Critical care delivery across health care systems in low-income and low-middle-income country settings: A systematic review
Bibliographic record
Abstract
Background: Prior research has demonstrated that low- and low-middle-income countries (LLMICs) bear a higher burden of critical illness and have a higher rate of mortality from critical illness than high-income countries (HICs). There is a pressing need for improved critical care delivery in LLMICs to reduce this inequity. This systematic review aimed to characterise the range of critical care interventions and services delivered within LLMIC health care systems as reported in the literature. Methods: A search strategy using terms related to critical care in LLMICs was implemented in multiple databases. We included English language articles with human subjects describing at least one critical care intervention or service in an LLMIC setting published between 1 January 2008 and 1 January 2020. Results: A total of 1620 studies met the inclusion criteria. Among the included studies, 45% of studies reported on pediatric patients, 43% on adults, 23% on infants, 8.9% on geriatric patients and 4.2% on maternal patients. Most of the care described (94%) was delivered in-hospital, with the remainder (6.2%) taking place in out-of-hospital care settings. Overall, 49% of critical care described was delivered outside of a designated intensive care unit. Specialist physicians delivered critical care in 60% of the included studies. Additional critical care was delivered by general physicians (40%), as well as specialist physician trainees (22%), pharmacists (16%), advanced nursing or midlevel practitioners (8.9%), ambulance providers (3.3%) and respiratory therapists (3.1%). Conclusions: This review represents a comprehensive synthesis of critical care delivery in LLMIC settings. Approximately 50% of critical care interventions and services were delivered outside of a designated intensive care unit. Specialist physicians were the most common health care professionals involved in care delivery in the included studies, however generalist physicians were commonly reported to provide critical care interventions and services. This study additionally characterised the quality of the published evidence guiding critical care practice in LLMICs, demonstrating a paucity of interventional and cost-effectiveness studies. Future research is needed to understand better how to optimise critical care interventions, services, care delivery and costs in these settings. Registration: PROSPERO CRD42019146802.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".