Prevalence of Thrombocytopenia and Its Associated Factors Among Neonates Admitted in Neonatal Intensive Care Unit of Addis Ababa Public Hospitals, Ethiopia 2020/21(Cross Sectional Study)
Bibliographic record
Abstract
Abstract Background: Thrombocytopenia is one of the most frequent hematologic disorders encountered in the sick neonate. This is evidenced by a fairly high prevalence among neonates admitted to the neonatal intensive care unit 22%-35%, especially in very-low-birth-weight and preterm neonates its prevalence is up to 70%-80%. In Africa, the prevalence of neonatal thrombocytopenia in Nigeria is 53%, 12.4% in Tunisia, and 16.2% in Libya. However, in Ethiopia, there is limited study assessed both its prevalence and associated factors. Objective: to assess the prevalence of thrombocytopenia and its associated factors among neonates admitted to neonatal intensive care unit at public hospitals in Addis Ababa in 2020/21.Method: Institution based cross sectional study was conducted at NICU of selected Addis Ababa public hospitals from February 15thto March 15th, 2021. Single population proportion formula was used to determine sample size. The final sample size was 423. The collected data entered using Epi data and exported to SPSS version 25 for analysis. Variables that have P-value<0.05in bivariable entered in to multivariable logistic regression model to control for confounder. Statistical significance declared at p-value <0.05.Results: The prevalence of neonatal thrombocytopenia in the study area is 66%.In this study variables such as eclampsia(AOR=4.8, 95%CI: 2.66-13.94), Prolonged rupture of membrane(AOR=0.26, 95%CI:0.101-0.669), Intra uterine growth retardation(AOR=0.26, 95%CI: 0.1-0.68), neonatal sepsis (AOR=11.98, 95%CI: 4.023-25.7), Perinatal asphyxia(AOR=6.68, 95%CI: 2.616-17.6), Necrotizing enterocolitis (AOR=14.6, 95%CI: 2.84-35.61) and prolonged nothing per mouth(AOR=0.243,95%CI: 0.084-0.705) were factors associated with neonatal thrombocytopenia.Conclusion and recommendation: Prevalence of neonatal thrombocytopenia in Addis Ababa public hospitals neonatal intensive care unit is high. Therefore, identifying factors associated with it used as an input in reducing the problem.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".