Publications by authors named "Lazic I"

Article Synopsis
  • - This study assesses how well four machine learning algorithms can classify physiological stress using heart rate variability (HRV) and pulse rate variability (PRV), comparing two feature selection methods: automatic using Akaike's criterion and a physiological-based method.
  • - Data were gathered from 127 healthy individuals under various stress conditions, revealing that while it's feasible to classify stress, differentiating between postural and mental stress is still challenging; the classifiers performed similarly, with automatic feature selection showing a slight edge.
  • - The findings suggest that both HRV and PRV features are valuable for stress classification, which could enhance stress assessment techniques in clinical and everyday settings, thus promoting better well-being evaluation.
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Delayed cerebral ischemia is a major neurological complication of aneurysmal subarachnoid hemorrhage. Its unpredictable course and potentially unfavorable outcome draw attention to clinicians to improve the methods for its prediction, prevention, and diagnosis. The computed tomography perfusion (CTP) technique of the brain is one of the promising methods for revealing brain areas endangered by cerebral vasospasm and delayed cerebral ischemia.

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The increasing availability of time series data depicting the evolution of physical system properties has prompted the development of methods focused on extracting insights into the system behavior over time, discerning whether it stems from deterministic or stochastic dynamical systems. Surrogate data testing plays a crucial role in this process by facilitating robust statistical assessments. This ensures that the observed results are not mere occurrences by chance, but genuinely reflect the inherent characteristics of the underlying system.

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Objective: This research aimed to determine whether an adequate surgical approach can be chosen based on clearly defined values of anatomical landmarks (tentorial angle) and tumor size and extension.

Methods: We conducted a retrospective analysis of patients operated on because of pineal tumors. The cohort was divided depending on the surgical approach.

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Background: High-Flow Nasal Cannula (HFNC) oxygen therapy emerged as the therapy of choice in COVID-19-related pneumonia and moderate to severe acute hypoxemic respiratory failure (AHRF). HFNC oxygen therapy in COVID-19 has been recommended based its use to treat AHRF of other etiologies, and studies on assessing outcomes in COVID-19 patients are highly needed. This study aimed to examine outcomes in COVID-19 patients with pneumonia and severe AHRF treated with HFNC.

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Background/aim: Synovial calprotectin has been demonstrated as a promising biomarker for periprosthetic joint infections (PJI) in painful total hip (THA) and knee arthroplasties (TKA). However, its diagnostic utility has not been evaluated explicitly in cases with marked loosening or migration of the implant. Concerns have already been raised in cases with metallosis and severe periprosthetic osteolysis because wear-induced inflammation may yield false positive results.

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Purpose: Robotic arm-assisted total knee arthroplasty (raTKA), currently a major trend in knee arthroplasty, aims to improve the accuracy of implant positioning and limb alignment. However, it is unclear whether and to what extent manual radiographic and navigation measurements with the MAKO™ system correlate. Nonetheless, a high agreement would be crucial to reliably achieve the desired limb alignment.

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Objective: Risk factors for epilepsy in meningioma patients are not yet clearly defined, however, seizure freedom is a significant factor for quality of life after surgery.

Methods: We performed a retrospective study of the 333 adult patients who received surgery for supratentorial meningioma at our center. Various clinical, radiological, and surgical variables were included in the multivariate regression, and the outcomes measured were the occurrence of seizure(s) preoperatively, during the hospitalization, and during the follow-up period.

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Purpose: The diagnostic criteria of prosthetic joint infection (PJI) recommended by the most commonly used diagnostic algorithms can be obscured or distorted by other inflammatory processes or aseptic pathology. Furthermore, the most reliable diagnostic criteria are garnered during revision surgery. A robust, reliable addition to the preoperative diagnostic cascade is warranted.

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The diagnosis of periprosthetic joint infection (PJI) requires a combination of various clinical, laboratory, microbiological and histopathological parameters. A concomitant periprosthetic fracture (PPF) further complicates the diagnosis as it causes a confounding local inflammatory response. Synovial calprotectin has been demonstrated as a promising biomarker of PJI.

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In electron cryomicroscopy (cryo-EM), molecular images of vitrified biological samples are obtained by conventional transmission microscopy (CTEM) using large underfocuses and subsequently computationally combined into a high-resolution three-dimensional structure. Here, we apply scanning transmission electron microscopy (STEM) using the integrated differential phase contrast mode also known as iDPC-STEM to two cryo-EM test specimens, keyhole limpet hemocyanin (KLH) and tobacco mosaic virus (TMV). The micrographs show complete contrast transfer to high resolution and enable the cryo-EM structure determination for KLH at 6.

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Coronavirus disease (COVID-19) in immunocompromised patients represents a major challenge for diagnostics, surveillance, and treatment. Some individuals remain SARS-CoV-2 PCR-positive for a prolonged period. The clinical and epidemiological significance of this phenomenon is not well understood.

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Background: In revision total knee arthroplasty, zonal fixation methods with a combination of augments, press-fit stems, and sleeves are popular. We hypothesized that high distal femoral augmentation with diaphyseal press-fit stems leads to an increased rate of early aseptic loosening and that femoral metaphyseal sleeves improve implant survival. Therefore, we retrospectively investigated implant survival in relation to augment heights and sleeves.

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Single-molecule imaging with atomic resolution is a notable method to study various molecular behaviours and interactions. Although low-dose electron microscopy has been proved effective in observing small molecules, it has not yet helped us achieve an atomic understanding of the basic physics and chemistry of single molecules in porous materials, such as zeolites. The configurations of small molecules interacting with acid sites determine the wide applications of zeolites in catalysis, adsorption, gas separation and energy storage.

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Purpose: Diagnosing periprosthetic joint infections (PJI) are challenging and may be hampered by the presence of other causes of local inflammation. Conventional synovial and serum markers are not reliable under these circumstances. Synovial calprotectin has been recently shown as a promising biomarker for PJI in total hip (THA) and total knee arthroplasty (TKA).

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Background: Machine Learning (ML) in arthroplasty is becoming more popular, as it is perfectly suited for prediction models. However, results have been heterogeneous so far. We hypothesize that an accurate ML model for outcome prediction in THA must be able to compute arthroplasty-specific data.

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Purpose: The number of primary total knee arthroplasties (TKA) is expected to rise constantly. For patients and healthcare providers, the early identification of risk factors therefore becomes increasingly fundamental in the context of precision medicine. Others have already investigated the detection of risk factors by conducting literature reviews and applying conventional statistical methods.

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Vascular graft infections (VGI) are severe complications in prosthetic vascular surgery with an incidence ranging from 1 to 6%. In these cases, synthetic grafts are commonly used in combination with antimicrobial agents. Expanded polytetrafluoroethylene (ePTFE) is in clinical use as a synthetic graft material and shows promising results by influencing bacterial adhesion.

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Background/aim: Increasing economic pressure in modern healthcare necessitates an increase in efficiency in total knee arthroplasty (TKA) while maintaining high-quality outcomes. Removal of debris using pulsatile lavage (PL) during cement polymerization may considerably reduce the operative duration. However, water can penetrate the interface, resulting in impaired implant fixation.

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Scanning transmission electron microscopy (STEM) is a powerful imaging technique and has been widely used in current material science research. The attempts of applying STEM (annual dark field (ADF)-STEM or annular bright field (ABF)-STEM) into biological research have been going on for decades while applications have still been limited because of the existing bottlenecks in dose efficiency and non-linearity in contrast. Recently, integrated differential phase contrast (iDPC) STEM technique emerged and achieved a linear phase contrast imaging condition, while resolving signals of light elements next to heavy ones even at low electron dose.

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Purpose: Artificial intelligence (AI) in healthcare is rapidly growing and offers novel options of data analysis. Machine learning (ML) represents a distinct application of AI, which is capable of generating predictions and has already been tested in different medical specialties with various approaches such as diagnostic applications, cost predictions or identification of risk factors. In orthopaedics, this technology has only recently been introduced and the literature on ML in knee arthroplasty is scarce.

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Background/aim: The aim of the study was to analyze operative time and restoration of hip biomechanics in total hip arthroplasty (THA) via direct anterior approach (DAA) with and without the use of a traction table.

Patients And Methods: We retrospectively compared 97 cases where a traction table was used to 92 cases without a table. Ninety-seven patients received THA with a traction table (AMIS technique) and 92 patients with conventional DAA.

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