Challenges in pediatric post-sepsis care in resource limited settings: a narrative review
Bibliographic record
Abstract
OBJECTIVE: The objective of this narrative review is to outline the current epidemiology and interventional research within the context of sepsis recovery, and to provide a summary of key priorities for future work in this area. BACKGROUND: Morbidity and mortality secondary to sepsis disproportionately affects children, especially those in low- and middle-income countries (LMICs), where over 85% of global cases and deaths occur. These regions are plagued by poorly resilient health systems, widespread socio-economic deprivation and unique vulnerabilities such as malnutrition. Reducing the overall burden of sepsis will require a multi-pronged strategy that addresses all three important periods along the sepsis care continuum - pre-facility, facility and post-facility. Of these aspects, post-facility issues have been largely neglected in research, practice and policy, and are thus the focus of this review. METHODS: Relevant data for this review was identified through a literature search using PubMed, through a review of the citations of select systematic reviews and from the personal repositories of articles collected by the authors. Data is presented within three sections. The first two sections on the short and long-term outcomes among sepsis survivors each outline the epidemiology as well as review relevant interventional research done. Where clear gaps exist, these are stated. The third section focuses on priorities for future research. This section highlights the importance of data (and data systems) and of innovative interventional approaches, as key areas to improve research of post-sepsis outcomes in children. CONCLUSIONS: During the initial post-facility period, mortality is high with as many children dying during this period as during the acute period of hospitalization, mostly due to recurrent illness (including infections) which are associated with malnutrition and severe acute disease. Long-term outcomes, often labelled as post-sepsis syndrome (PSS), are characterized by a lag in developmental milestones and suboptimal quality of life (QoL). While long-term outcomes have not been well characterized in resource limited settings, they are well described in high-income countries (HICs), and likely are important contributors to long-term morbidity in resource limited settings. The paucity of interventional research to improve post-discharge outcomes (short- or long-term) is a clear gap in addressing its burden. A focus on the development of improved data systems for collecting routine data, standardized definitions and terminology and a health-systems approach in research need to be prioritized during any efforts to improve outcomes during the post-sepsis phase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".