Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Hybrid implementation effectiveness”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

1,157 records · Page 6Linked to original sources
PubMed2026

Human-Centered Workspace Optimization: A 2 × 2 Factorial Study of Adjustable Furniture and Indoor Environmental Quality.

Small workspaces function as integrated systems, yet ergonomic furniture and indoor environmental conditions are usually evaluated separately. A six-site, assessor-blinded, randomized 2 × 2 factorial controlled study was conducted of two multicomponent packages-adjustable furniture and optimized indoor environmental quality (IEQ)-among 240 office workers for four weeks. Each group included 60 participants. Overall comfort in week 4 was highest for both packages (5.62 ± 0.53 versus 3.99 ± 0.60 with fixed furniture and basic IEQ). In a site-adjusted factorial model with HC3 robust standard errors, the adjustable-furniture effect was 0.86 points (95% confidence interval [CI], 0.62-1.09), the optimized-IEQ effect was 0.34 points (95% CI, 0.12-0.55), and their interaction was 0.44 points (95% CI, 0.14-0.74). Adjustable furniture improved postural comfort and reduced neck and lower back discomfort; optimized IEQ improved environmental comfort; both packages improved perceived productivity, satisfaction, and fatigue. The task-accuracy interaction did not remain significant after false-discovery-rate adjustment, and exploratory mediation and spline analyses did not support indirect or nonlinear effects. These results support coordinated ergonomic and environmental implementation while preserving distinct outcome pathways.

Interior Design and Furnishings↗
PubMed2026

Multi‑omics approaches to decipher the molecular mechanisms of exercise‑mediated bone protection: From mechanistic insights to personalized exercise prescription (Review).

The global burden of bone metabolic disorders necessitates a shift from generic exercise recommendations toward personalized prescription strategies. Exercise confers skeletal protection through mechanotransduction, yet the underlying molecular networks remain incompletely understood. Multi‑omics technologies, including transcriptomics, proteomics, metabolomics and single‑cell spatial approaches, have revolutionized the capacity to decode exercise‑mediated bone adaptation at the systems level. The present review synthesizes current single‑omics landscapes and integrative multi‑omics analyses that elucidate the core regulatory networks, mechanobiological coupling mechanisms and multiorgan crosstalk that are implicated in the bone response to mechanical loading. Translational applications across clinical scenarios such as osteoporosis, osteoarthritis and disuse bone loss are evaluated, and the technical, analytical and translational challenges limiting clinical implementation are addressed. Finally, the present review provides a framework for translating multi‑omics molecular signatures into personalized exercise prescriptions for optimized skeletal health.

Humans↗
PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12 min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22 ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗
PubMed2026

From population to individual: advocating personalised digital tools for heat-health early warning in a changing climate.

Escalating heat extremes under climate change are imposing substantial health burdens, with 2023 and 2024 consecutively breaking global temperature records. Mounting evidence suggests that heatwaves elevate the risks of hospitalisation and mortality across multiple disease categories, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and acute kidney injury. Nonetheless, most existing heat-health warning systems remain primarily reliant on population-level predictions, and considering individual differences and disease-specific considerations when defining warning levels would benefit the effectiveness of early prevention for high-risk groups. In this Viewpoint, which is based on the framework of precision public health-delivering the right intervention to the right population at the right time-we propose a framework for personalised digital heat-health early warning tools comprising three dimensions: individualised, risk-stratified prediction models that generate tiered early warnings; personalised health prompts coupled with theory-informed behavioural interventions; and adaptive, equity-oriented alert delivery mechanisms tailored to diverse populations. Such tools have the potential to bridge precision disease prevention and climate adaptation, thereby helping to mitigate heat exposure risks and disease burdens, particularly among high-risk populations. Future implementation research will be essential to address substantial challenges related to feasibility, validation, and equity.

Journal Article↗
PubMed2026

Mechanisms of Hematopoietic Stem Cell Aging and Emerging Rejuvenation Strategies.

Hematopoietic stem cell (HSCs) aging is a complex biological process driven by both cell-intrinsic alterations and extrinsic cues from the bone marrow niche. Understanding these mechanisms is critical for developing therapies against aging-related hematopoietic disorders. This review synthesizes recent advances in the molecular mechanisms underlying HSCs aging, including microenvironmental aging, genomic instability, epigenetic dysregulation, mitochondrial dysfunction, and aberrant nuclear mechanotransduction. We summarize that the functional decline of HSCs during aging drives a compensatory expansion of the phenotypically defined stem cell pool, leading to an aberrant increase in cell number. We also highlight aging-associated HSCs heterogeneity, including CD150high and P-selectin-positive subsets that enrich for myeloid-biased or functionally compromised HSCs states while emphasizing that surface phenotype alone may not fully indicate functional rejuvenation. Finally, we discuss emerging rejuvenation strategies-including targeting myeloid-biased HSCs, modulating inflammatory pathways, and implementing epigenetic or metabolic interventions-supported by cutting-edge technologies such as single-cell multi-omics, gene editing, and computational modeling. These approaches hold promise for counteracting age-related hematopoietic decline and restoring immune competence.

Humans↗
PubMed2026

Perioperative care for patients with opioid exposure and opioid use disorder: screening and treatment strategies.

PURPOSE OF REVIEW: The prevalence of opioid tolerance, dependence, and use disorder is increasing among patients presenting for surgical care, yet perioperative management strategies for these patients remain inconsistent. This review examines the impact of preoperative opioid exposure on surgical outcomes, the scope of untreated opioid use disorder (OUD) among surgical patients, and advances in clinical and systems-level approaches to perioperative care. RECENT FINDINGS: Preoperative opioid exposure independently predicts worse surgical outcomes, including higher opioid consumption, readmissions, complications, and mortality, in a dose-dependent manner. Perioperative opioid exposure predicts persistent opioid use after surgery, with the duration of exposure a stronger predictor of subsequent OUD than daily dose. Data-driven prescribing guidelines and structured opioid tapering reduce overprescribing without compromising pain control. Among surgical patients with diagnosed OUD, approximately two-thirds do not receive medications for opioid use disorder (MOUD), though treatment engagement and maintenance substantially improve outcomes. Evidence now clearly supports perioperative buprenorphine continuation over interruption. SUMMARY: Effective perioperative management of opioid-complex surgical patients requires systematic screening, evidence-based prescribing, MOUD continuation, and institutional infrastructure. The primary barrier is shifting from evidence generation to implementation.

Humans↗
PubMed2026

School-based sexual violence prevention: A systematic review.

PURPOSE: Sexual violence profoundly affects the health and development of children, adolescents, and young adults, representing a persistent challenge to public policy. This systematic review examined the effectiveness of school-based interventions aimed at prevention. METHODS: Eighteen randomized controlled trials published between 2012 and 2024 were retrieved from four major databases. The programs were implemented in primary, secondary, and higher education settings and targeted children, adolescents, and young adults. RESULTS: The results revealed improvements in knowledge and attitude, particularly regarding consent and awareness, whereas evidence supporting behavioral changes was less frequent and often limited. Methodological limitations, such as short follow-up periods and participant attrition, restricted the assessment of long-term outcomes. CONCLUSIONS: This review highlights the importance of multicomponent, participatory, and culturally sensitive approaches, along with the integration of digital tools and continuous evaluation systems, to strengthen the role of schools as safe and transformative spaces in the prevention of sexual violence. IMPLICATIONS AND CONTRIBUTIONS: This systematic review suggests that school-based interventions hold significant potential for the prevention of sexual violence. It identifies promising strategies and reinforces the importance of culturally sensitive, sustained, evidence-based approaches to ensure learning environments that are safe, protective, and promotive of gender equity.

Humans↗
PubMed2026

Identifying and Prioritizing Core Components of Relationship Education Programs: a Case Study of an Artificial Intelligence (AI) Assisted Systematic Review.

The field of prevention science seeks to identify and implement effective strategies to address social, emotional, and health challenges. A critical aspect of this endeavor is determining the core components of prevention programs that drive positive outcomes. This article presents a case study utilizing artificial intelligence (AI)-assisted systematic review methods to identify key components of healthy marriage and relationship education programs. Given the growing body of research in this domain, AI tools offer a promising means to enhance the efficiency and accuracy of literature reviews. This study employed AI to screen, code, and validate research articles, demonstrating its effectiveness in expediting systematic reviews while maintaining high accuracy in inclusion screening. This case study involved a systematic review of 22,028 resources (identified from PsycINFO, Academic Search Ultimate, and Google) and a final data set of 268 relevant studies. AI screening was integral in effectively conducting multiple rounds of screening. However, findings also highlight challenges in AI-assisted qualitative data abstraction, underscoring the continued need for human expertise in complex coding tasks. The study contributes to the ongoing discourse on integrating AI into prevention science methodologies and offers insights for optimizing AI applications in systematic reviews.

Artificial Intelligence↗
PubMed2026

Dengue and chikungunya vaccines past, present and future: implications for travelers.

PURPOSE OF REVIEW: Novel vaccines for dengue and chikungunya viruses offer new prevention options against two globally important arboviral diseases. This review summarizes recent developments in vaccine licensure, implementation, real-world experience and research priorities, with emphasis on implications for both endemic populations and travelers. RECENT FINDINGS: Of the three live-attenuated dengue vaccines licensed to date, TAK-003 is authorized in >40 countries and Butantan-DV in Brazil, while manufacturing of CYD-TDV is discontinued. Long-term and postmarketing data continue to refine understanding of serotype-specific protection, waning immunity, and rare adverse events.For chikungunya, two single-dose vaccines are licensed-a live-attenuated vaccine (VLA1553) and virus-like particle vaccine (PXVX0317). Uptake is guided by emerging safety and effectiveness data, with each platform offering potential advantages in different settings.Further data on long-term protection, safety, effectiveness, use in vulnerable populations and integration into outbreak management and immunization systems is anticipated. SUMMARY: Dengue and chikungunya vaccines are increasingly being used in immunization programs and pretravel consultations. Further real-world data are needed-particularly for seronegative dengue vaccine recipients and older, immunocompromised or medically at-risk adults. Research priorities include developing single-dose, nonlive dengue vaccines suitable for high-risk groups, understanding long-term chikungunya vaccine performance, and exploring broader flaviviral or pan-arboviral platforms.

Humans↗
PubMed2026

Longitudinal Neurocognitive Changes for Patients With Hematologic Malignancies Undergoing Hematopoietic Stem Cell Transplantation: A Systematic Review With Structured Narrative Synthesis.

OBJECTIVES: Neurocognitive changes in hematological malignancies (HM) and as a sequela of hematopoietic stem cell transplantation (HSCT) remain under-recognized. These changes may substantially affect patients' quality of life. Therefore, this review systematically evaluated longitudinal neurocognitive changes in patients with HM undergoing HSCT. METHODS: Following PRISMA guidelines, PubMed, Scopus, and CINAHL were searched on October 30, 2025. Longitudinal studies assessing neurocognitive changes in patients with HM undergoing HSCT, with or without healthy controls, were included. Risk of bias was assessed using an adapted National Institutes of Health quality assessment tool for before-after studies. Effect sizes with 95% confidence intervals were calculated to quantify changes in neurocognitive performance. RESULTS: Nine of 2012 studies met the inclusion criteria, with overall moderate study quality. Improvements may occur post-HSCT; however, allogeneic HSCT and myeloablative conditioning were main risk factors identified for persistent cognitive decline. In line with white matter damage, executive function and attention/processing speed impairments likely represent core deficits, which may affect other cognitive impairments. Post-HSCT changes depend on task characteristics, cognitive load, and conditioning intensity. CONCLUSIONS: Future research should emphasize regular neurocognitive assessment to guide cognitive rehabilitation, implement pre-transplant cognitive rehabilitation strategies to mitigate post-HSCT cognitive decline, and enhance treatment outcomes.

Humans↗
PubMed2026

Relationship between participant-reported outcomes, residual beta cell function and metabolic parameters in youth with newly diagnosed type 1 diabetes.

AIMS/HYPOTHESIS: Clinical trials of interventions to preserve beta cell function in new-onset type 1 diabetes frequently employ participant-reported outcome measures (PROMs). However, the expected changes in PROMs scores immediately following diagnosis and their association with residual beta cell function, metabolic markers and continuous glucose monitoring (CGM) are unclear. METHODS: Repeated PROMs including Paediatric Quality of Life Inventory diabetes module (PedsQL) and hypoglycaemia fear survey (HFS) were recorded from participants aged 10-18 years with newly diagnosed type 1 diabetes and their parents in two clinical trials: CLOuD (N=97, hybrid closed loop [HCL] vs multiple daily injections [MDI]) and USTEKID (N=72, ustekinumab immunotherapy vs placebo). Scores were compared with serial mixed meal-stimulated C-peptide levels (AUC C-peptide), HbA1c and CGM data. RESULTS: PedsQL and HFS scores for children/adolescents and their parents showed wide variation between individuals but did not change substantially within individuals over the first 48 months from diagnosis. Baseline scores were highly predictive of scores at 12-48 months (p<0.001). PedsQL scores were higher (better) in those reported by children/adolescents than by their parents (p<0.01). In contrast, HFS scores were higher in parents than children (p<0.001), indicating more fear. Strong correlations were observed between child and parent scores (p<0.001). No significant improvement in these scores was detected following intervention (ustekinumab or HCL). Meta-analysis revealed modest but statistically significant associations between HbA1c and PedsQL (&#x3b2;(std)=-0.11; 95% CI -0.20, -0.03) and HFS (&#x3b2;(std)=0.11; 95% CI 0.00, 0.21), and between CGM time in range and PedsQL (&#x3b2;(std)=0.14; 95% CI 0.03, 0.26) but not HFS (&#x3b2;(std)=-0.05; 95% CI -0.16, 0.06). Beta cell function (AUC C-peptide) was strongly associated with HbA1c (&#x3b2;(std)=-0.29; 95% CI -0.39, -0.20) and CGM time in range (&#x3b2;(std)=0.41; 95% CI 0.30, 0.52). Higher beta cell function showed a trend towards better PedsQL (&#x3b2;(std)=0.11; 95% CI -0.03, 0.25) and lower HFS (&#x3b2;(std)=-0.05; 95% CI -0.17, 0.07) but this did not reach statistical significance. CONCLUSIONS/INTERPRETATION: PedsQL and HFS scores changed little during the first 48 months after diagnosis of type 1 diabetes. These scores showed modest but statistically significant associations with measures of glucose management (HbA1c and CGM time in range), whereas the relationships with residual beta cell function (C-peptide) were weaker and did not reach significance. The modest size of these effects suggests current PROMs capture only limited aspects of the clinical benefit associated with beta cell preservation. Future research should incorporate psychometric instruments that are specifically adapted for young people using modern diabetes technologies and undergoing disease-modifying therapy, to ensure outcomes are meaningfully represented in early-stage type 1 diabetes trials.

Adolescent↗
PubMed2026

Portable metagenomics for preventive surveillance and outbreak control in livestock and poultry: Pathogen detection, resistome profiling, and antimicrobial stewardship.

Conventional diagnostics for livestock and poultry outbreaks commonly rely on culture or targeted PCR panels, which may be too slow or too narrow to guide early control decisions. Portable metagenomics, particularly real-time nanopore sequencing, offers a route to broad pathogen detection, antimicrobial-resistance gene profiling, and outbreak investigation within an integrated workflow. This implementation-focused review evaluates how near-point-of-care metagenomics may support preventive veterinary medicine through earlier detection, surveillance, cohorting, biosecurity decisions, and antimicrobial stewardship. We synthesize sample-to-answer workflows for enteric and respiratory disease in food-producing animals, including sampling, nucleic-acid extraction, host depletion or target enrichment, library preparation, sequencing, bioinformatics, quality control, and interpretation. Applications in calf diarrhea, bovine respiratory disease, poultry outbreaks, mastitis, and resistome monitoring are considered alongside the central limitation that detection alone does not establish causation. Pathogen and resistance-gene signals must therefore be interpreted with clinical signs, lesions, epidemiology, controls, and confirmatory testing. We also propose a minimum reporting checklist, intended as a practical framework rather than a validated consensus standard. Portable metagenomics is not a replacement for conventional diagnostics, but appropriately validated workflows can reduce uncertainty during time-sensitive outbreaks and support more judicious antimicrobial use.

Animals↗
PubMed2026

The psychosocial supports and interventions accessed by family members of patients with developmental and epileptic encephalopathies: A systematic review.

AIM: Family members of patients with developmental and epileptic encephalopathies (DEEs) face profound emotional, social and practical challenges, yet little is known about how they access psychosocial support. We synthesised the literature on the psychosocial support accessed by family members of patients with DEEs, including evidence-based interventions. METHOD: Four databases were searched. Two reviewers independently screened and extracted data, appraised study quality (QualSyst Tool), and determined certainty of evidence (GRADE-CERQual Framework). Data were synthesised using inductive thematic analysis. RESULTS: 28 papers comprising 27 unique studies were included and methodological quality was high overall (median&#xa0;=&#xa0;0.91, IQR&#xa0;=&#xa0;0.85-1.00). Most studies focused on parent experiences; only two included siblings' perspectives. Families reported high psychological needs which were rarely met by psychological support. Clinicians rarely provided adequate information, quality communication or addressed mental health. Families valued respite care, but experienced barriers to access. Peer support was the most common and valued resource. Three studies tested interventions and appeared feasible and acceptable for parents. However, evidence for intervention effectiveness is preliminary and limited to small, uncontrolled pilot studies. INTERPRETATION: Gaps exist in psychosocial support provision for families of patients with DEEs, including insufficient research on siblings' and grandparents' needs, and lack of evidence-based interventions. We propose evidence-informed research and implementation strategies to address these gaps.

Humans↗
PubMed2026

The effectiveness of digital health interventions for type 2 diabetes in underserved populations: A systematic review and meta-analysis.

This systematic review and meta-analysis of 12 randomized controlled trials (1835 participants) evaluated whether digital health interventions (DHIs) improve glycemic control among underserved adults with type 2 diabetes (T2D), including racial/ethnic minority, low-income, Medicaid-insured, rural, and low-health-literacy populations. Searches of PubMed, Embase, and the Cochrane Central Register of Controlled Trials from inception to December 20, 2025 identified eligible parallel-group randomized controlled trials reporting change in hemoglobin A1c (HbA1c). Two reviewers independently screened studies, extracted data, and assessed risk of bias using the revised Cochrane Risk of Bias 2 tool. Random-effects meta-analysis showed that DHIs produced a modest but statistically significant HbA1c reduction versus control (mean difference, -0.37 %age points; 95% CI, -0.44 to -0.30; P&#x202f;<&#x202f;.0001; equivalent to -4.0&#x202f;mmol/mol). Heterogeneity was moderate-to-substantial (I&#xb2; = 69.9%). Subgroup analyses suggested directionally similar effects by population group and intervention modality, but interpretation was limited by study-level data and the small number of trials. Funnel-plot inspection and Egger's test (P&#x202f;=&#x202f;.31) did not suggest major small-study effects, although power was limited. Overall certainty for HbA1c was moderate. DHIs may support more equitable diabetes care when implemented with cultural tailoring, language access, digital-literacy support, and technology-access safeguards.

Humans↗
PubMed2026

Closed-loop insulin delivery for glycaemic control in hospitalised and perioperative adults: A systematic review and meta-analysis of randomised controlled trials.

We evaluated whether closed-loop insulin delivery improves glycaemic control in hospitalised and perioperative adults. PubMed/MEDLINE, Embase, CENTRAL, and ClinicalTrials.gov were searched from inception to 29 June 2026 for randomised controlled trials comparing closed-loop or automated insulin delivery with usual care or conventional insulin therapy. Random-effects meta-analyses were conducted; risk of bias was assessed using RoB 2 and certainty of evidence using GRADE. Seven trials involving 375 analysed participants were included. Closed-loop insulin delivery increased time in target glucose range by 23.91 percentage points (95% CI 19.40 to 28.43; I2&#xa0;=&#xa0;0%) and reduced mean glucose by 1.79&#xa0;mmol/L (95% CI 1.06 to 2.53 lower; I2&#xa0;=&#xa0;36.3%); certainty was moderate for both outcomes. Two trials involving 69 participants reported compatible participant-level data for clinically significant hyperglycaemia, and both estimates favoured closed-loop insulin delivery, although the evidence was exploratory and imprecise. No severe hypoglycaemic events occurred in either group, precluding reliable estimation of comparative safety. Closed-loop insulin delivery may improve glycaemic process measures, but larger pragmatic trials are needed to establish clinical benefits, safety, and implementation feasibility.

Humans↗
PubMed2026

Beyond Photometric Consistency: Addressing Loss Insensitivity to Depth Noise in Endoscopic Estimation via Error Calibration.

Self-supervised monocular depth estimation in endoscopy is fundamentally constrained by the ill-posed nature of photometric supervision. In this work, we identify a critical yet overlooked cause of this ambiguity: the inherent insensitivity of photometric loss to depth noise. To overcome this intrinsic limitation, we propose Depth Error Calibration Learning (DECL), a two-stage framework that suppresses prediction variance and mitigates residual errors in self-supervised depth estimation. In Stage I (Variance Reduction), a cyclic depth generation strategy produces multiple depth hypotheses for the input image. The per-pixel empirical variance is quantified and integrated into a dedicated variance loss term, which penalizes inconsistent predictions and encourages the network to generate more stable and reliable depth estimates. In Stage II (Bias Calibration), an image-conditioned diffusion model refines the Stage-I depth prior and mitigates structured residuals through iterative denoising, thereby improving geometric accuracy and global consistency. Extensive experiments on three public endoscopic datasets demonstrate that DECL achieves consistent improvements over representative self-supervised monocular depth estimation methods under the evaluated protocols. Moreover, ablation studies on two representative backbones indicate that DECL is not restricted to a single network implementation, while broader validation on additional backbone families remains necessary. The source code is publicly available at https://github.com/DavidLuBit/EndoDenoising.

Journal Article↗
PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗
PubMed2026

Prognostic value of the lactate-to-albumin ratio in adult sepsis: An updated systematic review of prognostic evidence.

BACKGROUND: The lactate-to-albumin ratio (LAR) has emerged as a potential prognostic biomarker in sepsis. This systematic review evaluated the prognostic value of LAR for mortality in adults with sepsis or septic shock. METHODS: PubMed/MEDLINE, Embase, Web of Science, Scopus, and the Cochrane Library were searched from inception through March 2026. Studies evaluating mortality-related prognostic performance of LAR in adults with sepsis or septic shock were included. Risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool. Adjusted odds ratios (ORs) and hazard ratios (HRs) were evaluated separately because of methodological heterogeneity. Discrimination was assessed using study-specific area under the curve (AUC), sensitivity, specificity, and LAR thresholds. RESULTS: Fourteen primary studies were included. Higher LAR was consistently associated with increased mortality across emergency department and intensive care populations. AUC values generally ranged from approximately 0.65 to 0.87, although one smaller cohort reported an AUC of 0.976. Several multivariable analyses demonstrated associations between higher LAR and mortality after adjustment for clinical covariates. Adjusted ORs and HRs were not pooled because of differences in LAR scaling, thresholds, mortality endpoints, and adjustment strategies. Considerable variability was observed in reported cut-offs and diagnostic performance. CONCLUSIONS: Higher LAR is associated with mortality in adult sepsis and may provide complementary prognostic information. However, clinical and methodological heterogeneity precludes a universal cut-off or single pooled adjusted effect. Standardized prospective multicenter studies are required before routine clinical implementation.

Humans↗