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      Derivation and validation of an accurate estimation of CD4 counts from the absolute lymphocyte count in virologically suppressed and immunologically reconstituted HIV infected adults

      research-article
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      BMC Infectious Diseases
      BioMed Central

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          Abstract

          Background

          A simple method to estimate CD4 counts in stable, HIV infected virologically-suppressed and immune-reconstituted adults could save the expense of unnecessary formal testing.

          Methods

          Using a baseline CD4 percent, CD4 counts were estimated from subsequent absolute lymphocyte counts (ALC) measured by an automated FBC machine (CD4 estimate calculated by the ALC multiplied by the baseline CD4 percent). The accuracy of this approach was established in a large, retrospective clinical laboratory dataset of virologically-suppressed HIV infected subjects. A case–control study explored important clinical factors for accurate estimates, and a heuristic algorithm was derived and validated in a random sample.

          Results

          Data from 3,630 subjects were available. CD4 counts were generally accurately estimated, with a mean 6.1 % underestimation. Overall 83.3 % of CD4 estimates were within 25 % of the actual values, with 12.1 % CD4 counts underestimated by more than 25 %, and 4.5 % overestimated. The CD4 count was increasingly underestimated with time from baseline, and the degree of underestimation correlated with baseline CD4 percent (p < 0.0001). From the case–control study, baseline CD4 percent of ≥20, no illness requiring hospitalization and more than a year since starting or switch of anti-retroviral therapy were identified as significant predictors of inaccurate estimates. Employing this simple algorithm, CD4 estimate accuracy improved to a mean 1.3 % underestimation, and the proportion of estimates within 25 % of the actual value increased to 93.4 %.

          Conclusions

          In virologically-suppressed and immune-reconstituted HIV-infected adults, the CD4 count can be accurately estimated from the ALC using a baseline CD4 percent for at least 2 years after measurement.

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          Most cited references7

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          Sources of variability in repeated T-helper lymphocyte counts from human immunodeficiency virus type 1-infected patients: total lymphocyte count fluctuations and diurnal cycle are important.

          The study objective was to determine the causes and magnitude of absolute CD4 (T4) count variation in human immunodeficiency virus type 1 (HIV-1)-infected (+) adult males. We conducted a prospective, blinded, and controlled study of 22 adult military male outpatients, including 16 HIV(+) [12 in Walter Reed stage (WR-) 1 through 5, 4 in WR-6 (AIDS)], and 6 HIV seronegative (-) healthy controls. Ten CD4+ cell counts were drawn within a 3-day interval from each patient at the following times: 0800, 1200, 1600, and 2200 h on day 1; and 0800, 1200, and 1600 h on days 2 and 3. A significant CD4+ cell count diurnal increase of 59 cells/mm3 was detected between 0800 h and 2200 h from the WR-1-5 patients (p = 0.018), although this diurnal change was significantly blunted (p = 0.028) as compared with the 506 cells/mm3 CD4+ cell count diurnal increase observed from the HIV(-) healthy controls. The coefficients of variation [CV = (standard deviation/average) x 100] of the three daily 0800 h CD4 cell counts from each patient were 15 (median) and 19 (average) for the WR-1-5 patient group. Blood leukocyte counts, differential fractions of lymphocytes, and total lymphocyte counts contributed more to the observed CD4+ cell count variability than did the CD4% measurements [CV = 7.5 (median), 11 (average)] obtained from flow cytometry. We conclude that the large fluctuations that we observed in repeated CD4+ cell counts in HIV(+) patients can be explained in part by CD4+ cell count diurnal cycle and in part by high variability in total lymphocyte counts.(ABSTRACT TRUNCATED AT 250 WORDS)
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            Risk factors and time-trends of cytomegalovirus (CMV), syphilis, toxoplasmosis and viral hepatitis infection and seroprevalence in human immunodeficiency virus (HIV) infected patients.

            Chronic bacterial, viral and parasitic infections contribute to the morbidity and mortality associated with human immunodeficiency virus (HIV) infection. This study investigated risk factors and time-trends of the seroprevalence of cytomegalovirus (CMV), toxoplasmosis and hepatitis A total antibody; and co-infection with syphilis, hepatitis B and hepatitis C among newly diagnosed HIV individuals in Singapore.
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              Quantification of the variation due to laboratory and physiologic sources in CD4 lymphocyte counts of clinically stable HIV-infected individuals.

              We have conducted a study to quantify the amount of variation in the CD4 lymphocyte counts of HIV-infected individuals due to laboratory and physiological factors. Thirty HIV-infected male volunteers had blood drawn on six occasions: three times in each of 2 weeks, 4 weeks apart. Two tubes of blood were drawn at each visit, and duplicate measurements were obtained from one of the tubes of blood. Differences between duplicate measurements from a single tube of blood and between CD4 counts obtained from two tubes of blood drawn on the same day were attributed to laboratory factors. Differences between CD4 counts obtained on different days were attributed to a combination of laboratory factors and physiologic factors, which included the effects of exercise, tobacco, and the consumption of alcohol and caffeine. The mean absolute CD4 count at the first visit was 450 (range 86-1,081). The short-term coefficient of variation of CD4 count was 13.7 (95% CI: 12.9, 14.6). Physiologic and laboratory factors accounted for 85% and 15% of the variation in CD4 counts, respectively. Variation in the absolute white blood cell count, lymphocyte percentage, and CD4 percentage accounted fo 52%, 29%, and 19% of the physiologic variation in CD4 counts, respectively. Our results confirm a high degree of short-term variability of CD4 counts among HIV-infected individuals, which can be largely attributed to physiological factors. This variability can be minimized more effectively by repeating CD4 counts over time than by repeating measurements at a single visit.(ABSTRACT TRUNCATED AT 250 WORDS)
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                Author and article information

                Contributors
                +65 8133 4132 , Barnaby_young@ttsh.com.sg
                Oon_tek_ng@ttsh.com.sg
                David_lye@ttsh.com.sg
                Yee_sin_leo@ttsh.com.sg
                Journal
                BMC Infect Dis
                BMC Infect. Dis
                BMC Infectious Diseases
                BioMed Central (London )
                1471-2334
                13 August 2015
                13 August 2015
                2015
                : 15
                : 330
                Affiliations
                [ ]Institute of Infectious Diseases and Epidemiology, , Tan Tock Seng Hospital, Singapore, Singapore
                [ ]Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
                [ ]Yong Yoo Lin School of Medicine, National University of Singapore, Singapore, Singapore
                Article
                1079
                10.1186/s12879-015-1079-5
                4535254
                f6dd5721-548e-414e-b76c-a72ef5d2dc97
                © Young et al. 2015

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 14 May 2015
                : 3 August 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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