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Background: The South African national HIV program has increased antiretroviral therapy (ART) coverage over the last decade, supported by policy changes allowing for earlier ART initiation. However, many patients still enter care with advanced (<200 cells/µL) and very advanced (<100 cells/µL) HIV disease. We assessed disease progression at entry to care using nationwide laboratory data. Methods: We constructed a national HIV cohort using laboratory records containing HIV RNA loads and CD4 counts from 2004 to 2016 to determine entry into care. We estimated numbers and proportions of adults with the first CD4 count <100 cells/ µL or 100-199 cells/µL. We calculated relative risks of presenting with advanced disease associated with male sex. Results: 8.04 million first CD4 results were identified. From 2005 to 2011, the proportion of patients entering into care with CD4 count <200 cells/µL declined from 46.8% to 35.6%. From 2011 onward, the proportion of patients entering ART with advanced HIV disease has remained relatively unchanged. In 2016, we estimated that of 654 868 patients entering care, 32.9% had advanced HIV disease, and 16.8% had very advanced HIV disease. Men were almost twice as likely as women (23.1% vs 12.6% ) to enter care with very advanced HIV disease. Conclusions: The proportion of patients presenting with advanced HIV disease in South Africa remains consistently high despite ART scale-up, representing a large and avoidable burden of morbidity. Early HIV diagnosis, rapid linkage to ART and approaches to attract men into early ART initiation should be prioritized.
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Efeitos Psicossociais da Doença , Infecções por HIV/tratamento farmacológico , Programas Nacionais de Saúde/estatística & dados numéricos , Fármacos Anti-HIV/uso terapêutico , Terapia Antirretroviral de Alta Atividade , Contagem de Linfócito CD4 , Estudos de Coortes , HIV/efeitos dos fármacos , Infecções por HIV/epidemiologia , Humanos , Laboratórios , Masculino , Fatores de Risco , África do Sul/epidemiologia , Carga ViralRESUMO
Background: The National Health Laboratory Service is mandated to deliver cost-effective and efficient diagnostic services across South Africa. Their mandate is achieved by a network of laboratories ranging from centralised national laboratories to distant rural facilities. Objective: This study aimed to establish a model of CD4 reagent utilisation as an independent measure of laboratory efficiency. Methods: The efficiency percentage was defined as finished goods (number of reportable results) over raw materials (number of reagents supplied) for 47 laboratories in nine provinces (both anonymised) for 2019. The efficiency percentage at national and provincial levels was calculated and compared to the optimal efficiency percentage derived using pre-set assumptions. Comparative laboratory analysis was conducted for the provinces with the best and worst efficiency percentages. The possible linear relationship between the efficiency percentage and call-outs, days lost, referrals, and turn-around time was assessed. Results: Data are reported for 2 806 799 CD4 tests, with an overall efficiency percentage of 84.5% (optimal of 84.98%). The efficiency percentage varied between 75.7% and 87.7% between provinces, while within the laboratory it ranged from 66.1% to 111.5%. Four laboratories reported an efficiency percentage ranging from 67.8% to 85.7%. No linear correlation was noted between the efficiency percentage, call-outs, days lost, and turn-around time performance. Conclusion: Reagent efficiency percentage distinguished laboratories into different utilisation levels irrespective of their CD4 service level. This parameter is an additional independent indicator of laboratory performance, with no relationship with any contributing factors tested, that can be implemented across pathology disciplines for monitoring reagent utilisation. What this study adds: This study provides an objective methodology to assess reagent utilisation as an independent measure of laboratory efficiency. This model could be applied to all routine pathology services.
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Background: South Africa has the largest HIV epidemic globally, with ~7.5 million people living with HIV in 2021. Adolescent girls (AG) and young women (YW), aged 15-19 years and 20-24 years, are twice as likely to be living with HIV as their male counterparts. The national HIV prevalence for young women was 9.1% (2021), with limited data on disease severity. Objectives: This study assessed very advanced HIV disease (CD4 < 100 cells/µL) in adolescent girls and young women (AGYW) in South Africa. Method: A retrospective descriptive study analysed data collated from the National Health Laboratory Service database for 2017 to 2021 calendar years for AGYW. National and provincial specimen volumes, the percentage of tests with a CD4 < 100 cells/µL and ≥ 100 cells/µL, and the median and interquartile ranges, were calculated. Logistic regression determined the odds ratio for a CD4 < 100 cells/µL, controlling for age category. Results: Data for 1 199 010 CD4 specimens indicated a significant decrease in volumes of 34% from 287 410 (2017) to 189 533 (2021). The percentage of samples with a count < 100 cells/µL ranged from 4.9% to 5.2% for YW versus 5.6% to 6.1% for AG. Provincial data for a CD4 count < 100 cells/µL ranged between 4.5% and 8.3% in AG and 3.6% to 6.3% for YW. Logistic regression indicated a 24% higher likelihood for AG having a CD4 count < 100 cells/µL. Conclusion: The study reported a higher proportion of very advanced HIV disease for AG versus YW nationally, with provincial disparity needing further analysis.
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Background: Flow cytometric immunophenotyping is well established for the diagnosis of haematological neoplasms. New commercially available systems offer fixed, pre-aliquoted multi-parameter analysis to simplify sample preparation and standardise data analysis. Objective: The Beckman Coulter (BC) ClearLLab™ 10C (4-tube) system was evaluated against an existing laboratory developed test (LDT). Methods: Peripheral blood and bone marrow aspirates (n = 101), tested between August 2019 and November 2019 at an academic pathology laboratory in Johannesburg, South Africa, were analysed. Following daily instrument quality control, samples were prepared for LDT (using > 20 2-4-colour in-house panels and an extensive liquid monoclonal reagent repertoire) or ClearLLab 10C, and respectively analysed using in-house protocols on a Becton Dickinson FACSCalibur, or manufacturer-directed protocols on a BC Navios. Becton Dickinson Paint-a-Gate or BC Kaluza C software facilitated data interpretation. Diagnostic accuracy (concordance) was established by calculating sensitivity and specificity outcomes. Results: Excellent agreement (clinical diagnostic concordance) with 100% specificity and sensitivity was established between LDT and ClearLLab 10C in 67 patients with a haematological neoplasm and 34 participants with no haematological disease. Similar acceptable diagnostic concordance (97%) was noted when comparing ClearLLab 10C to clinicopathological outcomes. Additionally, the ClearLLab 10C panels, analysed with Kaluza C software, enabled simultaneous discrimination of disease and concurrent background myeloid and lymphoid haematological populations, including assessing stages of maturation or sub-populations. Conclusion: ClearLLab 10C panels provide excellent agreement to existing LDTs and may reliably be used for immunophenotyping of haematological neoplasms, simplifying and standardising sample preparation and data acquisition.
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Background: The National Health Laboratory Service operates a platform of 226 laboratories across South Africa, ranging from highly sophisticated central academic hospitals to distant rural hospitals. The core function of the National Health Laboratory Service is to provide cost-effective and efficient health laboratory services in the public healthcare sector. Objective: This study aimed to assess the comprehensive cost of running a full-service receiving office (RO) at the Charlotte Maxeke Johannesburg Academic Hospital (CMJAH) laboratory. Methods: Top-down costing was conducted, with the cost per registration as the main outcome of interest. The annual equivalent costs (AEC) for the following categories were determined: registration materials, collection materials, staffing, laboratory equipment, building and electricity, and other operating costs. Data for the period from 01 April 2019 to 31 March 2020 were included in the analyses. Results: The AEC was $1 657 483.00 United States dollars (USD) and the cost per registration was $0.766 USD. Staff contributed 59.9% of the total cost per registration, while collection materials contributed 21.4%. The RO core staff (data clerks) contributed 50.8% of the total staffing costs, while messengers and drivers contributed 31.2%. The introduction of order entry at the CMJAH and other primary healthcare facilities reduced the total AEC by 20%. A single order entry application would serve both the CMJAH and primary healthcare facilities - hence we would prefer to not refer to order entries. Conclusion: Providing a comprehensive RO service costs approximately $1.00 USD per registration. The implementation of order entry at the CMJAH would reduce AECs substantially and improve efficiency.
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Background: Commercial multicolour fixed immunophenotyping panels can improve flow cytometric diagnostic immunophenotyping repertoire. Objective: This study validated the commercially available, standardised Beckman Coulter lyophilised DURAClone RE panels to discriminate specific haematolymphoid subtypes. Methods: We compared the diagnostic capability of the DURAClone acute leukaemia B (ALB), chronic leukaemia B (CLB), and plasma cells (PC) panels to the predicate second-line panels in Charlotte Maxeke Johannesburg Academic Hospital, Johannesburg, South Africa, from April to August 2020. Clinical diagnostic concordance between the in-house second-line immunophenotyping (the predicate method) and DURAClone was established. The ALB panels tested for precursor B-cell acute lymphoblastic leukaemia (n = 11) or normal bone marrow haematogones (n = 9); CLB panels established haematolymphoid subtypes of mature B-cell lymphoproliferative disorders (B-LPD) (n = 20), while PC panels detected plasma cell dyscrasias (PCD) (n = 17). Flow cytometer setup and data interpretation to discriminate normal and aberrant immunophenotypes were per manufacturer's instructions. Results: There was 100% clinical diagnostic concordance between the predicate and the test panels for second-line diagnostic investigation of B-ALL (with additional CD56), mature B-LPD (with additional discernment of CD81, ROR-1, CD79b and CD43) and PCD. Conclusion: The DURAClone CLB exceeded the predicate second-line performance, offering extended second-line diagnostic discernment of mature B-LPD subtypes and discernment of CD5+ B-LPD from other non-CD5+ (or CD5-) B-LPD; likewise, the PC panels enabled discovery of PCD. While ALB testing offered no additional diagnostic advantage over existing predicate investigation, CD58 did offer additional information to discern haematogones from B-ALL.
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Background: The Northern Cape is South Africa's largest province with an HIV prevalence of 7.1% versus a 13.5% national prevalence. CD4 testing is provided at three of five National Health Laboratory Service district laboratories, each covering a 250 km precinct radius. Districts without a local service report prolonged CD4 turn-around times (TAT). Objective: This study documented the impact of a new CD4 laboratory in Tshwaragano in the remote John Taolo Gaetsewe district of the Northern Cape, South Africa. Methods: CD4 test volumes and TAT (total, pre-analytical, analytical, and post-analytical) data for the Northern Cape province were extracted for June 2018 to October 2019. The percentage of CD4 results within the stipulated 40-h TAT cut-off and the median and 75th percentiles of all TAT parameters were calculated. Pre-implementation, samples collected at Tshwaragano were referred to Kimberley or Upington, Northern Cape, South Africa. Results: Pre-implementation, 95.4% of samples at Tshwaragano were referred to Kimberley for CD4 testing (36.3% of Kimberley's test volumes). Only 7.5% of Tshwaragano's total samples were referred post-implementation. The Tshwaragano laboratory's CD4 median total TAT decreased from 24.7 h pre-implementation to 12 h post-implementation (p = 0.003), with > 95.0% of results reported within 40 h. The Kimberley laboratory workload decreased by 29.0%, and testing time significantly decreased from 10 h to 4.3 h. Conclusion: The new Tshwaragano CD4 service significantly decreased local TAT. Upgrading existing community laboratories to include CD4 testing can alleviate provincial service load and improve local access, TAT and efficiency in the centralised reference laboratory.
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OBJECTIVES: The objective of our study was to use laboratory data to describe prostate-specific antigen (PSA) testing trends for primary healthcare (PHC) services from a single province. PHC is a basic package of services offered to local communities, serving as the first point of contact within the health system. These services are offered at clinics and community health centres (CHC), the latter providing additional maternity, accident and emergency services. DESIGN: The retrospective descriptive study design was used. METHODS: We analysed national laboratory data between 2006 and 2016 for men ≥30 years in the Gauteng Province. We used the probabilistic matching algorithm to create first-ever PSA cohort. We used the hot-deck imputation to assign missing race group values and the district health information system facility descriptors to identify PHC testing. We reported patient numbers by calendar year, age category and race group as well as descriptive statistics. We used multivariable logistic regression to assess any association for race group and age with a PSA ≥4 µg/L. RESULTS: Between 2006 and 2016, numbers of men tested increased from 1782 to 67 025, respectively, with 186 984/239 506 (78.1%) tests were from clinics. The majority of testing was for men in the 50-59 age category (31.5%) and Black Africans (86.4%). We reported a median of 0.9 µg/L that increased with age. A PSA ≥4 µg/L was reported for 11.7% of men, increasing to 35.5% for the ≥70 age category. The logistic regression reported that the adjusted odds of having a PSA ≥4 µg/L was significantly lower for Indian/Asians, multiracials and whites than for Black Africans (p value<0.0001). CONCLUSIONS: Our study has shown a marked increase in PSA testing from clinics and CHC suggestive of screening for prostate cancer. The approaches reported in this study can be extended for national data.
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Antígeno Prostático Específico , Neoplasias da Próstata , Humanos , Masculino , Gravidez , Atenção Primária à Saúde , Antígeno Prostático Específico/análise , Neoplasias da Próstata/diagnóstico , Estudos Retrospectivos , África do SulRESUMO
INTRODUCTION: A rare entity of a B-cell malignancy with precursor B-cell phenotype and concomitant translocation t(8;14) or variant MYC translocation exists. These cases show clinical, pathological and molecular overlap between precursor B-lymphoblastic leukaemia or lymphoma and Burkitt leukaemia or lymphoma (BLL). CASE PRESENTATION: We report a case from February 2019 at the Charlotte Maxeke Johannesburg Academic Hospital, South Africa, of a 9-month-old infant with a predominantly extracranial soft tissue mass showing extradural extension. There was no involvement of the peripheral blood or bone marrow. Fine needle aspiration and Tru-Cut biopsy of the soft tissue scalp mass showed the tumour to be of precursor B-cell phenotype. Contrastingly, an immunophenotypic assessment revealed a high S-phase fraction and raised concern for BLL. This prompted testing for the translocation t(8;14) by fluorescence in-situ hybridisation analysis, which confirmed this aberration. MANAGEMENT AND OUTCOME: Based on the published experience of other centres, the patient was initiated on a BLL protocol. Despite an excellent clinical response, the patient succumbed to neutropenic sepsis six months after diagnosis. CONCLUSION: Leukaemia or lymphoma with translocation t(8;14) or variant MYC translocation and precursor B-cell phenotype is a rare entity with a varied clinical presentation. This poses a challenge for diagnosis and classification and a clinical dilemma for the choice of treatment.
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OBJECTIVE: Reflex cryptococcal antigen (CrAg) screening of blood specimens with a CD4 count of <100 cells/µL was performed at 45 South African CD4 laboratories using a lateral flow assay (LFA). Our objective was to evaluate the reliability of routine LFA results through comparative interlaboratory testing. METHODS: All CrAg-positive and a selected number of CrAg-negative samples from the CD4 laboratories were retested at paired microbiology laboratories using the same LFA. Samples with discordant results were tested at a reference laboratory, using the LFA (with CrAg titers). RESULTS: During interlaboratory testing, 12,502 samples were retested, with 93 (0.7%) discordant results and a between-laboratory agreement of 99.3% (Cohen's kappa, 0.98). The proportion of retested samples with discordant results ranged from 0.17% to 5.31% per laboratory pair (median 0.28%), with 3 reporting >3% of results as discordant. CONCLUSION: Routine CrAg screening results were reliable, with <1% of samples having discordant results, mainly due to interpretation and transcription errors.
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Cryptococcus , Infecções por HIV , Meningite Criptocócica , Humanos , Meningite Criptocócica/diagnóstico , Meningite Criptocócica/prevenção & controle , África do Sul/epidemiologia , Estudos Retrospectivos , Reprodutibilidade dos Testes , Antígenos de Fungos , Contagem de Linfócito CD4 , Programas de Rastreamento , Reflexo , Infecções por HIV/diagnóstico , Infecções por HIV/epidemiologiaRESUMO
BACKGROUND: Globally, tuberculosis remains a major cause of mortality, with an estimated 1.3 million deaths per annum. The Xpert MTB/RIF assay is used as the initial diagnostic test in the tuberculosis diagnostic algorithm. To extend the national tuberculosis testing programme in South Africa, mobile units fitted with the GeneXpert equipment were introduced to high-burden peri-mining communities. OBJECTIVE: This study sought to assess the cost of mobile testing compared to traditional laboratory-based testing in a peri-mining community setting. METHODS: Actual cost data for mobile and laboratory-based Xpert MTB/RIF testing from 2018 were analysed using a bottom-up ingredients-based approach to establish the annual equivalent cost and the cost per result. Historical cost data were obtained from supplier quotations and the local enterprise resource planning system. Costs were obtained in rand and reported in United States dollars (USD). RESULTS: The mobile units performed 4866 tests with an overall cost per result of $49.16. Staffing accounted for 30.7% of this cost, while reagents and laboratory equipment accounted for 20.7% and 20.8%. The cost per result of traditional laboratory-based testing was $15.44 US dollars (USD). The cost for identifying a tuberculosis-positive result using mobile testing was $439.58 USD per case, compared to $164.95 USD with laboratory-based testing. CONCLUSION: Mobile testing is substantially more expensive than traditional laboratory services but offers benefits for rapid tuberculosis case detection and same-day antiretroviral therapy initiation. Mobile tuberculosis testing should however be reserved for high-burden communities with limited access to laboratory testing where immediate intervention can benefit patient outcomes.
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BACKGROUND: High-level monthly, quarterly and annual turn-around time (TAT) reports are used to assess laboratory performance across the National Health Laboratory Service in South Africa. Individual laboratory performances are masked by aggregate TAT reporting across network of testing facilities. OBJECTIVE: This study investigated weekly TAT reporting to identify laboratory inefficiencies for intervention. METHODS: CD4 TAT data were extracted for 46 laboratories from the corporate data warehouse for the 2016/2017 financial period. The total TAT median, 75th percentile and percentage of samples meeting organisational TAT cut-off (90% within 40 hours) were calculated. Total TAT was reported at national, provincial and laboratory levels. Provincial TAT performance was classified as markedly or moderately poor, satisfactory and good based on the percentage of samples that met the cut-off. The pre-analytical, testing and result review TAT component times were calculated. RESULTS: Median annual TAT was 18.8 h, 75th percentile was 25 h and percentage within cut-off was 92% (n = 3 332 599). Corresponding 75th percentiles of component TAT were 10 h (pre-analytical), 22 h testing and 1.6 h review. Provincial 75th percentile TAT varied from 17.6 h to 34.1 h, with three good (n = 13 laboratories), four satisfactory (n = 24 laboratories) and two poor performers (n = 9 laboratories) provinces. Weekly TAT analysis showed 12/46 laboratories (28.6%) without outlier weeks, 31/46 (73.8%) with 1-10 outlier weeks and 3/46 (6.5%) with more than 10 (highest of 20/52 weeks) outlier weeks. CONCLUSION: Masked TAT under-performances were revealed by weekly TAT analyses, identifying poorly performing laboratories needing immediate intervention; TAT component analyses identified specific areas for improvement.
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BACKGROUND: The South African National Health Laboratory Service provides laboratory services for public sector health facilities, utilising a tiered laboratory model to refer samples for CD4 testing from 255 source laboratories into 43 testing laboratories. OBJECTIVE: The aim of this study was to determine the impact of distance on inter-laboratory referral time for public sector testing in South Africa in 2018. METHODS: A retrospective cross-sectional study design analysed CD4 testing inter-laboratory turn-around time (TAT) data for 2018, that is laboratory-to-laboratory TAT from registration at the source to referral receipt at the testing laboratory. Google Maps was used to calculate inter-laboratory distances and travel times. Distances were categorised into four buckets, with the median and 75th percentile reported. Wilcoxon scores were used to assess significant differences in laboratory-to-laboratory TAT across the four distance categories. RESULTS: CD4 referrals from off-site source laboratories comprised 49% (n = 1 390 510) of national reporting. A positively skewed distribution of laboratory-to-laboratory TAT was noted, with a median travel time of 11 h (interquartile range: 7-17), within the stipulated 12 h target. Inter-laboratory distance categories of less than 100 km, 101-200 km, 201-300 km and more than 300 km (p < 0.0001) had 75th percentiles of 8 h, 17 h, 14 h and 27 h. CONCLUSION: Variability in inter-laboratory TAT was noted for all inter-laboratory distances, especially those exceeding 300 km. The correlation between distance and laboratory-to-laboratory TAT suggests that interventions are required for distant laboratories.
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BACKGROUND: Prostate cancer (PCa) is a leading male neoplasm in South Africa. OBJECTIVE: The aim of our study was to describe PCa using Systemized Nomenclature of Medicine (SNOMED) clinical terms codes, which have the potential to generate more timely data. METHODS: The retrospective study design was used to analyse prostate biopsy data from our laboratories using SNOMED morphology (M) and topography (T) codes where the term 'prostate' was captured in the narrative report. Using M code descriptions, the diagnosis, sub-diagnosis, sub-result and International Classification of Diseases for Oncology (ICD-O-3) codes were assigned using a lookup table. Topography code descriptions identified biopsies of prostatic origin. Lookup tables were prepared using Microsoft Excel and combined with the data extracts using Access. Contingency tables reported M and T codes, diagnosis and sub-diagnosis frequencies. RESULTS: An M and T code was reported for 88% (n = 22 009) of biopsies. Of these, 20 551 (93.37%) were of prostatic origin. A benign diagnosis (ICD-O-3:8000/0) was reported for 10 441 biopsies (50.81%) and 45.26% had a malignant diagnosis (n = 9302). An adenocarcinoma (8140/3) sub-diagnosis was reported for 88.16% of malignant biopsies (n = 8201). An atypia diagnosis was reported for 760 biopsies (3.7%). Inflammation (39.03%) and hyperplasia (20.82%) were the predominant benign sub-diagnoses. CONCLUSION: Our study demonstrated the feasibility of generating PCa data using SNOMED codes from national laboratory data. This highlights the need for extending the results of our study to a national level to deliver timeous monitoring of PCa trends.
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BACKGROUND: Mean turn-around time (TAT) reporting for testing laboratories in a national network is typically static and not immediately available for meaningful corrective action and does not allow for test-by-test or site-by-site interrogation of individual laboratory performance. OBJECTIVE: The aim of this study was to develop an easy-to-use, visual dashboard to report interactive graphical TAT data to provide a weekly snapshot of TAT efficiency. METHODS: An interactive dashboard was developed by staff from the National Priority Programme and Central Data Warehouse of the National Health Laboratory Service, Johannesburg, South Africa, during 2018. Steps required to develop the dashboard were summarised in a flowchart. To illustrate the dashboard, one week of data from a busy laboratory for a specific set of tests was analysed using annual performance plan TAT cut-offs. Data were extracted and prepared to deliver an aggregate extract, with statistical measures provided, including test volumes, global percentage of tests that were within TAT cut-offs and percentile statistics. RESULTS: Nine steps were used to develop the dashboard iteratively with continuous feedback for each step. The data warehouse environment conformed and stored laboratory information system data in two formats: (1) fact and (2) dimension. Queries were developed to generate an aggregate TAT data extract to create the dashboard. The dashboard successfully delivered weekly TAT reports. CONCLUSION: Implementation of a TAT dashboard can successfully enable the delivery of near real-time information and provide a weekly snapshot of efficiency in the form of TAT performance to identify and quantitate bottlenecks in service delivery.
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BACKGROUND: In South Africa's National Health Laboratory Service, ad hoc mean turn-around time (TAT) reporting is an important indicator of performance. However, historic static TAT reporting did not assess very long or very short times. An interactive TAT dashboard was developed using the following TAT measures; (1) median, (2) 75th percentile and (3) percentage of within cut-off TAT to allow for improved differentiation of TAT performance. OBJECTIVES: The objective of our study was to demonstrate increased efficiency achieved by using an interactive TAT dashboard. METHODS: A retrospective descriptive study design was used. Creatinine TAT outcomes were reported over 122 weeks from a high-volume laboratory in Gauteng, South Africa. The percentage of within cut-off and 75th percentile TAT were analysed and reported using Microsoft Excel. A focus group session was used to populate a cause and effect diagram. RESULTS: The percentage of within cut-off TAT increased from 10% in week 4 to 90% and higher from week 81. The 75th percentile decreased from 10 hours in week 4 to under 5 h from week 71. Component TAT analysis revealed that the 75th percentile testing was 5 h or longer for weeks 4, 5 and 48. The 75th percentile review TAT ranged from 1 h to 15 h. From week 41, the review TAT was under 1 h. CONCLUSION: Our study demonstrated that the use of an interactive TAT dashboard coupled with good management can dramatically improve TAT and efficiency in a high-volume laboratory.
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OBJECTIVE: To immunophenotype CD4+ and CD8+ T cell sub-populations in HIV-associated immune reconstitution inflammatory syndrome (IRIS). DESIGN: Nested case-control immunological study. METHODS: ART-naïve HIV-infected patients were prospectively observed for IRIS during the first 6 months of ART. Twenty-two IRIS cases and 22 ART-duration matched controls were sampled for T cell immunophenotyping. RESULTS: IRIS cases demonstrated significantly lower CD4 cell counts compared to controls (baseline: 79 versus 142, p = 0.02; enrollment: 183 versus 263, p = 0.05, respectively) with no differences in HIV RNA levels. Within CD4+T cells, cases exhibited more of an effector memory phenotype compared to controls (40.8 versus 27.0%, p = 0.20), while controls trended towards a central memory phenotype (43.8 versus 30.8%, p = 0.07). Within CD8+ T cells, controls exhibited more central memory (13.9 versus 7.81%, p = 0.01, respectively) and effector (13.2 versus 8.8%, p = 0.04, respectively) phenotypes compared to cases, whereas cases demonstrated more terminal effectors than controls (28.8 versus 15.1%, p = 0.05). Cases demonstrated increased activation of CD8+ T cell effector memory, terminal effector, and effector subsets than controls (p = 0.04, 0.02, and 0.02, respectively). CONCLUSION: CD4+ and CD8+ T cell subset maturational phenotypes were heterogeneous among IRIS cases and controls. However, IRIS cases demonstrated significant increases in activation of CD8+ T cell effector subpopulations.
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BACKGROUND: Flow cytometry has been the approach of choice for enumerating and documenting CD4-cell decline in HIV monitoring. Beckman Coulter has developed a single platform test for CD4+ T-cell lymphocyte count and percentage using PanLeucogating (PLG) technology on the automated AQUIOS flow cytometer (AQUIOS PLG). OBJECTIVES: This study compared the performance of AQUIOS PLG with the Flowcare PLG method and performed a reference interval for comparison with those previously published. METHODS: The study was conducted between November 2014 and March 2015 at 5 different centres located in Canada; Paris, France; Lyon, France; the United States; and South Africa. Two-hundred and forty samples from HIV-positive adult and paediatric patients were used to compare the performances of AQUIOS PLG and Flowcare PLG on a FC500 flow cytometer (Flowcare PLG) in determining CD4+ absolute count and percentage. A reference interval was determined using 155 samples from healthy, non-HIV adults. Workflow was investigated testing 440 samples over 5 days. RESULTS: Mean absolute and relative count bias between AQUIOS PLG and Flowcare PLG was -41 cells/µL and -7.8%. Upward and downward misclassification at various CD4 thresholds was ≤ 2.4% and ≤ 11.1%. The 95% reference interval (2.5th - 97.5th) for the CD4+ count was 453-1534 cells/µL and the percentage was 30.5% - 63.4%. The workflow showed an average number of HIV samples tested as 17.5 per hour or 122.5 per 8-hour shift for one technician, including passing quality controls. CONCLUSION: The AQUIOS PLG merges desirable aspects from conventional flow cytometer systems (high throughput, precision and accuracy, external quality assessment compatibility) with low technical operating skill requirements for automated, single platform systems.
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BACKGROUND AND OBJECTIVE: The National Health Laboratory Service provides CD4 testing through an integrated tiered service delivery model with a target laboratory turn-around time (TAT) of 48 h. Mean TAT provides insight into national CD4 laboratory performance. However, it is not sensitive enough to identify inefficiencies of outlying laboratories or predict the percentage of samples meeting the TAT target. The aim of this study was to describe the use of the median, 75th percentile and percentage within target of laboratory TAT data to categorise laboratory performance. METHODS: Retrospective CD4 laboratory data for 2015-2016 fiscal year were extracted from the corporate data warehouse. The laboratory TAT distribution and percentage of samples within the 48 h target were assessed. A scatter plot was used to categorise laboratory performance into four quadrants using both the percentage within target and 75th percentile TAT. The laboratory performance was labelled good, satisfactory or poor. RESULTS: TAT data reported a positive skew with a mode of 13 h and a median of 17 h and 75th percentile of 25 h. Overall, 93.2% of CD4 samples had a laboratory TAT of less than 48 h. 48 out of 52 laboratories reported good TAT performance, i.e. percentage within target > 85% and 75th percentile ≤ 48 h, with two categorised as satisfactory (one parameter met), and two as poor performing laboratories (failed both parameters). CONCLUSION: This study demonstrated the feasibility of utilising laboratory data to categorise laboratory performance. Using the quadrant approach for TAT data, laboratories that need interventions can be highlighted for root cause analysis assessment.
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BACKGROUND: A major challenge facing South Africa is the concomitant HIV and tuberculosis epidemics. The National Health Laboratory Service provides testing for staging HIV-positive patients, monitoring patients on antiretroviral therapy (ART) and diagnosing tuberculosis. Not all health districts have equivalent ART-related coverage in particular for CD4 and HIV viral load testing. OBJECTIVES: The Integrated Tiered Service Delivery Model coverage precinct approach was used to address ART-related testing service coverage gaps in a manner that balances cost, quality and equity. METHODS: An algorithm was developed to identify and address ART-related diagnostic coverage gaps. Data was extracted from the corporate data warehouse and Oracle systems for the period of April 2015 to March 2016. Daily test volumes were based on 21.73 working days per month. Data were analysed using MS Excel and mapped using ArcCatalog and ArcMap. Capacity analysis was informed by the available testing-platforms. RESULTS: Health district daily HIV viral load volumes ranged from 2 to 1308 samples. Nineteen candidate laboratories were identified to address the coverage gaps. Following the proximity analysis, testing was consolidated at four candidate laboratories, resulting in 13 revised candidate laboratories. The revised candidate laboratory daily HIV viral load referrals ranged between 5 and 205 samples, with CD4 volumes between 6 and 85 samples. Remaining coverage gaps were identified in seven municipalities. CONCLUSIONS: The study demonstrated that the service coverage precinct approach could be used to identify coverage gaps for a defined ART-related testing repertoire.