Melanoma histopathology reporting: are we complying with the National Minimum Dataset?

BACKGROUND: The Royal College of Pathologists introduced the National Minimum Dataset (NMDS) for the histopathological reporting of cutaneous melanoma in February 2002. AIM: To determine if histological reporting of invasive primary cutaneous melanoma in the West Midlands region of the UK was compliant with the NMDS. METHODS: Reports were identified from March 2002 to March 2003 via the regional Cancer Intelligence Unit, and compared with the NMDS. If all items of the NMDS were adhered to, the report was considered compliant. If not compliant, the report was checked to see if it included selected clinical and staging parameters. RESULTS: 543 cases of invasive cutaneous melanoma were identified, but only 407 reports were analysed. 69/407 (17%) (95% CI 14% to 20%) reports were fully compliant with the NMDS. Of the non-complaint reports, 45/361 (12%) (95% CI 9% to 16%) reported all staging and clinically relevant parameters; 62/361 (17%) (95% CI 59% to 65%) reported all staging parameters. Breslow thickness was reported in all but one of the reports (99.7%), Clark's level was reported in 344/407 (85%), ulceration in 280/407 (69%), and microsatellites in 146/407 (36%). CONCLUSION: There was slow uptake of the NMDS in this region in the year following its introduction. Although major parameters required for staging were more consistently reported, ulceration and microsatellites were less frequently reported.     

3D heart model for computer simulations in cardiac surgery

For a satisfactory computer simulation, a model, which imitates a natural situation, is needed. The Human heart is an irregular 3D object and thus difficult to reproduce. Basic data was taken from Visible Human Dataset (VHD), National Library of Medicine. The heart area was cut out of the original cross-sections and different tissues segmented. All the slices also had to be aligned to assure precise overlapping of the structures. A 3D computer heart model with the resolution of 1mm was designed. The heart model was dedicated to simulations of heat transfer during heart surgery however, it is applicable also to other medical simulations.     

Determination of standard times of nursing activities based on a Nursing Minimum Dataset

Title.  Determination of standard times of nursing activities based on a NursingMinimum Dataset.
Aim.  This paper is a report of a study conducted to determine the standard time per nursing activity and the proportion of nursing time covered by the nursing activities of the Belgian Nursing Minimum Dataset compared to the total time of a nurse shift, and to evaluate the correlation between hospital size and standard times of nursing activities.
Background.  Because of a shrinking workforce and rising workload, nursing managers need tools that help them to allocate their staff to the wards. Such tools should be based on objective time measurements.
Methods.  The study was performed in surgical, internal medicine and elder care wards in an acute hospital care setting. In the first phase, a two-round Delphi-procedure was used to operationalize the definitions of nursing activities. In the second phase, the standard time for each nursing activity was determined, based on data collected over a 6-month period during 2006–2007. A combination of 13,292 work sampling observations by external observers, 3000 recordings of direct time measurement by self-recording and subjective time assessments yielded times that were used to analyse the duration of the nursing activities.
Results.  A standard time for 102 nursing activities was established. The coverage of the Belgian Nursing Minimum Dataset in the surgical, internal medicine and elder care wards was 47·5%, 46·4% and 51·0% respectively. The Belgian Nursing Minimum Dataset was found to cover almost 70% of direct and indirect nursing care.
Conclusion.  Further research is needed to assess the impact on the standard times of nursing activities of inefficient organizational structures and different cultural interpretations of the way an activity is conducted.     

The Cataract National Dataset electronic multi-centre audit of 55,567 operations: risk indicators for monocular visual acuity outcomes

Aims

To report risk factors for visual acuity (VA) improvement and harm following cataract surgery using electronically collected multi-centre data conforming to the Cataract National Dataset (CND).

Methods

Routinely collected anonymised data were remotely extracted from the electronic patient record systems of 12 participating NHS Trusts undertaking cataract surgery. Following data checks and cleaning, analyses were performed to identify risk indicators for: (1) a good acuity outcome (VA 6/12 or better), (2) the pre- to postoperative change in VA, and (3) VA loss (doubling or worse of the visual angle).

Results

In all, 406 surgeons from 12 NHS Trusts submitted data on 55 567 cataract operations. Preoperative VA was known for 55 528 (99.9%) and postoperative VA outcome for 40 758 (73.3%) operations. Important adverse preoperative risk indicators found in at least 2 of the 3 analyses included older age (3), short axial length (3), any ocular comorbidity (3), age-related macular degeneration (2), diabetic retinopathy (3), amblyopia (2), corneal pathology (2), previous vitrectomy (2), and posterior capsule rupture (PCR) during surgery (3). PCR was the only potentially modifiable adverse risk indicator and was powerfully associated with VA loss (OR=5.74).

Conclusion

Routinely collected electronic data conforming to the CND provide sufficient detail for identification and quantification of preoperative risk indicators for VA outcomes of cataract surgery. The majority of risk indicators are intrinsic to the patient or their eye, with a notable exception being PCR during surgery.     

A new dataset evaluation method based on category overlap

The quality of dataset has a profound effect on classification accuracy, and there is a clear need for some method to evaluate this quality. In this paper, we propose a new dataset evaluation method using the R-value measure. This proposed method is based on the ratio of overlapping areas among categories in a dataset. A high R-value for a dataset indicates that the dataset contains wide overlapping areas among its categories, and classification accuracy on the dataset may become low. We can use the R-value measure to understand the characteristics of a dataset, the feature selection process, and the proper design of new classifiers.     

The climate impact on female acute pyelonephritis in Taiwan: A population-based study

Objective

Urinary tract infection (UTI) is the main reason of community-acquired infection which causes large losses in social economy. The individual as well as climate factors make changes on the incidence. Acute pyelonephritis (APN) is one of the most serious UTI in female. The object of our study is to analyze whether climate factors will have effect on the incidence of female APN in Taiwan.

肝连续薄层冠状断面数据获取研究

目的 应用数控冷冻铣削技术获取肝的连续薄层冠状断面数据集.方法 经CT、MRI扫描筛选后,选择无明显病变的成年男性尸体1例,截取其上腹部,按直立位置于包埋容器内,经明胶包埋和深低温冷冻后,在低温冷冻室内用数控铣床从前向后连续铣削,获得肝的连续薄层冠状断面,用数码相机逐层拍摄,获取原始数据.结果 该例上腹部标本冷冻铣削后共获得层厚为0.2mm的肝连续冠状断面图像699幅,断面能够清晰显示肝的形态结构、位置及毗邻关系和肝内管道系统及其分支的走行分布.结论 应用数控冷冻铣削技术获取的肝连续薄层冠状断面数据集精度高,质量优,为基于冠状断面数据集的肝及肝内管道系统的三维重建奠定了基础.