Reducing Communication Delays and Improving Quality of Care with a Tuberculosis Laboratory Information System in Resource Poor Environments: A Cluster Randomized Controlled Trial

<div><p>Background</p><p>Lost, delayed or incorrect laboratory results are associated with delays in initiating treatment. Delays in treatment for Multi-Drug Resistant Tuberculosis (MDR-TB) can worsen patient outcomes and increase transmission. The objective of this study was to evaluate the impact of a laboratory information system in reducing delays and the time for MDR-TB patients to culture convert (stop transmitting).</p><p>Methods</p><p>Setting: 78 primary Health Centers (HCs) in Lima, Peru. Participants lived within the catchment area of participating HCs and had at least one MDR-TB risk factor. The study design was a cluster randomized controlled trial with baseline data. The intervention was the e-Chasqui web-based laboratory information system. Main outcome measures were: times to communicate a result; to start or change a patient's treatment; and for that patient to culture convert.</p><p>Results</p><p>1671 patients were enrolled. Intervention HCs took significantly less time to receive drug susceptibility test (DST) (median 11 vs. 17 days, Hazard Ratio 0.67 [0.62–0.72]) and culture (5 vs. 8 days, 0.68 [0.65–0.72]) results. The time to treatment was not significantly different, but patients in intervention HCs took 16 days (20%) less time to culture convert (p = 0.047).</p><p>Conclusions</p><p>The eChasqui system reduced the time to communicate results between laboratories and HCs and time to culture conversion. It is now used in over 259 HCs covering 4.1 million people. This is the first randomized controlled trial of a laboratory information system in a developing country for any disease and the only study worldwide to show clinical impact of such a system.</p><p>Trial Registration</p><p>ClinicalTrials.gov <a href="http://clinicaltrials.gov/show/NCT01201941" target="_blank">NCT01201941</a></p></div

Flow of samples, results, and MDR treatment requests and plans within the Peruvian National TB Program.

<p>TB microscopy is carried out at point of care health centers, and smear positive samples are only referred for DST if there are risk factors for MDR TB.</p

Primary and secondary outcomes.

<p>Figures are median number of days and IQR in parentheses except for DST laboratory TAT >60 days, which is percentage and absolute value in parentheses.</p

Characteristics, outcome measures, and sample sizes for all study health centers (HCs) and participants.

<p>For characteristics, values are mean (SD) unless stated otherwise. The sample sizes are shown for both the control/intervention, as well as for before and after the implementation of e-Chasqui.</p

Flow of participants, cultures and DSTs through trial.

<p>The Pre-intervention groups represent baseline data collection prior to the RCT which was used to correct for baseline differences between sites during the analysis. Cx is sputum culture, DST is drug sensitivity test.</p

Table_2_A Larger Chocolate Chip—Development of a 15K Theobroma cacao L. SNP Array to Create High-Density Linkage Maps.XLSX

<p>Cacao (Theobroma cacao L.) is an important cash crop in tropical regions around the world and has a rich agronomic history in South America. As a key component in the cosmetic and confectionary industries, millions of people worldwide use products made from cacao, ranging from shampoo to chocolate. An Illumina Infinity II array was created using 13,530 SNPs identified within a small diversity panel of cacao. Of these SNPs, 12,643 derive from variation within annotated cacao genes. The genotypes of 3,072 trees were obtained, including two mapping populations from Ecuador. High-density linkage maps for these two populations were generated and compared to the cacao genome assembly. Phenotypic data from these populations were combined with the linkage maps to identify the QTLs for yield and disease resistance.</p

Table3_A Larger Chocolate Chip—Development of a 15K Theobroma cacao L. SNP Array to Create High-Density Linkage Maps.XLSX

<p>Cacao (Theobroma cacao L.) is an important cash crop in tropical regions around the world and has a rich agronomic history in South America. As a key component in the cosmetic and confectionary industries, millions of people worldwide use products made from cacao, ranging from shampoo to chocolate. An Illumina Infinity II array was created using 13,530 SNPs identified within a small diversity panel of cacao. Of these SNPs, 12,643 derive from variation within annotated cacao genes. The genotypes of 3,072 trees were obtained, including two mapping populations from Ecuador. High-density linkage maps for these two populations were generated and compared to the cacao genome assembly. Phenotypic data from these populations were combined with the linkage maps to identify the QTLs for yield and disease resistance.</p

Forest plots of the HR of the combined endpoint per one SD of annual mean CCA-IMT change (with 95% CIs).

<p>Panel I: Group A (asymptomatic individuals with three or more CVD risk factors), HR adjusted for age, sex and average mean CCA-IMT (model 1). Panel II: Group A (asymptomatic individuals with three or more CVD risk factors), HR adjusted for age, sex, average mean CCA-IMT and other CVD risk factors (model 2). Panel III: Group B (asymptomatic individuals with carotid plaques), HR adjusted for age, sex and average mean CCA-IMT (model 1). Panel IV: Group B (asymptomatic individuals with carotid plaques), HR adjusted for age, sex, average mean CCA-IMT and other CVD risk factors (model 2). Panel V: Group C (individuals with previous CVD events), HR adjusted for age, sex and average mean CCA-IMT (model 1). Panel VI: Group C (individuals with previous CVD events), HR adjusted for age, sex, average mean CCA-IMT and other CVD risk factors (model 2).</p

Forest plots of the HR of the combined endpoint per one SD of average mean CCA-IMT (with 95% CIs).

<p>Panel I: Group A (asymptomatic individuals with three or more CVD risk factors), HR adjusted for age, sex and annual mean CCA-IMT change (model 1). Panel II: Group A (asymptomatic individuals with three or more CVD risk factors), HR adjusted for age, sex, annual mean CCA-IMT change and other CVD risk factors (model 2). Panel III: Group B (asymptomatic individuals with carotid plaques), HR adjusted for age, sex and annual mean CCA-IMT change (model 1). Panel IV: Group B (asymptomatic individuals with carotid plaques), HR adjusted for age, sex, annual mean CCA-IMT change and other CVD risk factors (model 2). Panel V: Group C (individuals with previous CVD events), HR adjusted for age, sex and annual mean CCA-IMT change (model 1). Panel VI: Group C (individuals with previous CVD events), HR adjusted for age, sex, annual mean CCA-IMT change and other CVD risk factors (model 2).</p

Meta-regression plot for the HR (combined endpoint) per SD of annual mean CCA-IMT change (model 1), by the correlation of baseline and follow-up common CIMT.

<p>The size of each circle represents the precision of the log HR.</p