From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations for Developing Precision Medicine in the ICU

Oxygen targets in critically ill patients: from pathophysiology to population enrichment strategies

Oxygen supplementation is widely used to enhance oxygen delivery and to treat or prevent hypoxia; however, it requires careful management to avoid the harmful effects of excessive oxygen exposure. Both hyperoxia (inspiratory oxygen fraction exceeding 0.21) and hyperoxemia (arterial oxygen tension oxygen partial pressure [PaO2] > 100 mmHg) can contribute to lung injury, promote systemic vasoconstriction, and increase the production of reactive oxygen species, which can impair macromolecular and cellular functions. Conversely, in certain situations, hyperoxemia may provide benefits, such as hemodynamic stabilization in hyperdynamic shock, immunomodulation, and bactericidal effects. The literature presents conflicting evidence regarding the impact of different oxygen targets (i.e., PaO2 and/or peripheral saturation of oxygen [SpO2]) on both short- and long-term outcomes in patients with acute critical conditions, such as acute respiratory distress syndrome, sepsis, cardiac arrest, and acute central nervous system injuries. These discrepancies may stem from the small differences between the oxygenation targets used in randomized trials, the physiological limitations of PaO2 and SpO2 targets, which reflect blood oxygen content rather than oxygen delivery, the lack of measurements of microvascular function or oxygen delivery, and the heterogeneity in treatment response. Furthermore, advanced analytical methods (e.g., machine learning) are emerging as promising tools to implement population enrichment strategies. By refining patient sub-group identification, these approaches can significantly optimize precision medicine, enabling more personalized oxygen therapy tailored to individual patient characteristics.

Molecular endotypes in sepsis: integration of multicohort transcriptomics based on RNA sequencing

BACKGROUND

The heterogeneity of host responses in sepsis has hindered efforts to develop targeted therapies for this large patient population. Although growing evidence has identified sepsis endotypes based on the microarray data, studies using RNA-seq data-which offers higher sensitivity and a broader dynamic range-remain limited. We hypothesized that integrating RNA-seq data from patients with sepsis would reveal molecular endotypes with distinct biological and clinical signatures.

METHODS

In this meta-analysis, we systematically searched for publicly available RNA-seq datasets of sepsis. Using identified datasets, we applied a consensus clustering algorithm to identify distinct endotypes. To characterize the biological differences between these endotypes, we performed gene-set enrichment analysis and immune cell deconvolution. Next, we investigated the association between these endotypes and mortality risks. We finally developed gene classifiers for endotype stratification and validated our endotype classification by applying these classifiers to an external cohort.

RESULTS

A total of 280 adults with sepsis from four datasets were included in this analysis. Using an unsupervised approach, we identified three distinct endotypes: coagulopathic (n = 83, 30%), inflammatory (n = 118, 42%), and adaptive endotype (n = 79, 28%). The coagulopathic endotype exhibited upregulated coagulation signaling, along with an increased monocyte and neutrophil composition, although the adaptive endotype demonstrated enhanced adaptive immune cell responses, marked by elevated T and B cell compositions. The inflammatory endotype was characterized by upregulated TNF-α/NF-κB signaling and IL-6/JAK/STAT3 pathways with an increased neutrophil composition. Patients with the coagulopathic endotype had a significantly higher risk of mortality than those with the adaptive endotype (30% vs. 16%, odds ratio 2.19, 95% confidence interval 1.04-4.78, p = 0.04). To enable the practical application of these findings, we developed endotype classification models and identified 14 gene classifiers. In a validation cohort of 123 patients, we consistently identified these three endotypes. Furthermore, the mortality risk pattern was reproduced, with the coagulopathic endotype showing greater mortality risk than the adaptive endotype (34% vs 18%, p = 0.10).

CONCLUSIONS

This multicohort RNA-seq meta-analysis identified three biologically and clinically distinct sepsis endotypes characterized by coagulopathic, adaptive, and inflammatory responses. This endotype-based approach to patient stratification may facilitate the development of more precise therapeutic strategies for sepsis.

Addressing heterogeneous treatment effects in acute care syndromes: principles and practical considerations

BACKGROUND

Critical care medicine has historically relied on syndromic diagnoses such as sepsis, acute respiratory distress syndrome (ARDS) and acute kidney injury to guide research and treatment. While this approach has advanced clinical practice, the growing recognition of patient heterogeneity presents significant challenges for treatment optimisation and trial interpretation. Understanding heterogeneous treatment effects (HTE) has emerged as a crucial methodological frontier, particularly for complex critical care syndromes where patient responses to interventions vary substantially.

FINDINGS

There are three major methodological frameworks for analysing HTE: (1) Risk-based analyses, guided by the Predictive Approaches to Treatment effect Heterogeneity statement, provide an accessible framework for examining treatment effect variation across baseline risk strata but may overlook important effect modifiers. (2) Clustering techniques have successfully identified distinct phenotypes in both ARDS and sepsis, though external validation remains challenging. (3) Effect-based methods employing new methods offer sophisticated capabilities for identifying treatment effect modifiers but require careful consideration to model specification.

CONCLUSION

This review examines these methodological approaches through both theoretical framework and practical application. Considerations on the applicability of HTE are also provided. We conclude that while HTE methods offer promising tools for personalising critical care interventions, their successful implementation requires careful consideration of both methodological rigour and practical feasibility.

Defining and subphenotyping ARDS: insights from an international Delphi expert panel

Although the definition of acute respiratory distress syndrome (ARDS) has undergone numerous revisions aimed at enhancing its diagnostic accuracy and clinical practicality, the usefulness and precision of these definitions remain matters of ongoing discussion. In this Position Paper, we report on a Delphi study to reach a consensus on the conceptual model of ARDS, specifically identifying its defining components within clinical, research, and educational contexts as well as exploring the potential role of subphenotyping. We did a four-round Delphi study, involving experts in ARDS research and management from a diverse range of geoeconomic regions and professional backgrounds. Consensus was achieved for the conceptual model of ARDS; key components to be included for an ARDS definition in the context of research, education, and patient management; and the need for further research in subphenotyping ARDS. Additionally, we highlight knowledge gaps and research priorities that could guide future investigations in this area. Our study builds on previous non-Delphi-based consensus processes (eg, the new global definition of ARDS and recent society-based guidelines) by using a rigorous Delphi method that ensured panellist anonymity and used clear quantitative criteria to mitigate potential peer pressure and group conformity. The findings underscore the need to refine the ARDS definition to better account for the heterogeneity of clinical presentations and underlying pathophysiology, and to improve diagnostic precision, including the use of subphenotyping where appropriate.

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning

Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailored treatment and prognosis. We used the MIMIC-IV database to analyze patients diagnosed with Sepsis-3 within 24 h of ICU admission. Latent class mixed models (LCMM) were applied to leukocyte trajectories to identify sepsis subtypes. The primary outcome was 28-day all-cause mortality, with secondary outcomes including the need for life-support therapies. Associations between leukocyte trajectories and outcomes were assessed using multivariate regression, and findings were externally validated with the eICU database. Use the XGBoost model to identify baseline characteristics of high-risk mortality sepsis subgroups for predicting subgroup allocation upon patient admission to the ICU, and apply the SHAP method to interpret the contributing variables of the model. Among 7410 sepsis patients, eight distinct leukocyte trajectory subtypes were identified. Among those subtypes, patients with persistently high leukocyte levels had the poorest prognosis (HR 3.00; 95% CI 2.48-3.62) and a significantly greater need for life-support therapies; Patients with persistently low white blood cell levels had a higher risk of death (HR 1.68; 95% CI 1.24-2.27) but were less likely to receive invasive mechanical ventilation. Incorporating early ICU baseline variables into an XGBoost algorithm enables effective prediction of high-mortality risk subgroups (AUC > 0.8). SHAP method reveals distinct early clinical characteristics between hyperinflammatory subtypes (class 4, 7, and 8) and the hypoinflammatory subtype (class 1). In ICU-admitted sepsis patients, eight leukocyte trajectories are identified, which is the key independent predictors of prognosis, separating from single leukocyte measurements. High-mortality risk subgroups exhibit distinct clinical characteristics at ICU admission, providing valuable insights for their prediction and personalized early intervention.

Ferroptosis-related protein biomarkers for diagnosis, differential diagnosis, and short-term mortality in patients with sepsis in the intensive care unit

Background

Sepsis is a disease with high mortality caused by a dysregulated response to infection. Ferroptosis is a newly discovered type of cell death. Ferroptosis-related genes are involved in the occurrence and development of sepsis. However, research on the diagnostic value of ferroptosis-related protein biomarkers in sepsis serum is limited. This study aims to explore the clinical value of Ferroptosis-related proteins in diagnosing sepsis and predicting mortality risk.

Methods

A single-center, prospective, observational study was conducted from January to December 2023, involving 170 sepsis patients, 49 non-septic ICU patients, and 50 healthy individuals. Upon ICU admission, biochemical parameters, GCS, SOFA, and APACHE II scores were recorded, and surplus serum was stored at -80°C for biomarker analysis via ELISA. Diagnostic efficacy was evaluated using ROC curve analysis.

Results

Baseline serum levels of ACSL4, GPX4, PTGS2, CL-11, IL-6, IL-8, PCT, and hs-CRP significantly differed among sepsis, non-septic, and healthy individuals (all p-value < 0.01). ACSL4, GPX4, PTGS2, IL-6, IL-8, PCT, and hs-CRP demonstrated high diagnostic and differential diagnostic performance (AUC: 0.6688 to 0.9945). IL-10 and TNF-α showed good diagnostic performance (AUC = 0.8955 and 0.7657, respectively). ACSL4 (AUC = 0.7127) was associated with predicting sepsis mortality. Serum levels of ACSL4, CL-11, and IL-6 above the cut-off value were associated with shorter survival times. ACSL4 levels were positively correlated with SOFA (Rho = 0.354, p-value < 0.0001), APACHE II (Rho = 0.317, p-value < 0.0001), and septic shock (Rho = 0.274, p-value = 0.003) scores but negatively correlated with the GCS score (Rho = -0.218, p-value = 0.018). GPX4 levels were positively correlated with SOFA (Rho = 0.204, p-value = 0.027) and APACHE II (Rho = 0.233, p-value = 0.011) scores.

Conclusion

ACSL4 and GPX4 have strong diagnostic and differential diagnostic value in sepsis, including the ability to predict 28-day mortality in sepsis patients, and may become new potential serum markers for the diagnostic and differential diagnostic of sepsis.

Impact of Drugs Used in Intensive Care on Routine Coagulation Testing

Coagulation testing is commonly used in the intensive care unit (ICU) to monitor and manage the hemostatic balance, assess bleeding risk, and guide anticoagulant therapy. Routine tests used for this purpose include prothrombin time, activated partial thromboplastin time, fibrinogen, and anti-Xa assays. Some of the drugs commonly used in critically ill patients may influence coagulation assays by interacting in vitro with reagents or in vivo with coagulation pathways, thus altering the coagulation cascade and the fibrinolytic pathway. While the pharmacological effects of drugs on coagulation are usually documented, to our knowledge, no comprehensive review article has been published to date. In this review, we have conducted a critical analysis of the literature to define: (1) the impact of hydroxocobalamin, intravenous lipid emulsion, and propofol on chromogenic assays; (2) the impact of PEGylated compounds, emicizumab, recombinant activated factor VII, antibiotics, and sugammadex on chronometric assays; (3) the challenges associated with bridging anticoagulation in the ICU as well as the effect of N-acetylcystein, serotonin reuptake inhibitors, and tramadol on the hemostasis system. For each drug, we specify the routine coagulation assay that is impacted, whether this is linked to an in vitro interference or an in vivo effect, and the potential consequences on patient management.

Diagnostic Performance of Monocyte Distribution Width for the Detection of Sepsis: A Systematic Review and Meta-Analysis

Objectives

To aggregate literature on the diagnostic performance of monocyte distribution width (MDW) for sepsis detection among adults in the emergency department and inpatient settings.

Methods

We searched the MEDLINE, EMBASE, SCOPUS, and Cochrane databases for studies evaluating MDW for sepsis diagnosis in adults in the hospital setting through October 19, 2024. Two authors (G.E. and Q.H.) independently performed eligibility assessment, data extraction, and risk of bias assessment. We evaluated performance for sepsis-2 and sepsis-3 separately and applied separate diagnostic thresholds depending on the anticoagulant used in blood collection. Data were pooled using a random-effects model. We performed multiple sensitivity analyses to evaluate the stability of our findings.

Results

Twenty-five observational studies comprising 39,041 patients were included. The area under the summary receiver operating curve (AUC) was 0.82 (95% CI, 0.78-0.85) for both sepsis-2 and sepsis-3. Sensitivity and specificity were 0.79 (95% CI, 0.74-0.83) and 0.7 (95% CI, 0.61-0.78) for sepsis-2 and 0.83 (95% CI, 0.78-0.88) and 0.64 (95% CI, 0.55-0.71) for sepsis-3. The threshold-independent weighted-average AUC was 0.76 (SD, 0.1) for sepsis-2 and 0.77 (SD, 0.07) for sepsis-3. The aggregate negative predictive value was 94% for sepsis-2 and 96% for sepsis-3. We observed similar performance across all sensitivity analyses. We assessed the overall quality of evidence to be low.

Conclusions

MDW performs similarly to other biomarkers such as procalcitonin for the diagnosis of sepsis, with the unique advantage of rapid availability as part of routine testing.

Advances in resuscitation and deresuscitation

PURPOSE OF REVIEW

This review aims to provide a perspective on fluid resuscitation strategies and emerging trends in deresuscitation, with a particular emphasis on fluid stewardship, monitoring, and personalized fluid management.

RECENT FINDINGS

Recent studies underscore a paradigm shift in resuscitation strategies. Notably, aggressive plasma volume expansion has been linked to higher morbidity and mortality, favoring conservative fluid resuscitation. Dynamic parameters, such as pulse pressure variation (PPV) and stroke volume variation (SVV) outperform static markers like central venous pressure (CVP) in predicting preload responsiveness. Advances in hemodynamic monitoring and automated closed-loop fluid administration demonstrate efficacy in optimizing resuscitation. Fluid stewardship, supported by machine learning, is reshaping deresuscitation practices, and promoting negative fluid balance to reduce complications. Moreover, next-generation closed-loop systems and fluid management personalization as part of precision medicine are emerging as future directions.

SUMMARY

Advances in fluid resuscitation challenge traditional practices, with evidence favoring personalized and goal-directed strategies. Technological innovations in hemodynamic monitoring, automated fluid control, and machine learning are driving precision fluid management. Fluid stewardship and deresuscitation aim to mitigate fluid accumulation syndrome and improve patient outcomes.

An international observational study validating gene-expression sepsis immune subgroups

BACKGROUND

Sepsis gene-expression sub-phenotypes with prognostic and theranostic potential have been discovered. These have been identified retrospectively and have not been translated to methods that could be deployed at the bedside. We aimed to identify subgroups of septic patients at high-risk of poor outcome, using a rapid, multiplex RNA-based test.

METHODS

Adults with sepsis, in the intensive care unit (ICU) were recruited from 17 sites in the United Kingdom, Sweden and France. Blood was collected at days 2-5 (S1), 6-8 (S2) and 13-15 (S3) after ICU admission and analyzed centrally. Patients were assigned into 'high' and 'low' risk groups using two models previously developed for the Immune-Profiling Panel prototype on the bioMérieux FilmArray® system.

RESULTS

357 patients were recruited (March 2021-November 2022). 69% were male with a median age of 67 years, APACHE II score of 21 and a 30% 90-day mortality rate. The proportions of high-risk patients decreased over the three sampling times (model 1: 53%, 40%, 15% and model 2: 81%, 74%, 37%). In model 1, 90-day mortality was higher in a high-risk group at each time (S1: 35% vs 24%, p = 0.04; S2: 43% vs 20%, p < 0.001; S3: 52% vs 24%, p = 0.007). In model 2, mortality was only significantly different at the second sampling time (S1: 30% vs 27%, p = 0.77; S2: 34% vs 14%, p = 0.002; S3: 35% vs 23%, p = 0.13).

CONCLUSIONS

Gene-expression diagnostics can identify patients with sepsis at high-risk of poor outcomes and could be used to identify patients for precision medicine trials.

REGISTRATION

ISRCTN11364482 Registered 24th September 2020.

A common longitudinal intensive care unit data format (CLIF) for critical illness research

RATIONALE

Critical illness threatens millions of lives annually. Electronic health record (EHR) data are a source of granular information that could generate crucial insights into the nature and optimal treatment of critical illness.

OBJECTIVES

Overcome the data management, security, and standardization barriers to large-scale critical illness EHR studies.

METHODS

We developed a Common Longitudinal Intensive Care Unit (ICU) data Format (CLIF), an open-source database format to harmonize EHR data necessary to study critical illness. We conducted proof-of-concept studies with a federated research architecture: (1) an external validation of an in-hospital mortality prediction model for critically ill patients and (2) an assessment of 72-h temperature trajectories and their association with mechanical ventilation and in-hospital mortality using group-based trajectory models.

MEASUREMENTS AND MAIN RESULTS

We converted longitudinal data from 111,440 critically ill patient admissions from 2020 to 2021 (mean age 60.7 years [standard deviation 17.1], 28% Black, 7% Hispanic, 44% female) across 9 health systems and 39 hospitals into CLIF databases. The in-hospital mortality prediction model had varying performance across CLIF consortium sites (AUCs: 0.73-0.81, Brier scores: 0.06-0.10) with degradation in performance relative to the derivation site. Temperature trajectories were similar across health systems. Hypothermic and hyperthermic-slow-resolver patients consistently had the highest mortality.

CONCLUSIONS

CLIF enables transparent, efficient, and reproducible critical care research across diverse health systems. Our federated case studies showcase CLIF's potential for disease sub-phenotyping and clinical decision-support evaluation. Future applications include pragmatic EHR-based trials, target trial emulations, foundational artificial intelligence (AI) models of critical illness, and real-time critical care quality dashboards.

Acute kidney injury

Acute kidney injury (AKI) is a common, heterogeneous, multifactorial condition, which is part of the overarching syndrome of acute kidney diseases and disorders. This condition's incidence highest in low-income and middle-income countries. In the short term, AKI is associated with increased mortality, an increased risk of complications, extended stays in hospital, and high health-care costs. Long-term complications include chronic kidney disease, kidney failure, cardiovascular morbidity, and an increased risk of death. Several strategies are available to prevent and treat AKI in specific clinical contexts. Otherwise, AKI care is primarily supportive, focused on treatment of the underlying cause, prevention of further injury, management of complications, and short-term renal replacement therapy in case of refractory complications. Evidence confirming that AKI subphenotyping is necessary to identify precision-oriented interventions is growing. Long-term follow-up of individuals recovered from AKI is recommended but the most effective models of care remain unclear.

Haemodynamic management of septic shock

Septic shock is a significant challenge in the management of patients with burns and traumatic injuries when complicated by infection, necessitating prompt and effective haemodynamic support. This review provides a comprehensive overview of current strategies for vasopressor and fluid management in septic shock, with the aim to optimize patient outcomes. With regard to vasopressor management, we elaborate on the pharmacologic profiles and clinical applications of catecholamines, vasopressin derivatives, angiotensin II, and other vasoactive agents. Noradrenaline remains central to septic shock management. The addition of vasopressin, when sequentially added to noradrenaline, offers a non-catecholaminergic vasoactive effect with some clinical benefits and risks of adverse effects. Emerging agents such as angiotensin II and hydroxocobalamin are highlighted for their roles in catecholamine-resistant vasodilatory shock. Next, for fluid management, crystalloids are currently preferred for initial resuscitation, with balanced crystalloids showing benefits over saline. The application of albumin in septic shock warrants further research. High-quality evidence does not support large-volume fluid resuscitation, and an individualized strategy based on haemodynamic parameters, including lactate clearance and capillary refill time, is recommended. The existing knowledge suggests that early vasopressor initiation, particularly noradrenaline, may be critical in cases where fluid resuscitation takes inadequate effect. Management of refractory septic shock remains challenging, with novel agents like angiotensin II and methylene blue showing potential in recent studies. In conclusion, Further research is needed to optimize haemodynamic management of septic shock, particularly in developing novel vasopressor usage and fluid management approaches.

Recent advances of precision immunotherapy in sepsis

Precision immunotherapy signifies the administration of the required type of immune intervention tailored to the state of immune activation at the appropriate time window. The classification of patients into the different states of immune activation is usually done by either a protein blood biomarker or a molecular blood endotype that is diagnostic of the precise immune state. Evidence coming from trials of the last decade suggests that immune interventions should be split into strategies aiming to attenuate the exaggerated immune responses, restore sepsis-induced immunoparalysis (SII) and restore the vascular tone. Suggested strategies to attenuate the immune responses are anakinra, nangibotide and tocilizumab. Biomarkers that guide their use are ferritin, soluble triggering receptor expressed on myeloid cells-1 and C-reactive protein. Suggested strategies to restore SII are nivolumab, recombinant human interferon-gamma, CYT107, granulocyte macrophage colony stimulating factor and IgM-enriched immunoglobulin prepapations. Biomarkers that guide their use are the expression of the human leukocyte antigen DR on blood monocytes, the absolute lymphocyte count and blood levels of immunoglobulin M. One recently suggested strategy to restore vascular tone is adrecizumab, the use of which is guided by blood levels of bio-adrenomedulin. The use of these precision treatment strategies is still hampered by the need for large-scale randomized controlled trials.

Aiming for precision: personalized medicine through sepsis subtyping

According to the latest definition, sepsis is characterized by life-threatening organ dysfunction caused by a dysregulated host response to an infection. However, this definition fails to grasp the heterogeneous nature and the underlying dynamic pathophysiology of the syndrome. In response to this heterogeneity, efforts have been made to stratify sepsis patients into subtypes, either based on their clinical presentation or pathophysiological characteristics. Subtyping introduces the possibility of the implementation of personalized medicine, whereby each patient receives treatment tailored to their individual disease manifestation. This review explores the currently known subtypes, categorized by subphenotypes and endotypes, as well as the treatments that have been researched thus far in the context of sepsis subtypes and personalized medicine.

Non-adrenergic vasopressors for vasodilatory shock or perioperative vasoplegia: a meta-analysis of randomized controlled trials

BACKGROUND

Excessive exposure to adrenergic vasopressors may be harmful. Non-adrenergic vasopressors may spare adrenergic agents and potentially improve outcomes. We aimed to conduct a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the efficacy of non-adrenergic vasopressors in adult patients receiving vasopressor therapy for vasodilatory shock or perioperative vasoplegia.

METHODS

We searched PubMed, Embase, and Cochrane Library for RCTs comparing non-adrenergic vasopressors with adrenergic vasopressors alone or placebo in critically ill or perioperative patients. Each eligible study was categorized into septic shock, cardiac surgery, or non-cardiac surgery. Non-adrenergic vasopressors included vasopressin, terlipressin, selepressin, angiotensin II, methylene blue, and hydroxocobalamin. The primary outcome was mortality at longest follow-up. We conducted a random-effects meta-analysis. We registered the protocol in PROSPERO International Prospective Register of Systematic Reviews (CRD42024505039).

RESULTS

Among 51 eligible RCTs totaling 5715 patients, the predominant population was septic shock in 30 studies, cardiac surgery in 11 studies, and non-cardiac surgery in 10 studies. Cochrane risk-of-bias tool for randomized trials version 2 identified 17 studies as low risk of bias. In septic shock, mortality was significantly lower in the non-adrenergic group (960/2232 [43%] vs. 898/1890 [48%]; risk ratio [RR], 0.92; 95% confidence interval [95% CI], 0.86-0.97; P = 0.03; I2 = 0%), with none of the individual non-adrenergic vasopressors showing significant survival benefits. No significant mortality difference was observed in patients undergoing cardiac surgery (34/410 [8.3%] vs. 47/412 [11%]; RR, 0.82; 95% CI, 0.55-1.22; P = 0.32; I2 = 12%) or those undergoing non-cardiac surgery (9/388 [2.3%] vs. 18/383 [4.7%]; RR, 0.66; 95% CI, 0.31-1.41; P = 0.28; I2 = 0%).

CONCLUSIONS

Administration of non-adrenergic vasopressors was significantly associated with reduced mortality in patients with septic shock. However, no single agent achieved statistical significance in separate analyses. Although the pooled effects of non-adrenergic vasopressors on survival did not reach statistical significance in patients undergoing cardiac or non-cardiac surgery, the confidence intervals included the possibility of both no effect and a clinically important benefit from non-adrenergic agents. These findings justify the conduct of further RCTs comparing non-adrenergic vasopressors to usual care based on noradrenaline alone.

Proportional Assist Ventilation for Minimizing the Duration of Mechanical Ventilation (the PROMIZING study): update to the statistical analysis plan for a randomized controlled trial

BACKGROUND

We previously published the protocol and statistical analysis plan for a randomized controlled trial of Proportional Assist Ventilation for Minimizing the Duration of Mechanical Ventilation: the PROMIZING study in Trials ( https://doi.org/10.1186/s13063-023-07163-w ). This update summarizes changes made to the statistical analysis plan for the trial since the publication of the original protocol and statistical analysis plan.

METHODS/DESIGN

The Proportional Assist Ventilation for Minimizing the Duration of Mechanical Ventilation (PROMIZING) study is a multi-center, open-label, randomized controlled trial designed to determine if ventilation with proportional assist ventilation with load-adjustable gain factors will result in a shorter duration of time spent on mechanical ventilation compared to ventilation with pressure support ventilation for patients with acute respiratory failure. The statistical analysis plan for the trial was incorporated into the original publication of the protocol in Trials ( https://doi.org/10.1186/s13063-023-07163-w ) and was based on version 5.0 of the study protocol and version 1.0 of the statistical analysis plan (SAP), which included plans for both frequentist and Bayesian analyses. We have since updated the SAP to refine the Bayesian analysis plan, update the multistate model diagram, and include plans for a cluster analysis to determine if there is heterogeneity of treatment effect. This update summarizes the changes made and their rationale and provides a refined SAP for the PROMIZING trial with additional background information, in adherence with guidelines for the prospective reporting of SAPs for randomized controlled trials.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02447692 prospectively registered May 19, 2015.

Molecular Mechanisms, Diagnoses, and Treatments of Respiratory Diseases

The Special Issue "Molecular Mechanisms, Diagnoses, and Treatments of Respiratory Diseases" in the journal Biomedicines compiles critical advancements in the understanding of respiratory diseases, focusing on their molecular mechanisms, diagnostic approaches, and therapeutic strategies [...].

Biomarkers in acute kidney injury

Acute kidney injury (AKI) is a multifactorial syndrome with a high risk of short- and long-term complications as well as increased health care costs. The traditional biomarkers of AKI, serum creatinine and urine output, have important limitations. The discovery of new functional and damage/stress biomarkers has enabled a more precise delineation of the aetiology, pathophysiology, site, mechanisms, and severity of injury. This has allowed earlier diagnosis, better prognostication, and the identification of AKI sub-phenotypes. In this review, we summarize the roles and challenges of these new biomarkers in clinical practice and research.

A Patient-Level Meta-Analysis of Intensive Glucose Control in Critically Ill Adults

BACKGROUND

Whether intensive glucose control reduces mortality in critically ill patients remains uncertain. Patient-level meta-analyses can provide more precise estimates of treatment effects than are currently available.

METHODS

We pooled individual patient data from randomized trials investigating intensive glucose control in critically ill adults. The primary outcome was in-hospital mortality. Secondary outcomes included survival to 90 days and time to live cessation of treatment with vasopressors or inotropes, mechanical ventilation, and newly commenced renal replacement. Severe hypoglycemia was a safety outcome.

RESULTS

Of 38 eligible trials (n=29,537 participants), 20 (n=14,171 participants) provided individual patient data including in-hospital mortality status for 7059 and 7049 participants allocated to intensive and conventional glucose control, respectively. Of these 1930 (27.3%) and 1891 (26.8%) individuals assigned to intensive and conventional control, respectively, died (risk ratio, 1.02; 95% confidence interval [CI], 0.96 to 1.07; P=0.52; moderate certainty). There was no apparent heterogeneity of treatment effect on in-hospital mortality in any examined subgroups. Intensive glucose control increased the risk of severe hypoglycemia (risk ratio, 3.38; 95% CI, 2.99 to 3.83; P<0.0001).

CONCLUSIONS

Intensive glucose control was not associated with reduced mortality risk but increased the risk of severe hypoglycemia. We did not identify a subgroup of patients in whom intensive glucose control was beneficial. (Funded by the Australian National Health and Medical Research Council and others; PROSPERO number CRD42021278869.).