyzed during 2 separate 10-month timeframes in 2019 and 2021. The primary endpoint was the visit EML (1 through 5) based on Current Procedural Terminology E/M codes.ResultsIn 2019, 7.8% of all visits were billed as level 2, 85.8% of all visits were billed as level 3, and 6.3% of all visits were billed as level 4. In 2021, 2.8% of visits were billed as level 2, 54% of visits were billed as level 3, and 41.3% of visits were billed as level 4. Level 1 and Level 5 visits did not exceed 2% in either year. Across all 3 divisions, level 2 and 3 visits decreased significantly (P < .05), while level 4 visits increased significantly (P < .05).ConclusionSince the E/M coding criteria overhaul in 2021, there has been a significant trend towards higher level of service code selection across multiple divisions in our orthopaedic practice.     

Reimbursement for Hip Fractures: The Impact of Varied Current Procedural Terminology Coding Using Relative Value Units

BackgroundMany orthopedic practices routinely code hip fracture hemiarthroplasty as Current Procedural Terminology (CPT) 27125 even though 27236 is the correct CPT code. Our objective is to determine the financial impact this simple mistake has on surgeon reimbursement.MethodsOur data comprised cases assigned International Classification of Diseases, Tenth Revision code S72.001A through S72.035A and CPT code 27125 or 27236 within the American College of Surgeons National Surgical Quality Improvement Program 2016-2017 database. Relative value units (RVUs) per CPT code and the Centers for Medicare and Medicaid Services reported that RVU conversion factor of $36.0896 per 1 RVU was used to calculate reimbursement per case. The dollar difference and percent difference per case was then calculated between cases assigned CPT code 27125 and those assigned 27236.ResultsOur total sample consisted of 12,287 National Surgical Quality Improvement Program cases. Of those, 4185 (34%) were cases of a hip fracture treated with hemiarthroplasty that were incorrectly coded as CPT code 27125. That error in coding results in a decrease in reimbursement of $35.01 per case, a 5.51% difference.ConclusionSince the current healthcare reimbursement model relies solely on CPT codes to determine RVUs, it is imperative that orthopedic surgeons understand the financial impact of incorrect coding. Although correct coding of hemiarthroplasty procedures for hip fractures is an easy task to fix in the future, we hope that through this study a greater emphasis is placed on coding in orthopedic surgery.     

中文版共情沟通编码系统在新生儿监护室护患沟通中的应用

目的汉化共情沟通编码系统并应用于新生儿监护室护患沟通,了解护患双方共情沟通行为模式。方法收集新生儿监护室护患沟通的录音,运用汉化的共情沟通编码系统识别和归类患儿父母主动提供的共情机会及分析护理人员对此机会的反应模式。结果共收集32名护理人员与78名患儿父母的对话,识别91个共情机会-共情反应的对话组合。多数患儿父母倾向于直接表达"挑战"(38.5%)和"情绪"(29.7%)类型的共情机会,其次是"间接"(20.9%)和"进展"(6.6%),极少为"护士引发"(4.4%)。护理人员多采取"隐性识别"(27.5%)、"识别但未追问"(23.1%)和"拒绝"(16.5%)的共情回应策略,其中"情绪"型共情机会相对于其他类型能够得到更高层级的共情反应。结论中文版共情沟通编码系统可用于探索护患双方的共情沟通行为模式,为共情培训提供参考。     

A microstructure estimation Transformer inspired by sparse representation for diffusion MRI

Diffusion magnetic resonance imaging (dMRI) is an important tool in characterizing tissue microstructure based on biophysical models, which are typically multi-compartmental models with mathematically complex and highly non-linear forms. Resolving microstructures from these models with conventional optimization techniques is prone to estimation errors and requires dense sampling in the q-space with a long scan time. Deep learning based approaches have been proposed to overcome these limitations. Motivated by the superior performance of the Transformer in feature extraction than the convolutional structure, in this work, we present a learning-based framework based on Transformer, namely, a Microstructure Estimation Transformer with Sparse Coding (METSC) for dMRI-based microstructural parameter estimation. To take advantage of the Transformer while addressing its limitation in large training data requirement, we explicitly introduce an inductive bias—model bias into the Transformer using a sparse coding technique to facilitate the training process. Thus, the METSC is composed with three stages, an embedding stage, a sparse representation stage, and a mapping stage. The embedding stage is a Transformer-based structure that encodes the signal in a high-level space to ensure the core voxel of a patch is represented effectively. In the sparse representation stage, a dictionary is constructed by solving a sparse reconstruction problem that unfolds the Iterative Hard Thresholding (IHT) process. The mapping stage is essentially a decoder that computes the microstructural parameters from the output of the second stage, based on the weighted sum of normalized dictionary coefficients where the weights are also learned. We tested our framework on two dMRI models with downsampled q-space data, including the intravoxel incoherent motion (IVIM) model and the neurite orientation dispersion and density imaging (NODDI) model. The proposed method achieved up to 11.25 folds of acceleration while retaining high fitting accuracy for NODDI fitting, reducing the mean squared error (MSE) up to 70% compared with the previous q-space learning approach. METSC outperformed the other state-of-the-art learning-based methods, including the model-free and model-based methods. The network also showed robustness against noise and generalizability across different datasets. The superior performance of METSC indicates its potential to improve dMRI acquisition and model fitting in clinical applications.     

Towards computer-assisted coding: A case study of ‘charge by documentation’ software at an endoscopy clinic

ObjectivesAn imminent transition to the ICD-10 diagnostic code set has increased interest in automating portions of the reimbursement process for clinical procedures. In this paper, we compare two distinct sets of billing codes generated at an endoscopy clinic using a traditional manual methods and computer-assisted coding using a ‘charge by documentation’ approach.MethodsThis is a retrospective, cross sectional research design analyzing data collected from all patients treated at one outpatient endoscopy clinic from July 2010 through June 2011. The collected data were the medical record number, data of service, diagnosis, procedure, CPT codes, ICD-9-CM codes, and CPT modifiers. The paired data were categorized as either an exact match or discrepant.Results98% of the 2923 procedures were either colonoscopies or upper GI endoscopies, which have predictable workflow deviations that reliably map to changes in procedural and diagnostic codes. The codes from the two methods were an exact match for 31% of the cases. The automated approach generated 1–8 additional codes for 62% of the cases, and the manual approach generated codes without accompanying supporting documentation in the progress note for 24% of the cases.ConclusionsWe conclude that the automated approach was superior to the manual approach. We recommend the ‘charge by documentation’ approach for settings where the workflow is relatively predictable, including pre-identified frequently occurring branches to the workflow that affect the selection of procedural and diagnostic codes.