Nursing Implications of the Updated 2021 Surviving Sepsis Campaign Guidelines
Bibliographic record
Abstract
Sepsis is a life-threatening illness that affects millions of people worldwide. Early recognition and timely treatment are essential for decreasing mortality from sepsis. The Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2021, the fifth iteration of the guidelines, was released in October 2021 and includes 93 recommendations for the management of sepsis. The evidence-based guidelines include recommendations and rationales for screening and early treatment, initial resuscitation, mean arterial pressure targets, admission to intensive care, management of infection, hemodynamic monitoring, ventilation, and additional therapies. A new section addresses long-term outcomes and goals of care. This article presents several recommendations, changes, and updates in the 2021 guidelines and highlights the important contributions nurses have in delivering timely and evidence-based care to patients with sepsis. Recommendations may be for or against an intervention, according to the evidence. Although many recommendations are unchanged, several new recommendations directly affect nursing care and may require specialized training (eg, venovenous extracorporeal membrane oxygenation). The newest section, long-term outcomes and goals of care, is aimed at using available resources to provide care that is aligned with the patient and the patient's family through goals-of-care discussions and shared decision-making. Interventions aimed at improving recovery across the continuum of care should include attention to long-term outcomes. Nurses are essential in identifying patients with sepsis, administering and assessing response to treatment, supporting the patient and family, and limiting sequelae from sepsis. This article highlights the 2021 recommendations that influence nursing care for patients with sepsis.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".