Introduction: Plasma amino acids profiling can aid in the screening and diagnosis of aminoacidopathies. The goal of the current study was to analyze and report the metabolic profiles of plasma amino acid (PAA) and additionally to compare PAA-reference intervals (RI) from Pakistan with more countries utilizing Clinical Laboratory Integrated Reports (CLIR).
Methods: This was a cross sectional prospective single center study. Twenty-two amino acids were analyzed in each sample received for one year at the clinical laboratory Data was divided into reference and case data files after interpretation by a team of pathologists and technologists. All PAA samples were analyzed using ion-exchange high-performance chromatography. The CLIR application of Amino Acid in Plasma (AAQP) was used for statistical analysis for both data sets and post-analytical interpretive tools using a single condition tool was applied.
Result: The majority of 92% (n = 1913) of PAA profiles out of the total 2081 tests run were non-diagnostic; the PAA values were within the age-specific RI. The PAA median was in close comparison close to the 50th percentile of reference data available in CLIR software. Out of the total 2081 tests run, one hundred and sixty-eight had abnormal PAA levels; 27.38% were labeled as non-fasting samples, and the main aminoacidopathies identified were Phenylketonuria and Maple Syrup Urine Disorder.
Conclusion: An agreement of >95% was observed between the reporting done by the pathologists and technologists' team and then after the application of CLIR. Augmented artificial intelligence using CLIR can improve the accuracy of reporting rare aminoacidopathies in a developing country like ours.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577660 | PMC |
http://dx.doi.org/10.1016/j.amsu.2022.104651 | DOI Listing |
Acad Radiol
December 2024
Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.); Division of Medical Physics, University of Florida College of Medicine, Gainesville, FL (R.F.); Department of Neurology, Division of Movement Disorders, University of Florida College of Medicine, Gainesville, FL (R.F.); Department of Otolaryngology - Head and Neck Surgery, McGill University, Montreal, Quebec, Canada (R.F.); Department of Radiology, AdventHealth Medical Group, Maitland, FL (R.F.). Electronic address:
Rationale And Objectives: To evaluate and compare image quality of different energy levels of virtual monochromatic images (VMIs) using standard versus strong deep learning spectral reconstruction (DLSR) on dual-energy CT pulmonary angiogram (DECT-PA).
Materials And Methods: A retrospective study was performed on 70 patients who underwent DECT-PA (15 PE present; 55 PE absent) scans. VMIs were reconstructed at different energy levels ranging from 35 to 200 keV using standard and strong levels with deep learning spectral reconstruction.
Oral Maxillofac Surg
December 2024
Department of Oral Implantology, Osaka Dental University, 8-1 Kuzuhahanazonocho, Hirakata, 573-1121, Osaka, Japan.
Background: The pre-extraction overbuilding procedure was designed aiming to mitigate buccal bone resorption following tooth extraction. The objective of this study was to compare the efficacy of pre-extraction and juxta-extraction buccal overbuilding treatments in preserving buccal bone volume following tooth extraction.
Material And Methods: At the test sites (pre-extraction sites), an alveolar crest overbuilding was performed on the buccal aspect of the distal root of the fourth premolar using a xenograft covered with a collagen membrane.
Sci Rep
December 2024
ETH Zurich, Zurich, Switzerland.
Artificial intelligence (AI) provides considerable opportunities to assist human work. However, one crucial challenge of human-AI collaboration is that many AI algorithms operate in a black-box manner where the way how the AI makes predictions remains opaque. This makes it difficult for humans to validate a prediction made by AI against their own domain knowledge.
View Article and Find Full Text PDFAcad Radiol
December 2024
Department of Otorhinolaryngology, Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China (Y.W., P.Y., J.W., Z.Z., G.W., Y.Z., Y.Y., Y.M., X.S.); Shandong Provincial Clinical Research Center for Otorhinolaryngologic Diseases, Yantai Yuhuangding Hospital, Yantai, China (Y.W., P.Y., J.W., Z.Z., G.W., Y.Z., Y.Y., Y.M., X.S.); Yantai Key Laboratory of Otorhinolaryngologic Diseases, Yantai Yuhuangding Hospital, Yantai, China (Y.W., P.Y., J.W., Y.Z., Y.Y., Y.M., X.S.). Electronic address:
Rationale And Objectives: Nasal polyps (NP) and inverted papilloma (IP) are benign tumors within the nasal cavity, each necessitating distinct treatment approaches. Herein, we investigate the utility of a deep learning (DL) model for distinguishing between NP and IP.
Materials And Methods: A total of 1791 patients with nasal benign tumors from two hospitals were retrospectively enrolled.
J Med Imaging Radiat Oncol
December 2024
St John of God Subiaco, Perth, Western Australia, Australia.
Uterine leiomyomata, commonly known as fibroids, are prevalent benign tumours affecting a significant percentage of women of reproductive age. Although many patients remain asymptomatic, a substantial proportion experience severe symptoms, including abnormal uterine bleeding and adverse reproductive outcomes. Surgical intervention often becomes necessary for patients with symptomatic fibroids, despite advancements in medical therapies.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!