Diagnostic Parameters Research Articles

Comparison of preoperative diagnostic performance between dual-energy CT, conventional CT, and MRI in endometrial cancer.

To compare the diagnostic performance of virtual monoenergetic imaging (VMI), computed tomography (CT), and magnetic resonance imaging (MRI) in patients with endometrial cancer (EC). This retrospective study analysed 45 EC patients (mean age: 62 years, range: 44-84 years) undergoing contrast-enhanced CT with dual-energy CT (DECT) and MRI between September 2021 and October 2022. Dual-energy CT generated conventional CT (C-CT) and 40 keV VMI. Quantitative analysis compared contrast-to-noise ratio (CNR) of tumour to myometrium between C-CT and VMI. Qualitative assessment by 5 radiologists compared C-CT, VMI, and MRI for myometrial invasion (MI), cervical invasion, and lymph node metastasis. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated and compared for each diagnostic parameter. Virtual monoenergetic imaging showed significantly higher CNR than C-CT (p < 0.001) and a higher sensitivity for MI than C-CT (p = 0.027) and MRI (p = 0.011) but lower specificity than MRI (p = 0.018). C-CT had a higher sensitivity and AUC for cervical invasion than MRI (p = 0.018 and 0.004, respectively). The study found no significant superiority of MRI over CT across all diagnostic parameters. VMI demonstrated heightened sensitivity for MI, and C-CT showed greater sensitivity and AUC for cervical invasion than MRI. This suggests that combining VMI with C-CT holds promise as a comprehensive preoperative staging tool for EC when MRI cannot be performed.

Unisex and Sex-Specific Prescriptive Fetal Growth Charts for Improved Detection of Small-for-Gestational-Age Babies in a Low-Risk Population: A post hoc Analysis of a Cluster-Randomized Study.

Our aim was to develop and evaluate the performance of population-based sex-specific and unisex prescriptive fetal abdominal circumference growth charts in predicting small-for-gestational-age (SGA) birthweight, severe SGA (sSGA) birthweight, and severe adverse perinatal outcomes (SAPO) in a low-risk population. This is a post hoc analysis of the Dutch nationwide cluster-randomized IRIS study, encompassing ultrasound data of 7,704 low-risk women. IRIS prescriptive unisex and IRIS sex-specific abdominal circumference (AC) fetal growth charts were derived using quantile regression. As a comparison, we used the descriptive unisex Verburg chart, which is commonly applied in the Netherlands. Diagnostic parameters were calculated based on the 34-36 weeks' ultrasound. Sensitivity rates for predicting SGA and sSGA birthweights were more than twofold higher based on the IRIS prescriptive sex-specific (respectively SGA 43%; sSGA 59%) and unisex (SGA 39%; sSGA 55%) charts, compared to the Verburg chart (SGA 16%; sSGA 23% both p &lt; 0.01). Specificity rates were highest for Verburg (SGA 99%; sSGA 98%) and lowest for IRIS sex-specific (SGA 94%; sSGA 92%). Results for predicting SGA with SAPO were similar for the prescriptive charts (44%), and again higher than the Verburg chart (20%). The IRIS sex-specific chart identified significantly more males as SGA and sSGA (respectively, 42%; 60%, p &lt; 0.001) than the IRIS unisex chart (respectively, 35%; 53% p &lt; 0.01). Our study demonstrates improved performance of both the IRIS sex-specific and unisex prescriptive fetal growth compared to the Verburg descriptive chart, doubling detection rates of SGA, sSGA, and SGA with SAPO. Additionally, the sex-specific chart outperformed the unisex chart in detecting SGA and sSGA. Our findings suggest the potential benefits of using prescriptive AC fetal growth charts in low-risk populations and emphasize the importance of considering customizing fetal growth charts for sex. Nevertheless, the increased sensitivity of these charts should be weighed against the decrease in specificity.

Cerebrospinal fluid neurofilament light chain in acute optic neuritis and its predictive ability of multiple sclerosis

BackgroundStudies on the capability of cerebrospinal fluid neurofilament light chain (cNfL) to predict multiple sclerosis (MS) conversion in clinically isolated syndromes have yielded varying results.ObjectivesTo expand our understanding of cNfL in optic neuritis (ON) and investigate whether incorporating cNfL into the 2017 McDonald criteria could accelerate the diagnosis of MS in patients with ON.MethodscNfL was measured in diagnostic samples from 74 patients with verified ON. MS was diagnosed using the 2017 McDonald criteria with a minimum observation time of two years from ON onset.Results20.5% of 44 MS-converters did not fulfil the 2017 McDonald criteria at ON onset. A doubling of cNfL was associated with 207% (74%–514%) higher odds of MS (p = 0.00042, adjusted for age). Fulfilment of ≥ 1 MRI criterion for dissemination in space (DIS) and presence of brain contrast-enhancing lesions were associated with higher cNfL. Furthermore, cNfL correlated with inter-eye differences in retinal nerve fiber layer (RNFL) thickness (Spearman’s ρ = 0.46, p = 8 × 10–5). Incorporating cNfL ≥ 906 pg/mL as a substitute for either dissemination in time or one MRI criterion for DIS increased the sensitivity (90.9% vs. 79.6%) and accuracy (91.9% vs. 87.8%), but also reduced the specificity (93.3% vs. 100%) of the 2017 McDonald criteria.ConclusioncNfL was related to MS diagnostic parameters and the degree of RNFL swelling. Clinical use of cNfL may aid in identification of ON patients with increased risk of MS until larger studies have elaborated on the potential loss of specificity if used diagnostically.

Neurological Complications of COVID-19: Unraveling the Pathophysiological Underpinnings and Therapeutic Implications.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease (COVID-19), induced a global pandemic with a diverse array of clinical manifestations. While the acute phase of the pandemic may be waning, the intricacies of COVID-19's impact on neurological health remain a crucial area of investigation. Early recognition of the spectrum of COVID-19 symptoms, ranging from mild fever and cough to life-threatening respiratory distress and multi-organ failure, underscored the significance of neurological complications, including anosmia, seizures, stroke, disorientation, encephalopathy, and paralysis. Notably, patients requiring intensive care unit (ICU) admission due to neurological challenges or due to them exhibiting neurological abnormalities in the ICU have shown increased mortality rates. COVID-19 can lead to a range of neurological complications such as anosmia, stroke, paralysis, cranial nerve deficits, encephalopathy, delirium, meningitis, seizures, etc., in affected patients. This review elucidates the burgeoning landscape of neurological sequelae associated with SARS-CoV-2 infection and explores the underlying neurobiological mechanisms driving these diverse manifestations. A meticulous examination of potential neuroinvasion routes by SARS-CoV-2 underscores the intricate interplay between the virus and the nervous system. Moreover, we dissect the diverse neurological manifestations emphasizing the necessity of a multifaceted approach to understanding the disease's neurological footprint. In addition to elucidating the pathophysiological underpinnings, this review surveys current therapeutic modalities and delineates prospective avenues for neuro-COVID research. By integrating epidemiological, clinical, and diagnostic parameters, we endeavor to foster a comprehensive analysis of the nexus between COVID-19 and neurological health, thereby laying the groundwork for targeted therapeutic interventions and long-term management strategies.

Diagnostic Risk Percentage Based on Vital Signs Readings on Health Monitoring Devices

The development of the field of health technology has progressed rapidly - especially in the aspect of being connected to the Internet and also allowing the storage and monitoring of vital signs data utilizing IoT features. However, there is no health monitoring that contains advanced check-up analysis referring to the acquisition of vital signs data that has been stored in the health data record. This is exactly where additional parameters beyond the vital signs have not been integrated in health monitoring. The purpose of this independent research is to find a gap between industry and academia in the form of additional parameters that are not yet available in the industrial world. The additional parameter is the percentage value of health diagnostic risk. The selection of this parameter is based on the need to analyze the level of diagnostic risk through the acquisition of vital signs that have available readings in health monitoring device equipment. The algorithm mechanism itself revolves around mapping for the diagnosis of health conditions referring to the normal limits of vital signs utilizing the decision tree algorithm. The goal is none other than to simplify the flow in determining the patient's advanced health diagnosis. Regarding the diagnostic risk percentage parameter, the diagnosis and calculation include five vital signs that are the main indicators: heart rate, oxygen saturation (SPO2), body temperature (TBody) supplemented with skin temperature (TSkin), and respiratory rate.

Quintessential f(G) gravity with statistically fitting of H(z)

Inspired by high-energy physics and by considering standard gravity theory as the low-energy limit of quantum theory, the modification of general relativity as [Formula: see text] has been proposed. This paper is dedicated to investigating the cosmological model of modified Gauss–Bonnet gravity in four dimensions. General field equations for the four-dimensional Friedmann– Robertson–Walker metric are given in detail. Also, it is well known that Hubble parameter [Formula: see text] measurements are helpful for the inference of cosmological model parameters. We try to explain the MCMC statistical approach used to calculate Hubble’s parameter. The resulting form of [Formula: see text] was limited using Cosmic Chronometric data, Standard Candles SN Ia from Pantheon, and Baryon Acoustic Oscillations to obtain the best match values by using the regression equation. Finally, to examine the late-time dynamics of our Universe, the behavior of physical and kinematic variables like the deceleration parameter [Formula: see text], State-finder parameters [Formula: see text], diagnostic parameter ([Formula: see text]), equation of state parameter as well as the behavior of energy conditions versus redshift with the parameter values are presented.

Improving Hepatitis B diagnosis by implementing statistical quality controls

Hepatitis B is a viral infection that causes major health problems worldwide. The hepatitis B virus (HBV) and 1.2 million deaths per year globally infect more than two billion people. Hepatitis B mainly affects the liver and causes liver cirrhosis and hypocellularity carcinoma. This study investigates diagnostic quality parameters of quantitative polymerase Chain Reaction (qPCR) and enzyme-linked Immunosorbent Assay (ELISA) called enzyme immunoassay (EIA) for HBV Diagnosis. The research was conducted at the Molecular Biochemistry Laboratory (MBL) in the Department of Biochemistry at the University of Agriculture, Faisalabad, Pakistan. The samples for the randomized study containing 977 male and female samples who had pre-diagnosis HBV infection were selected for this comparative study and collected from the Punjab Institute of Nuclear Medicine (PINUM) Hospital and Allied Hospital Faisalabad, Pakistan. This study compared the sensitivity and specificity of the ELISA assay with the HBV qPCR assay to diagnose HBV infection. The cut-off value &lt; 1.00 was considered non-reactive, whereas ≥ 1.00 was reactive patients for ELISA. Similarly, HBV viral load was measured on qPCR &lt; 101 IU/mL was considered a negative result, and &gt; 101 IU/mL showed positive results. Statistical data analysis was conducted using Statistical Package for Social Sciences (SPSS 22) software. These tests were used to diagnose HBV infection on a large scale to calculate the percentage value of sensitivity, specificity, and other parameters. With a 95% confidence interval, the qPCR's positive predictive value (PPV) was 46%, whereas 52% for ELISA. The negative predictive value (NPV) for qPCR was 98%, but it was the same for ELISA. The specificity for qPCR was 91% and 92% for ELISA. The sensitivity value for qPCR was 83%, and 87% for ELISA was observed from the samples. Accuracy for both methods varied, which showed their proficiency and size. The results obtained from qPCR were more accurate and authentic than those obtained from ELISA.

Deep Learning–Assisted Two-Dimensional Transperineal Ultrasound for Analyzing Bladder Neck Motion in Women With Stress Urinary Incontinence

BACKGROUNDNo universally recognized transperineal ultrasound parameters are available for evaluating stress urinary incontinence. The information captured by commonly used perineal ultrasound parameters is limited and insufficient for a comprehensive assessment of stress urinary incontinence. Although bladder neck motion plays a major role in stress urinary incontinence, objective and visual methods to evaluate its impact on stress urinary incontinence remain lacking. OBJECTIVETo use a deep learning–based system to evaluate bladder neck motion using two-dimensional transperineal ultrasound videos, exploring motion parameters for diagnosing and evaluating stress urinary incontinence. We hypothesized that bladder neck motion parameters are associated with stress urinary incontinence and are useful for stress urinary incontinence diagnosis and evaluation. STUDY DESIGNThis retrospective study including 217 women involved the following parameters: maximum and average speeds of bladder neck descent, β angle, urethral rotation angle, and duration of the Valsalva maneuver. The fitted curves were derived to visualize bladder neck motion trajectories. Comparative analyses were conducted to assess these parameters between stress urinary incontinence and control groups. Logistic regression and receiver operating characteristic curve analyses were employed to evaluate the diagnostic performance of each motion parameter and their combinations for stress urinary incontinence. RESULTSOverall, 173 women were enrolled in this study (82, stress urinary incontinence group; 91, control group). No significant differences were observed in the maximum and average speeds of bladder neck descent and in the speed variance of bladder neck descent. The maximum and average speed of the β and urethral rotation angles were faster in the stress urinary incontinence group than in the control group (151.2 vs 109.0 mm/s, P=0.001; 6.0 vs 3.1 mm/s, P <0.001; 105.5 vs 69.6 mm/s, P <0.001; 10.1 vs 7.9 mm/s, P=0.011, respectively). The speed variance of the β and urethral rotation angles were higher in the stress urinary incontinence group (844.8 vs 336.4, P <0.001; 347.6 vs 131.1, P <0.001, respectively). The combination of the average speed of the β angle, maximum speed of the urethral rotation angle, and duration of the Valsalva maneuver demonstrated a strong diagnostic performance (area under the curve, 0.87). When 0.481*β anglea + 0.013*URAm + 0.483*Dval = 7.405, the diagnostic sensitivity was 70% and specificity was 92%, highlighting the significant role of bladder neck motion in stress urinary incontinence, particularly changes in the speed of the β and urethral rotation angles. CONCLUSIONSA system utilizing deep learning can describe the motion of the bladder neck in women with stress urinary incontinence during the Valsalva maneuver, making it possible to visualize and quantify bladder neck motion on transperineal ultrasound. The speeds of the β and urethral rotation angles and duration of the Valsalva maneuver were relatively reliable diagnostic parameters.

Acoustic frequency-based method for high-speed aircraft combustion analysis and hybrid artificial intelligence diagnostics

In the paper, a method of high-speed continuous combustion monitoring for jet aircrafts, based on acoustic data processing, is proposed. As part of the research, acoustic signals corresponding to the specific phases of the combustible mixture formation and its combustion were separated. They were assigned to the generated process energy value. In the result, parametric functions were obtained in multidimensional spaces of states and processes. Parameters and acoustic characteristics in the amplitude, frequency and JTFA domains constituted information about particular symptoms in the jet engine, thanks to which reference waveforms of signals and forms for specific malfunctions were mapped. The above graphic characteristics have been parameterized to determine their diagnostic reliability factors.The method is verified by empirical signals obtained from turbojet propulsion system in time and power dependent conditions. Appropriate exothermic combustion phases were assigned for the determined acoustic spectra, taking into account the obtained power. Then, representative diagnostic parameters transformed in the process values domain were calculated. Finally, monitoring functions and algorithms of combustion efficiency with determination of malfunctions sources (at dynamic conditions) are proposed.As a result, it is possible to identify first outbreaks of design and process failures during fuel injection and combustion in aircrafts, taking into account artificial intelligence methods. The obtained results indicate it is possible to adapt the acoustic characteristics of the spectra and their discrete representatives, for appropriate states and failures, to detect first dangerous symptoms in the aircraft during flight conditions (supporting OBD with the acoustic adaptive diagnostic procedures).

Підвищення ефективності забезпечення працездатності транспортних засобів

Accidental failures, leading to unplanned repairs, significantly increase the cost of their elimination compared to planned measures. A significant part of such failures are not sudden in nature. Gradual failure is preceded by a gradual change in some parameters. The impact of gradual failures on the efficient operation of road freight transport is increasing. Despite the fact that the failure of the engine, clutch or automatic transmission is not dangerous to the life and health of people, their impact on the economic condition of the enterprise is significant. There is a trend of decreasing the size of the rolling stock fleet for most of the country's motor transport enterprises. Therefore, the importance of keeping each car in working condition increases. To increase the accuracy of the prevention of gradual and sudden-gradual failures, a forecasting method based on the diagnosis of trucks with a specialized diagnostic car scanner TEXA Navigator MULTIHUB is proposed. The selection of diagnostic parameters was carried out in accordance with the requirements for compliance with the accuracy, efficiency, and informativeness of the diagnostic parameters. The research was carried out on MAN TG-X, MAN TGA, VOLVO FH 12, DAF 105 XF, and DAF 106 cars. A sequential cylinder shutdown test was conducted to determine the compression and efficiency of all cylinders. A gradual change in the operating parameter is determined based on the obtained decrease in revolutions. In the next test, the correction of the injectors for the amount of fuel injected into the cylinders is checked. The reference value is taken as 0. The correction tolerance for increasing or decreasing the fuel supply time should be within +1 or –1. Based on the received data, the nozzle is determined, in the correction gradually increases, which signals a problem with the nozzle's operation. For the clutch, a test of the position of the start of switching on and off was carried out. By reducing the percentage of idling, you can determine the gradual engagement of the clutch. All the conducted tests make it possible to graphically display a change in a parameter or property and, using extrapolation, to predict the moment of failure. All cars carry out freight transportation in international traffic. Control parameters and data extrapolation made it possible to predict engine, clutch, and automatic transmission failures. Selected diagnostic parameters can be used to predict and prevent failures.

Дослідження режимів розгону автомобіля Skoda Octavia на роликовому стенді

As you know, the main characteristics that determine the state of the power unit are the power level and torque. These parameters affect the dynamic qualities of the car and can also play a role in fuel consumption and emission levels. To check these characteristics, traction roller stands of the inertial type are used. These stands allow you to simulate real traffic conditions and loads. Usually, on such stands, the traction force on the driving wheels is measured, which makes it easy to calculate the power in certain driving modes. However, creating a full-fledged load on the driving wheels of the car being diagnosed requires the use of powerful loading and driving devices. This significantly increases the cost of the stand and its metal content. An alternative to this method is the compressed acceleration method. In this method, the load is created by a relatively small inertial mass together with a loading and driving device of moderate power. The diagnostic parameter in this method can be traction force on the wheels, acceleration, time or path of acceleration of the wheels in the selected speed range. For measurement accuracy, it is better to use acceleration time. However, all the advantages of the method can be manifested only with the correct choice of test modes. During testing, results depend on the accuracy and stability of maintaining the test mode. Acceleration time will be measured more accurately, the slower the wheels and rollers of the stand accelerate. During the tests, it is necessary to choose the high-speed measurement mode to ensure a sufficiently stable torque value. The article analyzes the acceleration modes of a car on a roller stand and their influence on the accuracy of diagnostics. The smallest error is achieved when measuring acceleration time from 50 to 70 km/h in IV gear with additional load or in V gear without load.

Diagnostic Imaging Performance of Dual-Energy Computed Tomography Compared with Conventional Computed Tomography and Magnetic Resonance Imaging for Uterine Cervical Cancer.

Objective This article evaluates the ability of low-energy (40 keV) virtual monoenergetic images (VMIs) in the local diagnosis of cervical cancer compared with that of conventional computed tomography (C-CT) and magnetic resonance imaging (MRI), using clinicopathologic staging as a reference. Methods This prospective study included 33 patients with pathologically confirmed cervical cancer who underwent dual-energy CT and MRI between 2021 and 2022. The contrast-to-noise ratio (CNR) of the tumor-to-myometrium was compared between C-CT and VMI. Additionally, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) for each local diagnostic parameter were compared between C-CT, VMI, and MRI. Interradiologist agreement was also assessed. Results The mean CNR was significantly higher on VMI ( p = 0.002). No significant difference in AUC was found between C-CT and VMI for all local diagnostic parameters, and the specificity of VMI was often significantly less than that of MRI. For parametrial invasion, mean sensitivity, specificity, and AUC for C-CT, VMI, and MRI were 0.81, 0.99, 0.93; 0.64, 0.35, 0.79; and 0.73, 0.67, 0.86, respectively, and MRI had significantly higher specificity and AUC than that of VMI ( p = 0.013 and 0.008, respectively). Interradiologist agreement was higher for VMI than C-CT and for MRI than VMI. Conclusion The CNR of VMI was significantly higher than C-CT and interradiologist agreement was better than with C-CT; however, the overall diagnostic performance of VMI did not significantly differ from C-CT and was inferior to MRI. VMI was characterized by low specificity, which should be understood and used for reading.

Удосконалення методу оцінки програмного забезпечення контролю параметрів транспортних засобів

The purpose of the conducted research is to improve the method of evaluating the performance of the vehicle parameter control software. It is stated that a new technique for road transport in the field of monitoring its working condition is the creation of information systems for organizational and functional support of rolling stock operation processes with the help of information integration, namely the stages of the life cycle of rolling stock and systems for its technical control and diagnostics. It is shown that nowadays in road transport the basis of life cycle information support can be CALS or IPV/CALS/PLM - technologies (continuous support of the life cycle of vehicles), which are sometimes called product information support systems and are a part of intelligent transport systems. The analysis and clarification of the structure of the intelligent vehicle monitoring system was carried out on the example of the assessment of its environmental safety and its engine parameters. In the work, it is also planned to obtain experimental data from vehicle, the results of processing of which will allow to prove the existence of a real possibility of using the diagnostic complex on a modern automatic transmission system. It should be noted that the system for monitoring environmental safety indicators of vehicle, which is proposed by the authors, also contains in its composition the subsystem of intelligent processing of primary information, which can be used precisely in the role of "intelligent monitoring system". The data obtained and analyzed in the work indicate the need to also improve the efficiency of the neutralization of harmful substances in the engine warm-up mode, which can be implemented by reducing the engine warm-up time and more effective control of the injection/ignition process in transient modes, as well as by introducing an improvement algorithm of the control subsystem composition of the mixture precisely with feedback. The main diagnostic parameters of the vehicle engine during the start-up and warm-up processes, which affect the composition of harmful substances in the exhaust gases, were obtained experimentally. The proposed scheme for monitoring pollution of the roadside environment by traffic flows in the city.

Thickened photoreceptor outer segment layer in children with hyperopic anisometropic amblyopia.

To quantitatively investigate the reflectivity and structure of the outer retinal layers in children with hyperopic anisometropic amblyopia by using swept-source optical coherence tomography (SS-OCT). Seventy-eight patients with amblyopia and 64 age-matched children with normal vision were included in this study. All participants underwent SS-OCT and detailed ophthalmic examinations. Longitudinal reflectance profile measurements were measured using Image J. The reflectivity of outer retinal layers was measured at the three selected positions: subfovea, 1 mm nasal to the fovea, and 1 mm temporal to the fovea. The reflectivity ratios were calculated by outer retinal layers divided by the nuclear layer (ONL) for normalization. Photoreceptor outer segment layer thickness was also measured. The results were compared between the amblyopia and normal controls. The possible effects of age, sex, and axial length on results were adjusted by generalized estimating equations. Photoreceptor outer segment layer thickness was significantly greater in amblyopic eyes than in normal control eyes at all three regions (18.41 ± 1.83 vs. 16.84 ± 1.39, P < 0.001 at the fovea; 14.78 ± 1.34 vs. 14.19 ± 1.40, P = 0.030 at 1 mm nasal to the foveal; 14.92 ± 1.48 vs. 14.41 ± 1.32, P = 0.049 at 1 mm temporal to the fovea). The reflectivity ratio of outer segment/ONL was higher only at 1 mm nasal to the fovea (2.94 ± 0.61 vs. 2.70 ± 0.42, P = 0.02). Subfoveal OS thickness was positively correlated with choroidal thickness (r = 0.248, P = 0.018) but was not correlated with spherical equivalent, age, axial length, or logMAR visual acuity. Quantitative measurement of SS-OCT images revealed greater photoreceptor outer segments in both eyes of children with amblyopia than in normal control eyes. A thicker OS thickness is somehow related to amblyopia, and this may be a new useful diagnostic parameter for amblyopia.

Evaluation of the Diagnostic Sensitivity of Digital Vibration Sensors Based on Capacitive MEMS Accelerometers.

In recent years, there has been an increasing use of digital vibration sensors that are based on capacitive MEMS accelerometers for machine vibration monitoring and diagnostics. These sensors simplify the design of monitoring and diagnostic systems, thus reducing implementation costs. However, it is important to understand how effective these digital sensors are in detecting rolling bearing faults. This article describes a method for determining the diagnostic sensitivity of diagnostic parameters provided by commercially available vibration sensors based on MEMS accelerometers. Experimental tests were conducted in laboratory conditions, during which vibrations from 11 healthy and faulty rolling bearings were measured using two commercial vibration sensors based on MEMS accelerometers and a piezoelectric accelerometer as a reference sensor. The results showed that the diagnostic sensitivity of the parameters depends on the upper-frequency band limit of the sensors, and the parameters most sensitive to the typical fatigue faults of rolling bearings are the peak and peak-to-peak amplitudes of vibration acceleration. Despite having a lower upper-frequency range compared to the piezoelectric accelerometer, the commercial vibration sensors were found to be sensitive to rolling bearing faults and can be successfully used in continuous monitoring and diagnostics systems for machines.

Health endangering overweight in preschool children

Background: Body mass index (BMI) is the dominant diagnostic parameter for obesity, but its suitability is controversial. Physical fitness (PF) can be used as an indicator for unhealthy body composition. Objectives: To characterize groups of overweight children via different anthropometric parameters and their respective PF. Sample and Methods: Anthropometric measurements (BMI, waist circumference (WC), skinfold thickness (SF), mid-upper arm circumference (MUAC) were assessed in 147 preschool children (age 4.7 ± 1.8 years) at 12 German Kindergartens. Measurements were related to a field battery for PF, assessing musculoskeletal fitness and motor fitness. Results: All anthropometric measurements characterize different children as overweight, only four children are classified as overweight by all measurements. Children with elevated triceps SF alone or in combination with high subscapular SF or WC but not BMI showed lower PF compared with non-overweight children (long jump (p &lt; 0.001), high jump (p = 0.002), shuttle run (p = 0.032)). Conclusions: Triceps SF measuring peripheral fat mass alone and in combination with parameters of central fat might be an effective method to detect poor PF indicating health impairing overweight in 3- to 6-year-old children while preventive examinations should not be placed exclusively on the BMI.

The impact of extended preoperative examination on the treatment tactics choice before the second stage of revision hip arthroplasty

Background. Reinfection and recurrence of periprosthetic infection rates during the second stage of revision hip arthroplasty (RHA) remain quite high. Performing preoperative diagnostic aspiration in patients with the installed hip spacer is a controversial issue. Aims of the study: 1) to compare the diagnostic accuracy, specificity and sensitivity of the used infection markers as a part of preoperative diagnostic protocols in order to exclude reinfection in patients with installed hip spacer before the second stage of RHA; 2) to analyze and compare the microbiological spectrum obtained at the stages of RHA. Methods. Diagnostic accuracy parameters of the used infection markers were assessed in order to exclude reinfection/recurrence in 107 patients with installed hip spacer. All patients were divided into two groups. In Group 1 (prospective), blood tests as well as diagnostic aspiration of synovial fluid were performed within the extended diagnostic protocol. In Group 2 (retrospective), the examination was performed according to the screening preoperative diagnostic protocol including blood tests. The used reference range of inflammatory biomarkers was based on the “small criteria” of ICM 2018. According to the results of the intraoperative microbiological examination of peri-implant tissue samples at the first and second stages of RHA, the analysis of detected microflora was conducted in order to assess probable reinfection/recurrence. Results. According to the results of the intraoperative microbiologic examination during the second stage of RHA, reinfection was detected in 40% of cases: in Group 1 — 9 cases, in Group 2 — 31 case. Synovial fluid was obtained from 85% of cases when preoperative diagnostic aspiration was performed. Synovial fluid could not be obtained in 15% cases (dry joint). Conclusion. Performing preoperative diagnostic aspiration before the second stage of RHA in patients with the installed spacer allowed choosing correct treatment tactics in 9% of cases. The parameters of diagnostic accuracy accounted for 82,6%. In the structure of detected pathogens in case of recurrence and reinfection, the representatives of Gram-positive coagulase-negative flora were the most frequent.

Evaluation of screening tools for primary ciliary dyskinesia in Egypt: single center study.

Primary ciliary dyskinesia (PCD) is a chronic respiratory illness that places significant strain on the healthcare system due to the complexity and expense of its diagnosis and treatment methods. The diagnostic process typically requires skilled technicians and an assortment of intricate, costly, and time-consuming approaches. Implementing screening tools can enhance efficiency by focusing the diagnostic process on those strongly suspected of having PCD. Tools such as the PCD Rule (PICADAR), North America Criteria Defined Clinical Features (NA-CDCF), the Clinical Index Score (CI), and the newly proposed CInew13 could potentially serve as useful screening tools. This study aims to examine the effectiveness of these tools individually, compare their performance against each other, and assess their results relative to prior research. We conducted a diagnostic accuracy test on 83 Egyptian patients referred to Alexandria University Children's Hospital for potential PCD diagnosis between January 2015 and December 2022. The scores obtained from the screening tools were calculated and assessed. Of the initial group, 10 patients were ruled out because they fit other diagnostic parameters. Forty-three cases received a confirmed diagnosis, while 30 did not. Notably, the confirmed cases consistently scored higher on our screening tools than those that remained unconfirmed (p <.001, for all tested scores). We used receiver operating characteristic curves to assess and compare the effectiveness of each tool. The NA-CDCF had the smallest area under curve 0.736 (95% confiedence interval 0.619-0.832); in contrast, the CI score had the largest 0.898 (95% confidence interval 0.808-0.957). All the tools tested were effective in identifying suitable patients for PCD testing at statistically significant levels. However, the PICADAR and NA-CDCF scores' performance did not significantly differ in the current study. The CI and CInew13 scores, on the other hand, outperformed both.

Immunological Assessment of Key Biomarkers in Stage III Breast Cancer

Objective: To investigate the predictive role of some immune parameters in progressive and diagnostic of stage III breast cancer BC patient. Methods: The study was conducted at Specialized Oncology Center – Tikrit City, and the Oncology of Baghdad Teaching Hospital, Baghdad city, Iraq, on 80 blood samples, 50 samples from women with stage III breast cancer, and 30 samples for control group (healthy women), the age range (25–50) year. The collect serum assessed by ELIZA, and the data analyzed by Independent-Samples T test spss. While AUC is measured by MedCalc. Results: Serum levels of all parameters were dramatically higher in patients group compared to control except in IL-23 which exhibitedslight elevation statically not significant. The (AUC) for the associated ROC curve of CA15-3 (1), TGF-β (1) and IL-10 (1) were the largest.AUC is valuable diagnostic parameters to predict of progressive and diagnostic of the disease, followed by TNF-α (0.997), IL-6 (0.974), IL-17 (0.890), IL-8 (0.838), CTL-4 (0.819) and finally the lowest on was IL-23 (0.616). Conclusion: Increasing levels of the measured parameters are an essential predictor of progressive and diagnostic of the disease.

The Performance of GeneXpert in the Diagnosis of Lymph Node Tuberculosis: A Prospective Study Comparing GeneXpert and Culture Findings.

Background and objective Lymph node tuberculosis (LNTB) is a common manifestation of extrapulmonary tuberculosis (EPTB). GeneXpert is a rapid diagnostic molecular test that simultaneously detects tuberculosis and rifampicin (RIF) resistance. In this study, we aimed to assess the epidemiology of LNTB and diagnostic performance parameters of the GeneXpert in routineENT practice. Methods We conducted a cross-sectional prospective study from January to July 2019,in the Department of Otorhinolaryngology and Head Neck Surgery at the Hassan II University Hospital Center of Fez, Morocco. The samples were collected using lymph node biopsy and subjected to GeneXpert assay, culture, and histopathology. Diagnostic performance parameters of the GeneXpert were calculated and compared with culture. Results All patients with cervical adenopathy were included. Lymph node biopsies were performed for all patients. The performance of the GeneXpert was assessed according to culture findings. Among the 75 cases, the mean age was 21.6 ± 12.7 years with a female predominance (60%). GeneXpert was positive in 66.7% of specimens. The sensitivity and specificity of the GeneXpert assay were 78.6% and 40.4% respectively. GeneXpert accuracy was 54.6%. The positive predictive value (PPV) and negative predictive value (NPV) were found to be 44% (95% CI: 30.2-57.8) and 76% (95% CI: 59.3-92.7) respectively. Mycobacterium bovis was isolated in all samples, with no case of resistance to RIF found. Conclusions The performance of GeneXpert was found to be superior in terms of establishing the diagnosis of LNTB. It offers speedy and prompt results and clinicians should adopt it in routine clinical practice.