Current status and challenges in the care of patients with bacterial meningitis in the Philippines: A scoping review
Bibliographic record
Abstract
OBJECTIVE: Bacterial meningitis is associated with high morbidity and mortality if not treated early. Due to the high disease burden, there are barriers in the provision of healthcare services for these patients, especially in low- to middle-income countries, such as the Philippines. We aimed to give an overview of healthcare services delivery and identify gaps in the provision of care for patients with bacterial meningitis in the Philippines. METHOD: We conducted a scoping review on the available literature on the epidemiology, research, health services delivery, diagnostics and management of Filipino patients with bacterial meningitis. A qualitative summary of the results was conducted to provide an overview of the findings. RESULTS: There is a paucity of epidemiological data and research on bacterial meningitis. Healthcare expenditure remains out-of-pocket, with limited coverage from the national health insurance programme. There is an inadequate number of neurologists as well as inequities in the distribution of manpower and facilities due to the devolution of the healthcare system. Diagnosis remains a challenge due to the inaccessibility of tests for CSF analysis. Costs of antibiotics, adjunctive treatment, neurosurgical interventions and rehabilitation are also prohibitive. Outbreaks can be prevented by strengthening existing surveillance systems and improving vaccination coverage against the most common causative organisms. CONCLUSION: Enormous challenges still exist with regards to health services delivery in patients with bacterial meningitis in the Philippines in terms of epidemiologic data and research, access to healthcare facilities and diagnostic tools, healthcare costs, surveillance systems and immunisation against causative pathogens.
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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 | 0.014 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".