The value of battery testing in the clinical laboratory: A PERT network case study

1984 ◽  
Vol 8 (4) ◽  
pp. 239-247
Author(s):  
N. K. Kwak ◽  
John J. Vargo ◽  
Marc J. Schniederjans
Keyword(s):  
2021 ◽  
Vol 5 (1) ◽  
pp. 89-92
Author(s):  
Z. P. Lemeshevskaya ◽  
◽  
M. V. Pavlukevich ◽  
N. I. Procopchik ◽  
◽  
...  

Background. COVID-19 infection keeps changing our understanding of its clinical course when associated with various somatic diseases. Objective. To present a clinical case of a patient with non-specific ulcerative colitis (NUC) and COVID-19 infection. Material and methods: medical documentation, general clinical, laboratory and instrumental data as well as histological examination of bioptates stained with hematoxylin and eosin that were obtained during colonoscopy. Results. The article presents a case history of a patient with manifestations of severe total NUC developed in association with the subclinical form of COVID-19 infection, the former being the cause of death in concomitant pathology. Conclusions. This clinical case describes a variant of an unfavorable outcome of NUC, one of the reasons for the manifestation of which was the atypical form of COVID-19 infection, which became a trigger for an autoimmune inflammatory process in the intestine. The accumulation of new knowledge about the features of the pathogenesis and manifestations of both pathologies will make it possible to improve the effectiveness of treatment and predict the course and outcomes of combined pathology.


2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S934-S934
Author(s):  
David Stupplebeen ◽  
Tetine L Sentell ◽  
Lance Ching ◽  
Blythe Nett ◽  
Hermina Taylor ◽  
...  

Abstract An estimated one-quarter of United States’ older adults (≥65 years) have diabetes (DM) while half have prediabetes (PreDM). Timely diagnosis can prevent disease progression, but significant proportions of PreDM/DM are undiagnosed. Among Hawai‘i adults, one-third of diabetes and two-thirds of prediabetes cases are undiagnosed; rates for older adults are unknown. Algorithms integrated into Electronic Medical Records (EMR) may improve care by identifying probable undiagnosed cases in patient panels using clinical/laboratory measures. We assessed one algorithm developed by the Hawai‘i Department of Health that identified individuals overdue for screening or with Pre/DM using the records of 20,362 adult patients (51.33% were >65) from a major state health system. 6,371 (31.3%) patients were excluded from analysis; they had no HbA1c screening in the past year or were overdue for screening (70%) based on standard guidelines. Of the remaining 13,991 patients, 7317 were older adults; 6130 (84%) had a PreDM (50.6%) or DM (33.2%) HbA1c value; the rest were controlled or false-positive. Of those older adults with probable PreDM/DM, 38.6% were undiagnosed. Adults >65 were significantly more likely to be flagged with undiagnosed PreDM compared to their younger counterparts (58 versus 54%, p<.001). Notably, 61% of older men flagged with PreDM were undiagnosed. Of the 5,737 patients identified with DM, 22% of those 65 were undiagnosed. Given the recognized high burden of diabetes among older adults, results indicate substantial missed opportunities for the prevention and early treatment of this condition as identified by an EMR algorithm.


2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Claudia Archetti ◽  
Alessandro Montanelli ◽  
Dario Finazzi ◽  
Luigi Caimi ◽  
Emirena Garrafa

<em>Background</em>. This paper presents a case study of an automated clinical laboratory in a large urban academic teaching hospital in the North of Italy, the Spedali Civili in Brescia, where four laboratories were merged in a unique laboratory through the introduction of laboratory automation. <br /><em>Materials and Methods</em>. The analysis compares the preautomation situation and the new setting from a cost perspective, by considering direct and indirect costs. It also presents an analysis of the turnaround time (TAT). The study considers equipment, staff and indirect costs. <br /><em>Results</em>. The introduction of automation led to a slight increase in equipment costs which is highly compensated by a remarkable decrease in staff costs. Consequently, total costs decreased by 12.55%. The analysis of the TAT shows an improvement of nonemergency exams while emergency exams are still validated within the maximum time imposed by the hospital. <br /><em>Conclusions</em>. The strategy adopted by the management, which was based on re-using the available equipment and staff when merging the pre-existing laboratories, has reached its goal: introducing automation while minimizing the costs.


1997 ◽  
Vol 43 (9) ◽  
pp. 1610-1617 ◽  
Author(s):  
Sharon S Ehrmeyer ◽  
Ronald H Laessig

Abstract The CLIA’88 classified all clinical laboratory testing as waived, moderate, or high complexity. The eight original waived tests were characterized as simple, accurate, error-free, risk-free, and suitable for home use by nonlaboratory professionals. The subjective nature of the classification process was challenged immediately. The Clinical Laboratory Improvement Advisory Committee asked the CDC and the Health Care Financing Administration to develop objective criteria that included assessment of performance by field-test and in-house data. We examined the efficacy of the CDC protocol with empirical data from the HemoCue B-Hemoglobin Test System® submission, to assess operator competency, intra-/interoperator and between-site imprecision, and accuracy. Non-laboratory-trained operators demonstrated 2–3% imprecision (40–200 g/L). Accuracy studies yielded a slope of 1.01, an intercept of 3.53 g/L, and r of 1.00 (52–230 g/L). Results met the protocol’s Tonks’ criterion for imprecision (less than one-fourth of the reference range).


2018 ◽  
Vol 53 ◽  
pp. 164-167 ◽  
Author(s):  
Jan Palaty ◽  
Danijela Konforte ◽  
Theano Karakosta ◽  
Ernest Wong ◽  
Cristiana Stefan

10.19082/4077 ◽  
2017 ◽  
Vol 9 (4) ◽  
pp. 4077-4083 ◽  
Author(s):  
Ali Mouseli ◽  
Mohsen Barouni ◽  
Mohammadreza Amiresmaili ◽  
Siamak Mirab Samiee ◽  
Leila Vali

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