Machine learning based assessment of preclinical health questionnaires.

BACKGROUND: Within modern health systems, the possibility of accessing a large amount and a variety of data related to patients' health has increased significantly over the years. The source of this data could be mobile and wearable electronic systems used in everyday life, and specialized medical devices. In this study we aim to investigate the use of modern Machine Learning (ML) techniques for preclinical health assessment based on data collected from questionnaires filled out by patients. METHOD: To identify the health conditions of pregnant women, we developed a questionnaire that was distributed in three maternity hospitals in the Mureș County, Romania. In this work we proposed and developed an ML model for pattern detection in common risk assessment based on data extracted from questionnaires. RESULTS: Out of the 1278 women who answered the questionnaire, 381 smoked before pregnancy and only 216 quit smoking during the period in which they became pregnant. The performance of the model indicates the feasibility of the solution, with an accuracy of 98 % confirmed for the considered case study. CONCLUSION: The proposed solution offers a simple and efficient way to digitize questionnaire data and to analyze the data through a reduced computational effort, both in terms of memory and computing power used.

An Investigation for Future Practice of Elective Hip and Knee Arthroplasties during COVID-19 in Romania.

Background and Objectives: Elective arthroplasty in Romania has been severely affected by the COVID-19 pandemic, and its effects are not quantified so far. The aim of this paper is to determine the impact of COVID-19 on arthroplasty interventions and how they varied in Romania. Materials and Methods: We performed a national retrospective analysis of patients who underwent primary and revision elective hip and knee interventions at the 120 orthopedic-traumatology hospitals in Romania that are registered in the National Endoprosthesis Registry from 1 January 2019 to 1 September 2022. First, we examined the monthly trend in the number of surgeries for seven categories of arthroplasties. We calculated the percentage change in the average number of cases per month and compared them with other types of interventions. We then examined the percentage change in the average monthly number of arthroplasty cases, relative to the number of COVID-19 cases reported nationwide, the influence of the pandemic on length of hospital stay, and the percentage of patients discharged at home who no longer follow recovery protocols. Finally, we calculated the impact of the pandemic on hospital revenues. Results: There was an abrupt decrease in the volume of primary interventions in hip and knee patients by up to 69.14% with a low degree of patient care, while the average duration of scheduled hospitalizations increased. We found a 1-2-day decrease in length of hospital stays for explored arthroplasties. We saw an increasing trend of home discharge, which was higher for primary interventions compared to revision interventions. The total hospital revenues were 50.96% lower in 2020 compared to 2019, and are currently increasing, with the 2022 estimate being 81.46%. Conclusions: The conclusion of this study is that the COVID-19 pandemic severely affected the volume of arthroplasty of the 120 hospitals in Romania, which also had unfavorable financial implications. We proposed the development of new procedures and alternative clinical solutions, as well as personalized home recovery programs, to be activated if necessary, for possible future outbreaks.

Energy Contour Forecasting Optimization with Smart Metering in Distribution Power Networks.

Smart metering systems development and implementation in power distribution networks can be seen as an important factor that led to a major technological upgrade and one of the first steps in the transition to smart grids. Besides their main function of power consumption metering, as is demonstrated in this work, the extended implementation of smart metering can be used to support many other important functions in the electricity distribution grid. The present paper proposes a new solution that uses a frequency feature-based method of data time-series provided by the smart metering system to estimate the energy contour at distribution level with the aim of improving the quality of the electricity supply service, of reducing the operational costs and improving the quality of electricity measurement and billing services. The main benefit of this approach is determining future energy demand for optimal energy flow in the utility grid, with the main aims of the best long term energy production and acquisition planning, which lead to lowering energy acquisition costs, optimal capacity planning and real-time adaptation to the unpredicted internal or external electricity distribution branch grid demand changes. Additionally, a contribution to better energy production planning, which is a must for future power networks that benefit from an important renewable energy contribution, is intended. The proposed methodology is validated through a case study based on data supplied by a real power grid from a medium sized populated European region that has both economic usage of electricity-industrial or commercial-and household consumption. The analysis performed in the proposed case study reveals the possibility of accurate energy contour forecasting with an acceptable maximum error. Commonly, an error of 1% was obtained and in the case of the exceptional events considered, a maximum 15% error resulted.

The Impact of the COVID-19 Pandemic on the Orthopedic Residents: A Pan-Romanian Survey.

The COVID-19 pandemic has brought unprecedented challenges, with a potential stress which might affect the education of resident doctors in the field of orthopedics and traumatology. Its repercussion on the residents' strain and training routes is not well known. After two years of pandemic, this paper aims to analyze the repercussion of the coronavirus disease 2019 (COVID-19) on education, medical training, and the mental well-being of Romanian resident doctors in orthopedics and traumatology. In January-February 2022, an electronic questionnaire was distributed to all orthopedic resident doctors in the 12 residential training centers in Romania. Participants (n = 236) were resident doctors with an employment contract and professional activity during the COVID-19 pandemic. Resident doctors who did not work during this period were excluded. An online survey generator was used to electronically create the questionnaire. Statistical analysis was performed in Matlab version R2022a, with the support of Statistics and Machine Learning Toolbox Version 12.3. Descriptive statistics were performed for the standardized questions, while for the open questions, answers were collected by topic. The results of the Chi-square test indicate that there is a statistically significant association regarding the prevalence of infection among residents involved in the treatment of patients with COVID-19 (p = 0.028), and the influence of secondment in COVID-19 sections (p = 0.0003). The infection of residents is not related to their affiliation with a particular medical training center (p = 0.608), gender (p = 0.175), the year of study in residency (p = 0.733), the age group (p = 0.178), and the secondment period (p = 0.114). Residents who participated in the study had an overall well-being index of 13.8 ± 5.7, which indicates a low level of well-being for a large number of residents. Residents who would like to choose a new residency specialization, or would choose a non-medical career, had reduced average WHO wellness rates, as the risk of infection is associated with the treatment of patients with COVID-19 and secondment in COVID-19 sections. The findings of this study may help residency training centers to develop robust programs that can alleviate the impact of this pandemic. Some major changes will be needed to be integrated into residency training programs around the world. Emphasis should be placed on electronic educational portfolios, simulation of surgical processes, and distance learning, all of which have a high potential for health and safety, as well as for the moral support of residents.

Structured Integration and Alignment Algorithm: A Tool for Personalized Surgical Treatment of Tibial Plateau Fractures.

The planning of the surgical treatment in orthopedics, with the help of three-dimensional (3D) technologies, arouses an increasing scientific interest. Scientific literature describes some semi-automatic reconstructive attempts at fragmented bone fractures, but the matching algorithms presented are likely to improve. The aim of this paper is to develop a new method of aligning fragments of comminutive fractures. We have created a structured integration process and an alignment algorithm integrated in a clinical workflow for personalized surgical treatment of fractures. The provided solution is able to align the surfaces of bone fragments derived from the segmentation process of volumetric tomographic data. Positional uncertainties are eliminated interactively by the user, who selects the corresponding pairs of fracture surfaces. The final matching and the right alignment are performed automatically by the innovative alignment algorithm. The paper solves a challenging problem for the reconstruction of fractured bones, namely the choice of the optimal matching option from the situation in which surface portions of a fracture fragment correspond to multiple high fragments. The method is validated in practice for preoperative planning of a 49-year-old male patient who had a tibial plateau fracture of Schatzker type VI.

Smart Metering Systems Optimization for Non-Technical Losses Reduction and Consumption Recording Operation Improvement in Electricity Sector.

One of the keys of enhancing the quality of electric power supply resides in the accuracy of the consumption metering. Nowadays development of the sensors, devices and systems for electricity metering offers the basis for this service. Nevertheless, this achievement in many situations is altered such that appropriate measures must be adopted even if already significant costs have been registered. In this paper is proposed and discussed an optimal solution based on the identification and minimizing the measurement errors for increasing the electricity readings accuracy and lowering the electricity losses and related costs. In this regard, a mathematical model was developed and a particular algorithm for the mentioned problem is proposed and tested in the case of a power distribution company where an enhancement on average of the own technological consumption with 4% was recorded.

Integration of Three-dimensional Technologies in Orthopedics: A Tool for Preoperative Planning of Tibial Plateau Fractures.

BACKGROUND: There is a growing scientific interest in the use of three-dimensional (3D) technologies in orthopedic surgery. Digitalization makes research in orthopedics more accurate and quantitative. Scientific literature describes an overview of current 3D technologies applications in orthopedics, without any emphasis on integrating available technologies as a clinical workflow. OBJECTIVE: To develop a clinical workflow integrating 3D technologies for patient-specific applications in orthopedics validated in practice by employment of a free 3D software solution with the aim of minimizing the intervention. METHOD: By exploring the applications of 3D technologies in orthopedic surgery, we have created a clinical workflow integrating 3D technologies for patient-specific applications in orthopedics. It is validated in practice for preoperative planning of a 49-year-old male patient who had a tibial plateau fracture of Schatzker type VI in his right leg. The software solution we have used is Democratiz3D, from Embodi3d platform, which allows patient-specific modeling and surgical planning. RESULTS: By using the proposed methodology we obtained the model of the tibial plateau fracture Schatzker type VI, as a "solid" representation in stl type files, which represents a numerically defined geometry of the bones fragments. It helps surgeons in planning the surgical approach. The time from the beginning to the end of the analysis was 193 min, which is 15% lower than times reported in similar studies. CONCLUSION: The planning potential of the 3D solution is a valuable instrument for surgeons in exploring the nature of tibial plateau fractures and the formulation of a suitable surgical plan for surface alignment, design and screw fixation guides, strength calculations of bone fragments, and printing surgical objects.