David Musorowegomo
Biographic Data
| ID | 9799084 |
|---|---|
| NAME | David Musorowegomo |
| GIVEN NAMES | David |
| FAMILY NAME | Musorowegomo |
| SIGNATURE | MUSOROWEGOMO D |
| AFFILIATIONS | University of Zimbabwe |
| VERIFIED | No |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 1 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Clinical prediction models to diagnose neonatal sepsis in low-income and middle-income countries
INTRODUCTION: Neonatal sepsis causes significant morbidity and mortality worldwide but is difficult to diagnose clinically. Clinical prediction models (CPMs) could improve diagnostic accuracy, facilitating earlier treatment for cases and avoiding antibiotic overuse. Neonates in low-income and middle-income countries (LMICs) are disproportionately affected by sepsis, yet no review has comprehensively synthesised evidence for CPMs validated in this…
No prominent works on this page.
Clinical prediction models to diagnose neonatal sepsis in low-income and middle-income countries
INTRODUCTION: Neonatal sepsis causes significant morbidity and mortality worldwide but is difficult to diagnose clinically. Clinical prediction models (CPMs) could improve diagnostic accuracy, facilitating earlier treatment for cases and avoiding antibiotic overuse. Neonates in low-income and middle-income countries (LMICs) are disproportionately affected by sepsis, yet no review has comprehensively synthesised evidence for CPMs validated in this…
Cochrane Library (1 work) · Developing country (1 work) · Emergency Medicine (1 work) · Environmental health (1 work) · Health care (1 work) · Intensive care (1 work) · Intensive care medicine (1 work) · Internal Medicine (1 work) · Low and middle income countries (1 work) · Medicine (1 work)