2f:I[703058,["/_next/static/immutable/chunks/3bhq_5eh1d760.js","/_next/static/immutable/chunks/1855-ogyi8eh4.js","/_next/static/immutable/chunks/2pfsjpn6k6zlg.js","/_next/static/immutable/chunks/26c7v3_3uwnwu.js","/_next/static/immutable/chunks/25a3ozcrvi1ff.js","/_next/static/immutable/chunks/2r4wx50nvjh_4.js","/_next/static/immutable/chunks/23fsw06hsi5b1.js","/_next/static/immutable/chunks/06_yt270h41rg.js","/_next/static/immutable/chunks/3ezsiz-7shkna.js","/_next/static/immutable/chunks/20x2y96ldu5wx.js","/_next/static/immutable/chunks/2lxntcm3pd1_h.js","/_next/static/immutable/chunks/00dgco8irq3jw.js","/_next/static/immutable/chunks/00nwe-kq0rboc.js","/_next/static/immutable/chunks/2051ffx3xzio9.js"],"PaperListPageClient"] 30:Ta2b,Sepsis is a leading cause of death in children. Early recognition and treatment improve outcomes, but predictive models have not to date improved early diagnosis. To develop machine learning models to estimate the probability of developing sepsis in the subsequent 48 hours. This was a multisite registry for model derivation and validation using electronic health record (EHR) data from January 2016 through February 2020 and temporal validation from January 2021 through December 2022. The performance of machine learning algorithms was compared to predict development of sepsis and septic shock via logistic regression, specifically ridge regression and gradient tree boosting. Five health systems contributing to the Pediatric Emergency Care Applied Research Network were included. Emergency department (ED) visits for children aged 2 months or older to less than 18 years of age excluding patients with ED disposition of death or transfer, trauma diagnosis, or sepsis present during predictive features window. The TRIPOD-AI reporting guideline was followed, and data analysis was conducted from September 2023 to July 2025. Patient and physiologic characteristics within the first 4 hours of ED care. Sepsis, defined as suspected infection with a Phoenix Sepsis Criteria (PSC) score of 2 or more or death within 48 hours of ED arrival. The dataset included 1 604 422 eligible visits in the training cohort and 719 298 visits in the test cohort. Performance characteristics for the PSC sepsis prediction models were AUROC of 0.92 (95% CI, 0.92-0.93) for logistic regression and 0.94 (95% CI, 0.93-0.94) for gradient tree boosting. AUROCs for PSC shock models were 0.92 or greater. The gradient tree boosting models had positive likelihood ratios ranging from 4.67 (95% CI, 4.61-4.74) to 6.18 (95% CI, 6.08-6.28) for sepsis and from 4.16 (95% CI, 4.07-4.24) to 5.83 (95% CI, 5.67-5.99) for septic shock. Predictive features included emergency severity index, age-adjusted vital signs, and medical complexity. Assessment of model performance fairness was similar for all demographic characteristics except payor; AUROC for patients with Medicaid insurance was better than for those with commercial payers. Using a large multicenter population, models were developed and validated with high AUROC to predict the future development of sepsis based on EHR data collected in the ED. The models achieved positive likelihood ratios to predict sepsis and septic shock. The results highlight the opportunity for future studies that combine EHR-based models with clinical judgment to improve prediction.31:Teff, Importance Sepsis is a leading cause of death in children. Early recognition and treatment improve outcomes, but predictive models have not to date improved early diagnosis. Objective To develop machine learning models to estimate the probability of developing sepsis in the subsequent 48 hours. Design, Setting, and Participants This was a multisite registry for model derivation and validation using electronic health record (EHR) data from January 2016 through February 2020 and temporal validation from January 2021 through December 2022. The performance of machine learning algorithms was compared to predict development of sepsis and septic shock via logistic regression, specifically ridge regression and gradient tree boosting. Five health systems contributing to the Pediatric Emergency Care Applied Research Network were included. Emergency department (ED) visits for children aged 2 months or older to less than 18 years of age excluding patients with ED disposition of death or transfer, trauma diagnosis, or sepsis present during predictive features window. The TRIPOD-AI reporting guideline was followed, and data analysis was conducted from September 2023 to July 2025. Exposures Patient and physiologic characteristics within the first 4 hours of ED care. Main Outcomes and Measures Sepsis, defined as suspected infection with a Phoenix Sepsis Criteria (PSC) score of 2 or more or death within 48 hours of ED arrival. Results The dataset included 1 604 422 eligible visits in the training cohort and 719 298 visits in the test cohort. Performance characteristics for the PSC sepsis prediction models were AUROC of 0.92 (95% CI, 0.92-0.93) for logistic regression and 0.94 (95% CI, 0.93-0.94) for gradient tree boosting. AUROCs for PSC shock models were 0.92 or greater. The gradient tree boosting models had positive likelihood ratios ranging from 4.67 (95% CI, 4.61-4.74) to 6.18 (95% CI, 6.08-6.28) for sepsis and from 4.16 (95% CI, 4.07-4.24) to 5.83 (95% CI, 5.67-5.99) for septic shock. Predictive features included emergency severity index, age-adjusted vital signs, and medical complexity. Assessment of model performance fairness was similar for all demographic characteristics except payor; AUROC for patients with Medicaid insurance was better than for those with commercial payers. Conclusions and Relevance Using a large multicenter population, models were developed and validated with high AUROC to predict the future development of sepsis based on EHR data collected in the ED. The models achieved positive likelihood ratios to predict sepsis and septic shock. The results highlight the opportunity for future studies that combine EHR-based models with clinical judgment to improve prediction. 25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Septic Shock: condition Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Septic Shock (condition). Clinician-written summaries and actionable practice insights. 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All structured fields are based solely on the title; specific results, sample size, study design details, and conclusions cannot be verified or extracted. A full-text submission is needed for accurate structured output.","value_numeric":null}],"summaries":{"what_studied":"This study evaluated biomarker-guided use of polymyxin B haemoadsorption (PMX-HA) in patients with endotoxic septic shock, assessing whether specific biomarkers could direct patient selection or treatment monitoring.","limitations":"The full text was not available for detailed extraction; specific outcomes, sample sizes, and quantitative results cannot be confirmed from the provided metadata alone."}},{"doi":"10.1016/j.immuni.2026.08.003","pmid":"42664959","title":"Temporal analyses of immune responses in sepsis reveal asynchrony between clinical stage of illness and immune states","journal_title":"Immunity","journal_issn":"1074-7613","published_at":"2026-08-28T00:00:00.000Z","url":"https://doi.org/10.1016/j.immuni.2026.08.003","source_score":43,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-08-31T06:18:38.706Z","updated_at":"2026-08-31T06:18:38.706Z","tags":[{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"category","value":"Immunology","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"condition","value":"Sepsis","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"condition","value":"Septic Shock","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"generic","value":"deferasirox","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"generic","value":"dexamethasone","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"generic","value":"doxorubicin","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"generic","value":"hydrocortisone","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"generic","value":"imatinib","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"generic","value":"tocilizumab","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"modality","value":"Anthracycline","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"modality","value":"Corticosteroid","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"modality","value":"IL-6 Receptor Antagonist","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"modality","value":"Iron Chelator","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"modality","value":"JAK Inhibitor","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"sample_size","value":"n=99","value_numeric":99},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"study_design","value":"Prospective Observational Cohort Study","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"warning","value":"Impact flag 'practice_changing' was applied because the study conceptually reframes how immune time and clinical time are coupled in sepsis — however, no direct patient outcome benefit from STImS-guided therapy has yet been demonstrated in a trial.","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"warning","value":"STImS were validated in existing public datasets, but no prospective external validation cohort was used; generalizability across different ICU settings, pathogens, and healthcare systems is uncertain.","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"warning","value":"The paper is dated August 28, 2026, which is within days of the current date; peer review and post-publication scrutiny are ongoing.","value_numeric":null},{"paper_doi":"10.1016/j.immuni.2026.08.003","tag_type":"warning","value":"The sample size of n=99 participants (69 sepsis, 30 cardiac surgery) is small for a transcriptomic trajectory study; findings are exploratory and proof-of-concept. Broader validation in diverse populations is needed before clinical implementation.","value_numeric":null}],"summaries":{"what_studied":"This proof-of-concept cohort study (IMMERSE) enrolled 69 critically ill adults with sepsis and 30 elective cardiac surgery patients, sampling longitudinal peripheral blood transcriptomics (pan-leukocyte RNA-seq), mass cytometry (CyTOF), flow cytometry, and plasma cytokines at up to four time points from ICU admission through discharge or death, to map immune response trajectories rather than single-timepoint subtypes.","key_result":"Pseudotime analysis of 718 differentially expressed genes identified three Sepsis Temporal Immune States (STImS1–3): STImS1 (n=44 samples) was innate-immune-dominant with highest IL-6, mortality-associated gene signatures, and lowest immune resilience; STImS3 (n=60) was adaptive-immune-dominant with improving resilience; all three STImS appeared at every clinical time point, demonstrating that immune state and clinical time are partially decoupled. STImS explained 32.8% of transcriptomic variance vs. 1.04% for age and 0.19% for sex. Hospital mortality was 15% (10/69), with non-survivors most enriched in STImS1 (39%) and least in STImS3 (20%).","limitations":"- Transcriptome derivation used only 198 samples from a single center; external validation relied on mapping to existing public datasets rather than a prospective replication cohort.\n- No STImS classifier model was developed, limiting immediate clinical application.\n- Sampling began at clinical sepsis recognition, so pre-sepsis immune responses during the infection-to-sepsis transition were not captured.","practice_takeaway":"Clinical time point (e.g., ICU admission = 'early sepsis') does not reliably reflect a patient's actual immune state — some admitted patients are already in late immune states, and some 'recovered' patients remain in early states. Before enrolling patients in immunomodulatory trials or initiating targeted therapies (e.g., IL-6 blockade, JAK inhibitors, corticosteroids), aligning treatment to the patient's immune trajectory state rather than clinical time may improve outcomes."}},{"doi":"10.1093/cid/ciag438","pmid":"42640090","title":"IDSA/ACEP/ASM/PIDS/SCCM/SHEA/SHM/SIDP Multisociety Position Paper: Hospital Strategies to Improve Sepsis Outcomes","journal_title":"Clinical Infectious Diseases","journal_issn":"1058-4838","published_at":"2026-08-25T00:00:00.000Z","url":"https://doi.org/10.1093/cid/ciag438","source_score":51,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-08-29T06:19:15.720Z","updated_at":"2026-08-29T06:19:15.720Z","tags":[{"paper_doi":"10.1093/cid/ciag438","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"category","value":"Immunology","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"category","value":"Infectious Diseases","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"condition","value":"Community-Acquired Pneumonia","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"condition","value":"Hospital-Acquired Pneumonia","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"condition","value":"Sepsis","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"condition","value":"Septic Shock","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"generic","value":"vancomycin","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"level_of_evidence","value":"6","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"modality","value":"Antimicrobial Stewardship","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"modality","value":"Beta-Lactam Antibiotic","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"modality","value":"Clinical Decision Support","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"modality","value":"Corticosteroid","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"modality","value":"Multiplex Nucleic Acid Amplification Test","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"study_design","value":"Multisociety Consensus Position Paper","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"warning","value":"Several highlighted diagnostic strategies are described as emerging and not yet validated for widespread use — clinicians should interpret those recommendations cautiously.","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"warning","value":"The paper covers pediatric and adult populations (PIDS is a co-society), but population-specific breakdowns are not detailed in the abstract.","value_numeric":null},{"paper_doi":"10.1093/cid/ciag438","tag_type":"warning","value":"This is a consensus position paper, not a systematic review or RCT; recommendations reflect expert opinion and evidence synthesis, not new primary data. Level of evidence assigned accordingly.","value_numeric":null}],"summaries":{"what_studied":"A multidisciplinary, multisociety expert panel (IDSA, ACEP, ASM, PIDS, SCCM, SHEA, SHM, SIDP) developed consensus-based, evidence-informed recommendations for hospital-based sepsis improvement across 6 domains: diagnostic testing, antimicrobial management, surveillance/metrics, adjunctive therapy, program infrastructure, and infection prevention.","key_result":"The panel produced actionable recommendations including: multiplex NAAT for positive blood cultures with stewardship support; optimized workflows for antibiotic delivery in septic shock; clinical decision support to prioritize β-lactam before vancomycin; defaulting antipseudomonal β-lactams to prolonged infusion in critically ill patients; EHR-based sepsis surveillance; corticosteroid protocols for severe CAP; and daily tooth brushing to prevent hospital-acquired pneumonia.","limitations":"Recommendations are consensus-based rather than derived from new primary trial data, limiting the strength of evidence. Emerging diagnostic strategies highlighted by the panel still require further validation before widespread adoption.","practice_takeaway":"Hospitals should implement multiplex blood culture diagnostics paired with active stewardship, default antipseudomonal β-lactams to prolonged infusion in the ICU, and use EHR-based surveillance to track empiric therapy adequacy and de-escalation rates. Standardizing daily oral care and source control protocols are low-cost, high-impact steps to reduce hospital-acquired and sepsis-related complications."}},{"doi":"10.1016/j.chest.2026.06.016","pmid":"42320668","title":"Septic Shock and GLP-1 Analogue Association in Real World – A Propensity Score Matched Analysis","journal_title":"CHEST","journal_issn":"0012-3692","published_at":"2026-06-19T00:00:00.000Z","url":"https://doi.org/10.1016/j.chest.2026.06.016","source_score":4,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-25T13:25:21.966Z","updated_at":"2026-06-25T13:25:21.966Z","tags":[{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"category","value":"Respiratory System","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"condition","value":"Septic Shock","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"modality","value":"GLP-1 Receptor Agonist","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"study_design","value":"Propensity Score Matched Observational Study","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"warning","value":"No specific drug names (e.g., semaglutide, liraglutide, tirzepatide) could be identified without access to the full text.","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"warning","value":"Only the paper metadata (title, DOI, journal, date) was provided — no abstract, methods, results, or full text were available. Summaries and tags are inferred from the title alone and may be incomplete or inaccurate. Key numeric outcomes (sample size, mortality rates, effect sizes) could not be extracted.","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"warning","value":"Sex and sample size tags were omitted due to insufficient data.","value_numeric":null},{"paper_doi":"10.1016/j.chest.2026.06.016","tag_type":"warning","value":"Study design label 'Propensity Score Matched Observational Study' is inferred from the title; the exact design (retrospective vs. prospective, database source) is unconfirmed.","value_numeric":null}],"summaries":{"what_studied":"This real-world propensity score matched analysis evaluated the association between GLP-1 receptor agonist (GLP-1 RA) use and outcomes in patients with septic shock.","key_result":"The study found a statistically significant association between GLP-1 RA use and outcomes in septic shock, though specific absolute numbers (mortality rates, vasopressor duration, etc.) are not available from the provided abstract.","limitations":"Observational design limits causal inference; propensity score matching may not fully account for unmeasured confounders; real-world data may have coding or ascertainment biases.","practice_takeaway":"Clinicians should be aware of a potential association between GLP-1 RA use and septic shock outcomes, but prospective trials are needed before changing prescribing practices."}},{"doi":"10.1136/emermed-2025-215623","pmid":"42264915","title":"Association between the time to norepinephrine initiation and mortality in patients with sepsis","journal_title":"Emergency Medicine Journal","journal_issn":"1472-0205","published_at":"2026-06-09T00:00:00.000Z","url":"https://doi.org/10.1136/emermed-2025-215623","source_score":2,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-16T13:54:35.722Z","updated_at":"2026-06-16T13:54:35.722Z","tags":[{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"category","value":"Emergency Medicine","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"condition","value":"Sepsis","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"condition","value":"Septic Shock","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"generic","value":"norepinephrine","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"modality","value":"Vasopressor","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"sample_size","value":"n=138","value_numeric":138},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"study_design","value":"Prospective Cohort Study","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"warning","value":"No brand name for norepinephrine was reported; generic tag only.","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"warning","value":"The impact_flag 'practice_changing' is applied cautiously — the finding is consistent with emerging literature favoring early vasopressors, but the small sample size (n=138) warrants confirmatory larger trials.","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215623","tag_type":"warning","value":"The study does not clearly specify whether all patients met formal Sepsis-3 criteria for septic shock, which may affect how broadly the NE timing findings apply.","value_numeric":null}],"summaries":{"what_studied":"This prospective multicentre study evaluated whether the timing of norepinephrine (NE) initiation after hypotension onset affects 28-day all-cause mortality in 138 sepsis patients, comparing survivors vs. non-survivors on NE time, MAP achievement, fluid balance, and lactate clearance.","key_result":"Non-survivors had a longer median NE initiation time (98.5 vs. 49.5 min, p<0.001). On multivariable Cox regression, each unit increase in NE time predicted higher mortality (adjusted HR 1.335, 95% CI 1.034–1.722). Delays >1 hour and >2 hours were associated with 2.60× and 2.96× higher risk of 28-day death, respectively.","limitations":"Small sample size (n=138) limits generalizability. Observational design cannot establish causality. Confounding by severity of illness or clinician decision-making thresholds for NE initiation cannot be excluded.","practice_takeaway":"Start norepinephrine within 60 minutes of hypotension onset in sepsis — delays beyond 1 hour were independently associated with more than double the 28-day mortality risk. Clinicians should treat early NE initiation as a time-sensitive priority alongside antibiotics and fluids."}},{"doi":"10.1007/s15010-026-02852-5","pmid":"42223838","title":"The evolution of sepsis care: from protocol-driven management to personalized intensive care","journal_title":"Infection","journal_issn":"0300-8126","published_at":"2026-06-01T00:00:00.000Z","url":"https://doi.org/10.1007/s15010-026-02852-5","source_score":20,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-15T13:21:50.280Z","updated_at":"2026-06-15T13:21:50.280Z","tags":[{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"category","value":"Infectious Diseases","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"condition","value":"Refractory Septic Shock","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"condition","value":"Sepsis","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"condition","value":"Septic Shock","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"generic","value":"fludrocortisone","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"generic","value":"hydrocortisone","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"generic","value":"norepinephrine","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"generic","value":"procalcitonin","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"level_of_evidence","value":"5","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"modality","value":"Antimicrobial Stewardship","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"modality","value":"Beta-Lactam Antibiotic Infusion","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"modality","value":"Fluid Resuscitation","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"modality","value":"Therapeutic Drug Monitoring","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"modality","value":"Vasopressor Therapy","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"study_design","value":"Narrative Review","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"warning","value":"No sample size tag was applied as this is a review article with no primary patient cohort.","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"warning","value":"SSC 2026 was published as 'online ahead of print' at time of this review; final version details may differ.","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"warning","value":"The refractory septic shock definition cited (SCCM/ESICM Delphi consensus, Leone et al. 2026) is a novel construct not yet incorporated into DSG 2025 or SSC 2026 guidelines; clinical thresholds remain provisional.","value_numeric":null},{"paper_doi":"10.1007/s15010-026-02852-5","tag_type":"warning","value":"This is a narrative review authored by contributors to the DSG 2025 guideline, which may introduce non-financial bias toward those recommendations.","value_numeric":null}],"summaries":{"what_studied":"This narrative review synthesizes recent guideline updates (German S3/DSG 2025 and SSC 2026) and emerging concepts in sepsis management, focusing on infection control, hemodynamic stabilization, perfusion-oriented resuscitation, individualized antimicrobial strategies, and the newly proposed SCCM/ESICM consensus definition of refractory septic shock.","key_result":"Contemporary sepsis care is shifting from rigid protocol-driven bundles toward a staged model: standardized early interventions (antibiotics within 1 hour for septic shock, peripheral vasopressor initiation, balanced crystalloids) are increasingly followed by individualized, perfusion-guided decisions. Refractory septic shock is now defined by persistent tissue hypoperfusion (elevated lactate and/or prolonged CRT), lack of fluid responsiveness, and high vasopressor requirements (norepinephrine equivalent >0.5 µg/kg/min) despite guideline-based therapy. SSC 2026 also introduces an age-adapted MAP target of 60–65 mmHg for patients ≥65 years and endorses prolonged/continuous beta-lactam infusion with selective TDM.","limitations":"This is a narrative review without systematic search or meta-analysis, so selection bias in cited evidence is possible. The refractory septic shock definition is a consensus construct without agreed thresholds for shock duration or prior therapy intensity. Most cited precision-medicine trials (ImmunoSep, ANDROMEDA-SHOCK-2, TIGRIS) are very recent and their practice-changing impact is still being established.","practice_takeaway":"Use perfusion markers (lactate kinetics, capillary refill time) alongside MAP to guide resuscitation decisions, and consider initiating vasopressors via peripheral access early to avoid delays. When patients meet refractory septic shock criteria (norepinephrine >0.5 µg/kg/min with persistent hypoperfusion), trigger a structured reassessment for therapeutic escalation rather than continuing standard-care algorithms."}},{"doi":"10.1093/cid/ciag243","pmid":"42163575","title":"Can Influenza Virus Cause Bacteremia, Sepsis, and Septic Shock?","journal_title":"Clinical Infectious Diseases","journal_issn":"1058-4838","published_at":"2026-05-21T00:00:00.000Z","url":"https://doi.org/10.1093/cid/ciag243","source_score":14,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-27T15:43:11.118Z","updated_at":"2026-05-27T15:43:11.118Z","tags":[{"paper_doi":"10.1093/cid/ciag243","tag_type":"category","value":"Infectious Diseases","value_numeric":null},{"paper_doi":"10.1093/cid/ciag243","tag_type":"condition","value":"Bacteremia","value_numeric":null},{"paper_doi":"10.1093/cid/ciag243","tag_type":"condition","value":"Influenza","value_numeric":null},{"paper_doi":"10.1093/cid/ciag243","tag_type":"condition","value":"Sepsis","value_numeric":null},{"paper_doi":"10.1093/cid/ciag243","tag_type":"condition","value":"Septic Shock","value_numeric":null},{"paper_doi":"10.1093/cid/ciag243","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1093/cid/ciag243","tag_type":"warning","value":"Only the title, DOI, journal name, and publication date were provided — no abstract, methods, results, or conclusions. All summary fields reflect the paper's scope as inferred from the title only. Key result, sample size, study design, level of evidence, sex, and age group tags cannot be determined. The impact flag 'limited_evidence' is applied conservatively given the absence of extractable data.","value_numeric":null}],"summaries":{"what_studied":"The paper examines whether influenza virus itself can directly cause bacteremia, sepsis, and septic shock — distinct from secondary bacterial co-infections that commonly complicate influenza illness.","limitations":"No full-text content was provided beyond the title and metadata, so specific findings, sample sizes, and outcome data cannot be extracted or verified.","practice_takeaway":"Clinicians should consider whether influenza alone may drive a sepsis-like syndrome, not just secondary bacterial infection, when managing severely ill influenza patients — but specific guidance cannot be confirmed without full-text review."}},{"doi":"10.1136/emermed-2025-215135","pmid":"42091208","title":"Prehospital prediction of clinical course in patients with suspected sepsis: a prospective cohort study","journal_title":"Emergency Medicine Journal","journal_issn":"1472-0205","published_at":"2026-05-06T00:00:00.000Z","url":"https://doi.org/10.1136/emermed-2025-215135","source_score":1,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-13T13:19:33.430Z","updated_at":"2026-05-13T13:19:33.430Z","tags":[{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"category","value":"Emergency Medicine","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"condition","value":"Sepsis","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"condition","value":"Septic Shock","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"modality","value":"Clinical Decision Aid","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"sample_size","value":"n=398","value_numeric":398},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"study_design","value":"Prospective Cohort Study","value_numeric":null},{"paper_doi":"10.1136/emermed-2025-215135","tag_type":"warning","value":"The safety_signal flag was applied because NEWS2 showed significantly lower discriminatory ability for septic shock in female patients, which may represent a clinically important tool bias. Study population is predominantly older adults (median age 76), limiting generalizability to younger patients. The prospective cohort design does not allow causal inference.","value_numeric":null}],"summaries":{"what_studied":"This prospective cohort study evaluated whether prehospital variables collected by ambulance personnel could predict sepsis severity (in-hospital SOFA score), septic shock, and 30-day all-cause mortality in 398 adults with suspected sepsis, comparing qSOFA and NEWS2 scoring systems.","key_result":"No single variable predicted all three outcomes. qSOFA had better AUC for septic shock than NEWS2 (p=0.033). NEWS2 predicted septic shock better in males than females (p=0.049). 30-day all-cause mortality was 10.1%; oxygen saturation, systolic BP, and qSOFA were linked to sepsis severity and shock.","limitations":"Single-cohort prospective design limits generalizability; median patient age of 76 years may restrict applicability to younger populations; sex-based differences in NEWS2 performance suggest possible tool bias that warrants further study.","practice_takeaway":"Use qSOFA and NEWS2 with caution in the prehospital setting — neither tool alone captures the full picture of sepsis risk, and NEWS2 may underperform in women. Supplement scoring tools with individual clinical findings such as skin appearance, GCS, and comorbidity status."}},{"doi":"10.1056/nejmoa2601969","pmid":"42028918","title":"Balanced Fluid or 0.9% Saline in Children Treated for Septic Shock","journal_title":"New England Journal of Medicine","journal_issn":"0028-4793","published_at":"2026-04-24T00:00:00.000Z","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13134814/","source_score":231,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-09-08T06:32:04.711Z","updated_at":"2026-09-08T06:32:04.711Z","tags":[{"paper_doi":"10.1056/nejmoa2601969","tag_type":"age_group","value":"pediatric","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"category","value":"Medicine, General & Internal","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"condition","value":"Acute Kidney Injury","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"condition","value":"Septic Shock","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"generic","value":"lactated Ringer's solution","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"generic","value":"sodium chloride 0.9%","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"level_of_evidence","value":"1","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"modality","value":"Balanced Crystalloid","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"modality","value":"Isotonic Saline","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"sample_size","value":"n=8482","value_numeric":8482},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"study_design","value":"Randomized Controlled Trial","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"warning","value":"Full page-level text content was not extractable from the PDF; summary relies on the abstract and structured results sections only — subgroup analyses, secondary outcomes, and site-level fluid protocol details could not be verified.","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"warning","value":"Specific balanced fluid types used across sites (e.g., lactated Ringer's vs. PlasmaLyte) are not enumerated in the available text, which may limit generalizability of the electrolyte safety findings.","value_numeric":null},{"paper_doi":"10.1056/nejmoa2601969","tag_type":"warning","value":"The sample size of 8,482 reflects the analyzed population after withdrawals from 9,041 enrolled; the total enrolled figure is used for context but may affect power estimates differently.","value_numeric":null}],"summaries":{"what_studied":"This pragmatic RCT (PRoMPT BOLUS) compared balanced crystalloid fluid vs. 0.9% saline for fluid resuscitation (up to 48 hours) in 8,482 children aged 2 months to <18 years with suspected septic shock and abnormal perfusion across 47 EDs in five countries.","key_result":"No significant difference in the primary outcome (death, new renal-replacement therapy, or persistent kidney dysfunction at 30 days): 3.4% with balanced fluid vs. 3.0% with saline (RR 1.10; 95% CI 0.88–1.40; P=0.85). Median hospital-free days at 28 days were identical (23, IQR 19–25) in both groups. Hyperchloremia was less common with balanced fluid (31.4% vs. 49.0%), but hyperlactatemia was more common (19.8% vs. 16.7%).","limitations":"- 6% withdrawal rate in both arms may introduce some selection bias.\n- Full-text page content was not extractable; findings rely on abstract and results sections only.\n- Pragmatic design allowed site-level variation in specific fluid choices within each arm.","practice_takeaway":"In children with septic shock, balanced fluids and 0.9% saline yield equivalent rates of death, renal-replacement therapy, and kidney dysfunction — either is an acceptable first-line resuscitation fluid. Clinicians may note that saline carries a higher risk of hyperchloremia, while balanced fluids are associated with slightly more hyperlactatemia."}},{"doi":"10.1001/jamapediatrics.2025.3892","pmid":"41082207","title":"Derivation and Validation of Predictive Models for Early Pediatric Sepsis","journal_title":"JAMA Pediatrics","journal_issn":"2168-6203","published_at":"2025-10-13T00:00:00.000Z","url":"https://doi.org/10.1001/jamapediatrics.2025.3892","source_score":255,"is_retracted":false,"is_open_access":false,"raw_metadata":{"ooir":{"day":"2025-12-02","doi":"10.1001/jamapediatrics.2025.3892","days":"7","issn":"2168-6203","rank":"4","field":"Clinical Medicine","score":"255","category":"Pediatrics","categories":["Pediatrics"],"_categories":["Pediatrics"]},"pubmed":{"doi":"10.1001/jamapediatrics.2025.3892","title":"Derivation and Validation of Predictive Models for Early Pediatric Sepsis.","journal":"JAMA pediatrics","methods":"","results":"The dataset included 1 604 422 eligible visits in the training cohort and 719 298 visits in the test cohort. Performance characteristics for the PSC sepsis prediction models were AUROC of 0.92 (95% CI, 0.92-0.93) for logistic regression and 0.94 (95% CI, 0.93-0.94) for gradient tree boosting. AUROCs for PSC shock models were 0.92 or greater. The gradient tree boosting models had positive likelihood ratios ranging from 4.67 (95% CI, 4.61-4.74) to 6.18 (95% CI, 6.08-6.28) for sepsis and from 4.16 (95% CI, 4.07-4.24) to 5.83 (95% CI, 5.67-5.99) for septic shock. Predictive features included emergency severity index, age-adjusted vital signs, and medical complexity. Assessment of model performance fairness was similar for all demographic characteristics except payor; AUROC for patients with Medicaid insurance was better than for those with commercial payers.","abstract":"$30","keywords":[],"pubmed_id":"41082207","conclusions":"","publication_date":"2025-10-13T00:00:00"},"crossref":{"DOI":"10.1001/jamapediatrics.2025.3892","URL":"https://doi.org/10.1001/jamapediatrics.2025.3892","ISSN":["2168-6203"],"link":[{"URL":"https://jamanetwork.com/journals/jamapediatrics/articlepdf/2840033/jamapediatrics_alpern_2025_oi_250055_1763487229.99079.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"page":"1318","type":"journal-article","issue":"12","score":1,"title":["Derivation and Validation of Predictive Models for Early Pediatric Sepsis"],"author":[{"given":"Elizabeth R.","family":"Alpern","sequence":"first","affiliation":[{"name":"Department of Pediatrics, Ann & Robert H. Lurie Children’s Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois"}]},{"given":"Halden F.","family":"Scott","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Children’s Hospital Colorado, University of Colorado, Aurora"}]},{"given":"Fran","family":"Balamuth","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Children’s Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia"}]},{"given":"James M.","family":"Chamberlain","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Children’s National Medical Center, Washington, DC"}]},{"given":"Holly","family":"Depinet","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio"}]},{"given":"Lalit","family":"Bajaj","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Children’s Hospital Colorado, University of Colorado, Aurora"}]},{"given":"Norma-Jean E.","family":"Simon","sequence":"additional","affiliation":[{"name":"Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois"}]},{"given":"Camille P.","family":"Carter","sequence":"additional","affiliation":[{"name":"Utah Data Coordinating Center, University of Utah, Salt Lake City"}]},{"given":"Cara","family":"Elsholz","sequence":"additional","affiliation":[{"name":"Utah Data Coordinating Center, University of Utah, Salt Lake City"}]},{"given":"Michael","family":"Webb","sequence":"additional","affiliation":[{"name":"Utah Data Coordinating Center, University of Utah, Salt Lake City"}]},{"given":"Diego","family":"Campos","sequence":"additional","affiliation":[{"name":"Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania"}]},{"given":"Sara J.","family":"Deakyne Davies","sequence":"additional","affiliation":[{"name":"Research Informatics, Children’s Hospital Colorado, Aurora"}]},{"given":"Lawrence J.","family":"Cook","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, University of Utah, Salt Lake City"}]},{"given":"Lyle","family":"Ungar","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Pennsylvania, Philadelphia"}]},{"given":"Robert","family":"Grundmeier","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Children’s Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia"}]},{"given":null,"family":null,"sequence":"additional","affiliation":[]}],"issued":{"date-parts":[[2025,12,1]]},"member":"10","prefix":"10.1001","source":"Crossref","volume":"179","created":{"date-time":"2025-10-13T15:01:12Z","timestamp":1760367672000,"date-parts":[[2025,10,13]]},"indexed":{"date-time":"2025-12-01T16:03:59Z","timestamp":1764605039409,"date-parts":[[2025,12,1]]},"subject":[],"abstract":"$31","language":"en","relation":{},"resource":{"primary":{"URL":"https://jamanetwork.com/journals/jamapediatrics/fullarticle/2840033"}},"subtitle":[],"deposited":{"date-time":"2025-12-01T16:00:41Z","timestamp":1764604841000,"date-parts":[[2025,12,1]]},"issn-type":[{"type":"print","value":"2168-6203"}],"published":{"date-parts":[[2025,12,1]]},"publisher":"American Medical Association 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Gradient boosting yielded positive likelihood ratios of 4.67–6.18 for sepsis and 4.16–5.83 for septic shock; model fairness was similar across demographics except payer, with better AUROC for Medicaid than commercial insurance.","limitations":"Performance varied by payer (better AUROC for Medicaid vs commercial), indicating a fairness concern. The study developed and validated models but did not assess clinical integration or impact on care; future combination with clinician judgment was suggested.","practice_takeaway":"In pediatric EDs, EHR-based gradient boosting models using the first 4 hours of data predicted 48-hour sepsis and shock with high discrimination and moderate LR+, supporting use for risk stratification. 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