Light gradient boosting-based prediction of quality of life among oral cancer-treated patients.

BACKGROUND AND INTRODUCTION: Statisticians rank oral and lip cancer sixth in global mortality at 10.2%. Mouth opening and swallowing are challenging. Hence, most oral cancer patients only report later stages. They worry about surviving cancer and receiving therapy. Oral cancer severely affects QOL. QOL is affected by risk factors, disease site, and treatment. Using oral cancer patient questionnaires, we use light gradient Boost Tree classifiers to predict life quality. METHODS: DIAS records were used for 111 oral cancer patients. The European Organisation for Research and Treatment of Cancer's QLQ-C30 and QLQ-HN43 were used to document the findings. Anyone could enroll, regardless of gender or age. The IHEC/SDC/PhD/OPATH-1954/19/TH-001 Institutional Ethical Clearance Committee approved this work. After informed consent, patients received the EORTC QLQ-C30 and QLQ-HN43 questionnaires. Surveys were in Tamil and English. Overall, QOL ratings covered several domains. We obtained patient demographics, case history, and therapy information from our DIAS (Dental Information Archival Software). Enrolled patients were monitored for at least a year. After one year, the EORTC questionnaire was retaken, and scores were recorded. This prospective analytical exploratory study at Saveetha Dental College, Chennai, India, examined QOL at diagnosis and at least 12 months after primary therapy in patients with histopathologically diagnosed oral malignancies. We measured oral cancer patients' quality of life using data preprocessing, feature selection, and model construction. A confusion matrix was created using light gradient boosting to measure accuracy. RESULTS: Light gradient boosting predicted cancer patients' quality of life with 96% accuracy and 0.20 log loss. CONCLUSION: Oral surgeons and oncologists can improve planning and therapy with this prediction model.

Prediction of interactomic hub genes in PBMC cells in type 2 diabetes mellitus, dyslipidemia, and periodontitis.

BACKGROUND AND OBJECTIVE: In recent years, the complex interplay between systemic health and oral well-being has emerged as a focal point for researchers and healthcare practitioners. Among the several important connections, the convergence of Type 2 Diabetes Mellitus (T2DM), dyslipidemia, chronic periodontitis, and peripheral blood mononuclear cells (PBMCs) is a remarkable example. These components collectively contribute to a network of interactions that extends beyond their domains, underscoring the intricate nature of human health. In the current study, bioinformatics analysis was utilized to predict the interactomic hub genes involved in type 2 diabetes mellitus (T2DM), dyslipidemia, and periodontitis and their relationships to peripheral blood mononuclear cells (PBMC) by machine learning algorithms. MATERIALS AND METHODS: Gene Expression Omnibus datasets were utilized to identify the genes linked to type 2 diabetes mellitus(T2DM), dyslipidemia, and Periodontitis (GSE156993).Gene Ontology (G.O.) Enrichr, Genemania, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used for analysis for identification and functionalities of hub genes. The expression of hub D.E.G.s was confirmed, and an orange machine learning tool was used to predict the hub genes. RESULT: The decision tree, AdaBoost, and Random Forest had an A.U.C. of 0.982, 1.000, and 0.991 in the R.O.C. curve. The AdaBoost model showed an accuracy of (1.000). The findings imply that the AdaBoost model showed a good predictive value and may support the clinical evaluation and assist in accurately detecting periodontitis associated with T2DM and dyslipidemia. Moreover, the genes with p-value < 0.05 and A.U.C.>0.90, which showed excellent predictive value, were thus considered hub genes. CONCLUSION: The hub genes and the D.E.G.s identified in the present study contribute immensely to the fundamentals of the molecular mechanisms occurring in the PBMC associated with the progression of periodontitis in the presence of T2DM and dyslipidemia. They may be considered potential biomarkers and offer novel therapeutic strategies for chronic inflammatory diseases.

Gaucher: A Systematic Review on Oral and Radiological Aspects.

Background and Objectives: Gaucher disease (GD) is a lysosomal storage disorder with the genetic autosomal recessive transmission. Bone involvement is a prevalent finding in Gaucher disease. It causes deformity and limits daily activities and the quality of life. In 75% of patients, there is bone involvement. This review aims to evaluate the principal findings in the jaw by a Cone-beam computed tomography (CBTC) and X-ray orthopantomography; Materials and Methods: PubMed, Web of Science, Lilacs and Scopus were systematically searched until 31 December 2022. In addition, a manual search was performed using the bibliography of selected articles and a Google Scholar search. Clinical studies were selected that considered principal radiographic findings in radiography in a group of patients affected by GD. Results: Out of 5079 papers, four studies were included. The main findings are generalized rarefaction and enlarged narrow space, anodontia. Conclusions: The exact mechanism of bone manifestation is probably due to the infiltration of Gaucher cells in the bone marrow and, consequently, the destruction of bone architecture. All long bones are a potential means of skeletal manifestation. The jaw is more affected than the maxilla, and the principal features are cortical thinning, osteosclerosis, pseudocystic lesions, mental demineralization, flattening in the head of the condyle, effacement of anatomical structures, thickening of maxillary sinus mucosa. The dentist plays a crucial role in diagnosing and treating these patients. Sometimes the diagnosis can be made by a simple panoramic radiograph. All long bones are affected, and the mandible is particularly involved.

ARTIFICIAL INTELLIGENCE IN MEDICAL DEVICES: PAST, PRESENT AND FUTURE.

Artificial Intelligence (AI) has been drawing attention in the field of medical devices. However, due to system complexity, the variability of their architecture, as well as ethical and regulatory concerns there is an ongoing need to analyze its application and performance.This study presents a narrative commentary on the applications of artificial neural networks (ANN) and machine learning (ML) algorithms in medical devices, past, current and future perspectives of application. One research focus of this study was on identifying problems and issues related to the implementation of AI in medical devices. The commentary is based on scientific articles published in PubMed, Scopus ad ScienceDirect databases, official publications of international organizations: European Comission (EC), Food and Drug Administration (FDA), and World Health Organisation (WHO) published in 2009 - 2020 period. AI is revolutionizing healthcare, from medical applications to clinical engineering. However, before grasp-ing the full potential ethical, legal and social concerns need to be resolved and its application needs to be harmonized and regulated regarding equitable access, privacy, appropriate uses and users, liability and bias and inclusiveness.

From Heart Murmur to Echocardiography - Congenital Heart Defects Diagnostics Using Machine-Learning Algorithms.

The most common clinical sign in pediatric cardiology is heart murmur, which can often be uncharacteristic. The aim of this research was to present the results of development of a classifier based on machine learning algorithms whose purpose is to classify organic murmur that occur in congenital heart defect (CHD). The study is based on the data collected at Pediatric Clinic, Clinical Center University of Sarajevo during three-year period. Totally, 116 children aged from 1 to 15 years were enrolled in the study. Input parameters for classification are parameters obtained during basic physical examination and assessment of patient. First, analysis of relevance of the feature for classification was done using InfoGain, GainRatio, Relief and Correlation method. In the second step, classifiers based on Naive Bayes, Logistic Regression, Decision Tree, Random Forest and Support Vector Machine were developed and compared by performance. The results of this research suggest that high accuracy (>90%) classifier for detection of CHD based on 16 parameters can be developed. Such classifier with appropriate user interface would be valuable diagnostic aid to doctors and pediatricians at primary healthcare level for diagnostic of heart murmurs.

Risks of emergency use authorizations for medical products during outbreak situations: a COVID-19 case study.

BACKGROUND: The world is facing an unprecedented outbreak affecting all aspects of human lives which is caused by the COVID-19 pandemic. Due to the virus novelty, healthcare systems are challenged by a high rate of patients and the shortage of medical products. To address an increased need for essential medical products, national authorities, worldwide, made various legislative concessions. This has led to essential medical products being produced by automotive, textile and other companies from various industries and approved under the emergency use authorizations or legal concessions of national regulatory bodies. This paper presents a narrative commentary of the available documentation on emergency use authorizations and legal concessions for medical products during COVID-19 pandemic. METHODOLOGY: The basis for narrative commentary includes scientific articles published in Web of Science, Scopus, PubMed and Embase databases, official publications of international organizations: Food and Drug Agency (FDA), World Health Organisation (WHO), World Bank and United Nations (UN), and national regulatory agency reports in native languages (English, German, Bosnian, and Croatian) published from November 1, 2019 to May 1, 2020. This paper focuses on three types of essential medical products: mechanical ventilators, personal protective equipment (PPE) and diagnostic tests. Evidence-informed commentary of available data and potential identified risks of emergency use authorizations and legal concessions is presented. DISCUSSION: It is recognized that now more than ever, raising global awareness and knowledge about the importance of respecting the essential requirements is needed to guarantee the appropriate quality, performance and safety of medical products, especially during outbreak situation, such as the COVID-19 pandemic. Emergency use authorizations for production, import and approval of medical products should be strictly specified and clearly targeted from case to case and should not be general or universal for all medical products, because all of them are associated with different risk level. CONCLUSION: Presented considerations and experiences should be taken as a guide for all possible future outbreak situations to prevent improvised reactions of national regulatory bodies.

Testing of Anesthesia Machines and Defibrillators in Healthcare Institutions.

To improve the quality of patient treatment by improving the functionality of medical devices in healthcare institutions. To present the results of the safety and performance inspection of patient-relevant output parameters of anesthesia machines and defibrillators defined by legal metrology. This study covered 130 anesthesia machines and 161 defibrillators used in public and private healthcare institutions, during a period of two years. Testing procedures were carried out according to international standards and legal metrology legislative procedures in Bosnia and Herzegovina. The results show that in 13.84% of tested anesthesia machine and 14.91% of defibrillators device performance is not in accordance with requirements and should either have its results be verified, or the device removed from use or scheduled for corrective maintenance. Research emphasizes importance of independent safety and performance inspections, and gives recommendations for the frequency of inspection based on measurements. Results offer implications for adequacy of preventive and corrective maintenance performed in healthcare institutions. Based on collected data, the first digital electronical database of anesthesia machines and defibrillators used in healthcare institutions in Bosnia and Herzegovina is created. This database is a useful tool for tracking each device's performance over time.

Overview of Next-generation Sequencing Platforms Used in Published Draft Plant Genomes in Light of Genotypization of Immortelle Plant (Helichrysium Arenarium).

INTRODUCTION: Major advancements in DNA sequencing methods introduced in the first decade of the new millennium initiated a rapid expansion of sequencing studies, which yielded a tremendous amount of DNA sequence data, including whole sequenced genomes of various species, including plants. A set of novel sequencing platforms, often collectively named as "next-generation sequencing" (NGS) completely transformed the life sciences, by allowing extensive throughput, while greatly reducing the necessary time, labor and cost of any sequencing endeavor. PURPOSE: of this paper is to present an overview NGS platforms used to produce the current compendium of published draft genomes of various plants, namely the Roche/454, ABI/SOLiD, and Solexa/Illumina, and to determine the most frequently used platform for the whole genome sequencing of plants in light of genotypization of immortelle plant. MATERIALS AND METHODS: 45 papers were selected (with 47 presented plant genome draft sequences), and utilized sequencing techniques and NGS platforms (Roche/454, ABI/SOLiD and Illumina/Solexa) in selected papers were determined. Subsequently, frequency of usage of each platform or combination of platforms was calculated. RESULTS: Illumina/Solexa platforms are by used either as sole sequencing tool in 40.42% of published genomes, or in combination with other platforms - additional 48.94% of published genomes, followed by Roche/454 platforms, used in combination with traditional Sanger sequencing method (10.64%), and never as a sole tool. ABI/SOLiD was only used in combination with Illumina/Solexa and Roche/454 in 4.25% of publications. CONCLUSIONS: Illumina/Solexa platforms are by far most preferred by researchers, most probably due to most affordable sequencing costs. Taking into consideration the current economic situation in the Balkans region, Illumina Solexa is the best (if not the only) platform choice if the sequencing of immortelle plant (Helichrysium arenarium) is to be performed by the researchers in this region.

Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease.

BACKGROUND: This paper presents a system for classification of asthma and chronic obstructive pulmonary disease (COPD) based on fuzzy rules and the trained neural network. METHODS: Fuzzy rules and neural network parameters are defined according to Global Initiative for Asthma (GINA) and Global Initiative for chronic Obstructive Lung Disease (GOLD) guidelines. For neural network training more than one thousand medical reports obtained from database of the company CareFusion were used. Afterwards the system was validated on 455 patients by physicians from the Clinical Centre University of Sarajevo. RESULTS: Out of 170 patients with asthma, 99.41% of patients were correctly classified. In addition, 99.19% of the 248 COPD patients were correctly classified. The system was 100% successful on 37 patients with normal lung function. Sensitivity of 99.28% and specificity of 100% in asthma and COPD classification were obtained. CONCLUSION: Our neuro-fuzzy system for classification of asthma and COPD uses a combination of spirometry and Impulse Oscillometry System (IOS) test results, which in the very beginning enables more accurate classification. Additionally, using bronchodilatation and bronhoprovocation tests we get a complete patient's dynamic assessment, as opposed to the solution that provides a static assessment of the patient.

Chronic mild to moderate mitral regurgitation will not have an impact on left atrial strain parameters in the pediatric population.

BACKGROUND: Left atrial strain (LAS) analysis represents a newer non-invasive, sensitive and specific technique for assessing left atrial (LA) function and early detection of its deformation and dysfunction. However, its applicability in mitral regurgitation (MR) in pediatric population remains unexplored, raising pertinent questions regarding its potential role in evaluating the severity and progression of the disease. OBJECTIVE: To investigate the impact of chronic MR in children and adolescents on LA remodeling and function. METHODS: The study included 100 participants. Patients with primary and secondary chronic MR lasting at least 5 years fit our inclusion criteria. The exclusion criteria from the study were: patients with functional mitral regurgitation due to primary cardiomyopathies, patients with artificial mitral valve, patients with MR who had previously undergone surgery due to obstructive lesions of the left heart (aortic stenosis, coarctation of the aorta), patients with significant atrial rhythm disorders (atrial fibrillation, atrial flutter). The echocardiographic recordings were conducted by two different cardiologists. Outcome data was reported as mean and standard deviation (SD) or median and interquartile range (Q1-Q3). RESULTS: The study included 100 participants, of whom 50 had MR and the remaining 50 were without MR. The average age of all participants was 15.8 ± 1.2 years, with a gender distribution of 37 males and 63 females. There was a significant difference in the values of LA volume index (LAVI), which were higher in patients with MR (p= 0.0001), S/D ratio (and parameters S and D; p= 0.001, p= 0.0001, p= 0.013), mitral annulus radius (p= 0.0001), E/A ratio (p= 0.0001), as well as septal e' (m/s), lateral e' (m/s), and average E/e' ratio, along with the values of TV peak gradient and LV global longitudinal strain (%). There was no significant difference in LA strain parameters, nor in LA stiffness index (LASI). CONCLUSION: Our findings revealed significant differences in several echocardiographic parameters in pediatric patients with MR relative to those without MR, providing insight into the multifaceted cardiac structural and functional effects of MR in this vulnerable population.

Left atrial stiffness is in correlation with left atrial reservoir strain in pediatric patients with mitral regurgitation.

BACKGROUND: Left atrial stiffness index (LASI), defined as the ratio of early diastolic transmitral flow velocity/lateral mitral annulus myocardial velocity (E/e') to peak atrial strain, reflects reduced left atrial (LA) compliance and represents an emerging marker that can be used for noninvasive measurement of fibrosis of LA in patients with mitral regurgitation (MR). OBJECTIVE: To investigate the impact of chronic MR in children and adolescents on the remodeling and function of the LA, quantified through strain parameters and diastolic function. METHODS: The study included fifty patients (n= 50) diagnosed with primary and secondary chronic MR lasting at least 5 years. The echocardiographic recordings were performed by a third party, two cardiologists actively engaged in echocardiography on a daily basis. RESULTS: Older participants had higher values of the LASI (r= 0.467, p= 0.001). Participants with higher LASI values had a smaller LA reservoir (r= 0.784, p= 0.0001) and smaller LA conduit values (r=-0.374, p= 0.00). Participants with higher LASI values had a larger LA diameter (r= 0.444, p-value= 0.001) and higher average E/e' ratio (r= 0.718, p= 0.0001). There was a significant difference (p= 0.04) in the LASI among participants based on the MR jet area (< 20.85% ⩾ 20.85%), LASI was higher in participants with an area greater than 20.85%. Differences in other parameters such as LA reservoir, LA conduit, LA contractile were not statistically significant. CONCLUSION: Increased LA stiffness is associated with diminished atrial compliance and reservoir capacity, and LASI has a potential to as an early marker for assessing disease severity and progression in pediatric MR.

A novel method for conformity assessment testing of defibrillators for post-market surveillance purposes.

BACKGROUND: Defibrillators are medical devices (MDs) used in the most critical situations, hence their performance must be ensured at all times. This requires defibrillators to be subjected to regular performance assessments after they have been placed on the market. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party, notified bodies more strategically in hope to improve traceability of device performance. However, there is still an apparent gap in terms of standardised conformity assessment testing methods. OBJECTIVE: This paper proposes a novel evidence-based method for conformity assessment testing of defibrillators. METHOD: The proposed method is developed in accordance with the International Organisation of Legal Metrology (OIML) guidelines and is intended to be used for conformity assessment testing of defibrillators for post-market surveillance purposes. RESULTS: The developed method was validated from 2018 to 2021 in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of defibrillators as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of defibrillators during PMS, besides increasing reliability of the devices, is the first step in the digital transformation of the management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

A novel method for conformity assessment testing of patient monitors for post-market surveillance purposes.

BACKGROUND: Patient monitors are medical devices used to monitor vital parameters such as heart rate, respiratory rate, blood pressure, blood oxygen saturation, and body temperature during inpatient treatment. As such, patient monitors provide physicians with information necessary to adjust the treatment as well as evaluate the overall status and recovery of the patient. Measurements made by intrinsic sensors of patient monitors must be compliant and provide reliable readings in order to ensure safety and optimal quality of care to the patients. OBJECTIVE: This paper proposes a novel method for conformity assessment testing of patient monitors in healthcare institutions for post-market surveillance purposes. METHOD: The method was developed on the basis of metrology characteristics of sensors used to monitor vital parameters observed by patient monitors and evaluation of their vital safety and performance parameters. In addition to the evaluation of essential safety and visual integrity of patient monitors, their performance in terms of accuracy of the readings is evaluated. RESULTS: The developed method was validated between 2018 and 2021 in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of patient monitors as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of patient monitors during PMS, besides increasing reliability of the devices, is the first step in digital transformation of management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

A novel method for conformity assessment testing of therapeutic ultrasounds for post-market surveillance purposes.

BACKGROUND: Therapeutic ultrasounds are medical devices used for treatment of conditions such muscle spasms, joint contractures or general muscle pain. Their function relies in the delivery of ultrasonic pulses that generate heat in tissue thus relieving the symptoms of aforementioned conditions. Accuracy of the delivered pulses directly affects the quality and effectiveness of the treatment and has to be ensured throughout the utilization of the therapeutic ultrasound in practice. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party, notified bodies more strategically in hope to improve traceability of device performance. However, there is still an apparent gap in terms of standardised conformity assessment testing methods. OBJECTIVE: This paper proposes a novel method for conformity assessment testing of therapeutic ultrasounds for post-market surveillance purposes. METHOD: The method was developed based on metrology characteristics of therapeutic ultrasounds and includes visual, electrical safety and performance inspections of therapeutic ultrasounds to ensure that both safety and treatment reliability are achieved. RESULTS: The developed method was validated between 2018 and 2021 in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of therapeutic ultrasounds as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of therapeutic ultrasounds during PMS, besides increasing reliability of the devices, is the first step in digital transformation of management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

A novel method for conformity assessment testing of dialysis machines for post-market surveillance purposes.

BACKGROUND: Dialysis machines are used regularly in healthcare practice. They are classified as a type of medical device with moderate and high risk therefore significant requirements are placed on their safety and performance every time they are used on patients. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party, notified bodies more strategically in hope to improve traceability of device performance. However, there is still an apparent gap in terms of standardised conformity assessment testing methods. OBJECTIVE: This paper proposes a novel evidence-based method for conformity assessment testing of dialysis machines for post-market surveillance purposes. METHOD: The novel method is developed according to the International Organisation of Legal Metrology (OIML) guidelines and is to be used for the purpose of conformity assessment testing of Dialysis machines with respect to their metrological characteristics during PMS. RESULTS: The developed method was validated between 2018 and 2021 in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of dialysis machines as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of dialysis machines during PMS, besides increasing reliability of the devices, is the first step in digital transformation of management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

A novel method for conformity assessment testing of mechanical ventilators for post-market surveillance purposes.

BACKGROUND: Mechanical ventilators are medical devices used in intensive care units when patients are in need of mechanical aid to facilitate the process of breathing. As the function of breathing is the exchange of gases, the mechanical ventilator takes over that function while the patient is incapable to spontaneous breathing. As these devices are used to maintain the life of patents, their performance must be ensured and there cannot be significant deviations in the volumes and pressure of gases they introduce to the patient. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party, notified bodies more strategically in hope to improve traceability of device performance. However, there is still an apparent gap in terms of standardised conformity assessment testing methods. OBJECTIVE: This paper proposes a novel method for conformity assessment testing of mechanical ventilators for post-market surveillance purposes. METHOD: The method was developed on the basis of metrology characteristics of mechanical ventilators and evaluation of their vital safety and performance parameters. In addition to the evaluation of essential safety and visual integrity of mechanical ventilators, their performance in terms of volume of oxygen delivered to the patient as well as the flow and pressure of the delivered gas is evaluated. RESULTS: The developed method was validated between 2018 and 2021 in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of mechanical ventilators as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of mechanical ventilators during PMS, besides increasing reliability of the devices, is the first step in digital transformation of management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

A novel method for conformity assessment testing of anaesthesia machines for post-market surveillance purposes.

BACKGROUND: Anaesthesia machines, as moderate to high-risk medical devices intended for use on patients during surgical procedures must be safe and reliable with traceable performance every time they are used in healthcare practice. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party, notified bodies more strategically in hope to improve traceability of device performance. However, there is still an apparent gap in terms of standardised conformity assessment testing methods. OBJECTIVE: This paper proposes a novel evidence-based method for conformity assessment testing of anaesthesia machines for post-market surveillance purposes. METHOD: The novel method is developed according to the International Organisation of Legal Metrology (OIML) guidelines and is to be used for the purpose of conformity assessment testing of anaesthesia machines with respect to their technical and metrological characteristics during PMS. RESULTS: The developed method was validated between 2018 and 2021 in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of anaesthesia machines as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of anaesthesia machines during PMS, besides increasing reliability of the devices, is the first step in digital transformation of management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

A novel method for conformity assessment testing of electrocardiographs for post-market surveillance purposes.

BACKGROUND: Monitoring cardiac parameters is the fundamental aspect of every diagnostic process and is facilitated by electrocardiography (ECG) devices. This way, continuous state-of-the-art performance of ECG devices can be ensured. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party, notified bodies more strategically in hope to improve traceability of device performance. However, there is still an apparent gap in terms of standardised conformity assessment testing methods. OBJECTIVE: This paper proposes a novel method for conformity assessment testing of ECG devices for post-market surveillance purposes. METHOD: The method was developed on the basis of International Organisation of Legal Metrology (OIML) guidelines and applied in healthcare institutions from 2018 to 2021. RESULTS: The developed method was validated in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of the ECG device as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of ECG devices during PMS, besides increasing reliability of the devices, is the first step in the digital transformation of the management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

A novel method for conformity assessment testing of infusion and perfusion pumps for post-market surveillance purposes.

BACKGROUND: Introduction of fluids, medicaments and nutrients into the human body during hospitalization is fundamental for treatment and healing of patients. Fluids are introduced by means of infusion pumps while nutrients and medicaments are introduced by perfusion pumps. It is of vital importance for these devices to deliver exact amounts of the aforementioned substances as significant deviations can result in severe patient harm. Therefore it is important to effectively monitor their performance and prevent failures. OBJECTIVE: This paper proposes a novel method for conformity assessment testing of infusion and perfusion pumps for post-market surveillance purposes. METHOD: The method was developed on the basis of metrology characteristics of the devices. In addition to the evaluation of essential safety and visual integrity of infusion and perfusion pumps, their performance in terms of delivered volumes was assessed and monitored. RESULTS: The developed method was validated between 2018 and 2021 in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of infusion and perfusion pumps as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of infusion and perfusion pumps during PMS, besides increasing reliability of the devices, is the first step in digital transformation of management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

A novel method for conformity assessment testing of infant incubators for post-market surveillance purposes.

BACKGROUND: Premature born infants or infants born sick require immediate medical attention and decreasing the stress imposed onto their body by the environment. Infant incubators provide an enclosed environment that can be controlled to fit the needs of the infant. As such, their performance must be consistent and without significant deviations. The only manner to ensure this is by post-market surveillance (PMS) focused on evaluation of both safety and performance. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party, notified bodies more strategically in hope to improve traceability of device performance. However, there is still an apparent gap in terms of standardised conformity assessment testing methods. OBJECTIVE: This paper proposes a novel method for conformity assessment testing of infant incubators for post-market surveillance purposes. METHOD: The method was developed based on guidelines for devices providing measurements laid out by the International Organisation of Legal Metrology (OIML). The methodology was validated during a four year period in healthcare institutions of all levels. RESULTS: The developed method was validated between 2018 and 2021 in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of infant incubators as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. CONCLUSION: A standardized approach in conformity assessment testing of infant incubators during PMS, besides increasing reliability of the devices, is the first step in digital transformation of management of these devices in healthcare institutions opening possibility for use of artificial intelligence.