Characterization of T Lymphocyte Subset Alterations by Flow Cytometry in HIV Disease

1993 ◽  
Vol 677 (1 Clinical Flow) ◽  
pp. 126-137 ◽  
Author(s):  
JANIS V. GIORGI
Keyword(s):  
Flow Cytometry ◽  
T Lymphocyte ◽  
Lymphocyte Subset ◽  
Hiv Disease ◽  
T Lymphocyte Subset

scholarly journals Clinical Prognosis of Patients with Early-Stage Human Immunodeficiency Virus (HIV) Disease: Contribution of HIV-1 RNA and T Lymphocyte Subset Quantitation

2001 ◽  
Vol 166 (7) ◽  
pp. 571-576 ◽  
Author(s):  
◽  
Arthur E. Brown ◽  
Matthew J. Dolan ◽  
Nelson L. Michael ◽  
Susan Zhou ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
T Lymphocyte ◽  
Early Stage ◽  
Lymphocyte Subset ◽  
Hiv Disease ◽  
Clinical Prognosis ◽  
Immunodeficiency Virus ◽  
Hiv 1 ◽  
T Lymphocyte Subset

scholarly journals Isolation and initial characterization of multiple species of T-lymphocyte subset cDNA clones.

1987 ◽  
Vol 84 (9) ◽  
pp. 2896-2900 ◽  
Author(s):  
B. S. Kwon ◽  
G. S. Kim ◽  
M. B. Prystowsky ◽  
D. W. Lancki ◽  
D. E. Sabath ◽  
...  
Keyword(s):  
T Lymphocyte ◽  
Lymphocyte Subset ◽  
Cdna Clones ◽  
Initial Characterization ◽  
Multiple Species ◽  
T Lymphocyte Subset

scholarly journals Characterization of cytotoxic autoantibodies reacting with a cytotoxic/suppressor T-lymphocyte subset in myocarditis

1991 ◽  
Vol 17 (2) ◽  
pp. A381
Author(s):  
Uwe Kühl ◽  
Inge Pfeiffer ◽  
Heinz-Petter Schultheiβ ◽  
Bodo Eckehard Strauer
Keyword(s):  
T Lymphocyte ◽  
Lymphocyte Subset ◽  
Suppressor T Lymphocyte ◽  
T Lymphocyte Subset

The development of autoverification system of lymphocyte subset assays on the flow cytometry platform

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jue Shi ◽  
Run-Qing Mu ◽  
Pan Wang ◽  
Wen-Qing Geng ◽  
Yong-Jun Jiang ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
T Lymphocyte ◽  
Historical Data ◽  
Turnaround Time ◽  
Limited Range ◽  
Lymphocyte Subset ◽  
Test Validation ◽  
Online Test ◽  
Passing Rate ◽  
T Lymphocyte Subset

Abstract Objectives Peripheral blood lymphocyte subsets are important parameters for monitoring immune status; however, lymphocyte subset detection is time-consuming and error-prone. This study aimed to explore a highly efficient and clinically useful autoverification system for lymphocyte subset assays performed on the flow cytometry platform. Methods A total of 94,402 lymphocyte subset test results were collected. To establish the limited-range rules, 80,427 results were first used (69,135 T lymphocyte subset tests and 11,292 NK, B, T lymphocyte tests), of which 15,000 T lymphocyte subset tests from human immunodeficiency virus (HIV) infected patients were used to set customized limited-range rules for HIV infected patients. Subsequently, 13,975 results were used for historical data validation and online test validation. Results Three key autoverification rules were established, including limited-range, delta-check, and logical rules. Guidelines for addressing the issues that trigger these rules were summarized. The historical data during the validation phase showed that the total autoverification passing rate of lymphocyte subset assays was 69.65% (6,941/9,966), with a 67.93% (5,268/7,755) passing rate for T lymphocyte subset tests and 75.67% (1,673/2,211) for NK, B, T lymphocyte tests. For online test validation, the total autoverification passing rate was 75.26% (3,017/4,009), with 73.23% (2,191/2,992) for the T lymphocyte subset test and 81.22% (826/1,017) for the NK, B, T lymphocyte test. The turnaround time (TAT) was reduced from 228 to 167 min using the autoverification system. Conclusions The autoverification system based on the laboratory information system for lymphocyte subset assays reduced TAT and the number of error reports and helped in the identification of abnormal cell populations that may offer clues for clinical interventions.

scholarly journals Baseline T-lymphocyte subset absolute counts can predict both outcome and severity in SARS-CoV-2 infected patients: a single center study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marco Iannetta ◽  
Francesco Buccisano ◽  
Daniela Fraboni ◽  
Vincenzo Malagnino ◽  
Laura Campogiani ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
T Lymphocyte ◽  
Lymphocyte Subsets ◽  
Severe Disease ◽  
Laboratory Data ◽  
Lymphocyte Subset ◽  
Multivariable Logistic Regression Analysis ◽  
Double Positive ◽  
Increased Risk ◽  
T Lymphocyte Subset

AbstractThe aim of this study was to evaluate the role of baseline lymphocyte subset counts in predicting the outcome and severity of COVID-19 patients. Hospitalized patients confirmed to be infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) were included and classified according to in-hospital mortality (survivors/nonsurvivors) and the maximal oxygen support/ventilation supply required (nonsevere/severe). Demographics, clinical and laboratory data, and peripheral blood lymphocyte subsets were retrospectively analyzed. Overall, 160 patients were retrospectively included in the study. T-lymphocyte subset (total CD3+, CD3+ CD4+, CD3+ CD8+, CD3+ CD4+ CD8+ double positive [DP] and CD3+ CD4− CD8− double negative [DN]) absolute counts were decreased in nonsurvivors and in patients with severe disease compared to survivors and nonsevere patients (p < 0.001). Multivariable logistic regression analysis showed that absolute counts of CD3+ T-lymphocytes < 524 cells/µl, CD3+ CD4+ < 369 cells/µl, and the number of T-lymphocyte subsets below the cutoff (T-lymphocyte subset index [TLSI]) were independent predictors of in-hospital mortality. Baseline T-lymphocyte subset counts and TLSI were also predictive of disease severity (CD3+  < 733 cells/µl; CD3+ CD4+ < 426 cells/µl; CD3+ CD8+ < 262 cells/µl; CD3+ DP < 4.5 cells/µl; CD3+ DN < 18.5 cells/µl). The evaluation of peripheral T-lymphocyte absolute counts in the early stages of COVID-19 might represent a useful tool for identifying patients at increased risk of unfavorable outcomes.

AB0028 The Abnormal CD4+T Lymphocyte Subset Distribution Shown by Naïve Rheumatoid Arthritis Patients Can be Modulated by Methotrexate Treatment

2015 ◽  
Vol 74 (Suppl 2) ◽  
pp. 900.1-900
Author(s):  
C. Bohόrquez ◽  
L. Ruiz ◽  
C. Garcia ◽  
A. Gόmez-La Hoz ◽  
A. Turriόn ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
T Lymphocyte ◽  
Lymphocyte Subset ◽  
Methotrexate Treatment ◽  
Subset Distribution ◽  
T Lymphocyte Subset

T lymphocyte subset abnormalities in peripheral blood from patients with the Guillain-Barré syndrome

1994 ◽  
Vol 53 (2) ◽  
pp. 219-225 ◽  
Author(s):  
Charlotte Dahle ◽  
Magnus Vrethem ◽  
Jan Ernerudh
Keyword(s):  
T Lymphocyte ◽  
Peripheral Blood ◽  
Lymphocyte Subset ◽  
Guillain Barre Syndrome ◽  
Guillain Barré Syndrome ◽  
Guillain Barré ◽  
T Lymphocyte Subset

T cell receptor Vβ repertoire of the antigen specific CD8 T lymphocyte subset of HIV infected children

AIDS ◽  
2002 ◽  
Vol 16 (11) ◽  
pp. 1459-1465 ◽  
Author(s):  
Thomas W. McCloskey ◽  
Viraga Haridas ◽  
Rajendra Pahwa ◽  
Savita Pahwa
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
T Lymphocyte ◽  
Cell Receptor ◽  
Lymphocyte Subset ◽  
Cd8 T Lymphocyte ◽  
T Cell Receptor Vβ ◽  
T Lymphocyte Subset

scholarly journals Clinical usefulness of multivariate autoregressive (AR) modeling as a tool for analyzing T-lymphocyte subset fluctuations

1990 ◽  
Vol 14 ◽  
pp. 610-613 ◽  
Author(s):  
Takao Wada ◽  
Haruyasu Yamada ◽  
Hiroshi Inoue ◽  
Takenobu Iso ◽  
Eiichi Udagawa ◽  
...  
Keyword(s):  
T Lymphocyte ◽  
Lymphocyte Subset ◽  
Clinical Usefulness ◽  
Ar Modeling ◽  
T Lymphocyte Subset ◽  
Multivariate Autoregressive
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