Effect of Specimen Transport Network System in the Turnaround Time on Patients Tuberculosis Genexpert Test Results in the West Region of Cameroon
Bibliographic record
Abstract
Introduction : Specimen transport network system is a major tool in getting quick turnaround time for patient results in general and for tuberculosis (TB) diagnosis in particular given that TB is an airborne disease and any mismanagement of its specimens, sputum in particular, can lead to generation of aerosols, hence spread and infection of the persons transporting the specimens and the health care personnel receiving the specimens and the delay in the diagnosis leading to more spread of the bacilli and up to the death of the patient. It is therefore of great essence to establish a reliable specimen transport network system which is essential for effective TB patient care, allowing for rapid diagnosis, initiation of treatment and patient follow up in the West Region of Cameroon and Cameroon as a whole. This article is therefore aimed at establishing a better specimen transport network system to better the turn- around time for TB specimens in the West Region of Cameroon. Method: A descriptive retrospective study by means of secondary data collection was carried from January 2016 to July 2017 on 1,130 specimens requested by clinicians before the GeneXpert instruments were introduced in the West Region of Cameroon and from October 2017 to July 2018 when two GeneXpert instruments were introduced in the West region. Request forms with date of test requested at the health facilities in the West region and results registers in which date results from the Reference Laboratory were communicated to health facility in the West Region, were used as the data sources to calculate the turn- around time (TAT). TAT was analyzed in hours and converted to days using excel. Results : Results from this study shows an average decrease in turnaround time of patient’s results from 26 days when the specimens were tested only at the Reference laboratory in Bamenda to 7 days when two GeneXpert instruments were introduced in the West region with a total of 2 platforms where tests could possibly be done. Conclusion : Re designing a better specimen transport network system and increasing the number of Xpert platforms not only in the West region but in all other regions of Cameroon, will reduce TAT for TB results to only 01 to 02 days, thus increase quality of prevention and treatment programs, thereby reducing costs and live savings of the population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".