IMPORTANCE: Sepsis is a heterogeneous syndrome. Identification of distinct clinical phenotypes may allow more precise therapy and improve care. OBJECTIVE: To derive sepsis phenotypes from clinical ...data, determine their reproducibility and correlation with host-response biomarkers and clinical outcomes, and assess the potential causal relationship with results from randomized clinical trials (RCTs). DESIGN, SETTINGS, AND PARTICIPANTS: Retrospective analysis of data sets using statistical, machine learning, and simulation tools. Phenotypes were derived among 20 189 total patients (16 552 unique patients) who met Sepsis-3 criteria within 6 hours of hospital presentation at 12 Pennsylvania hospitals (2010-2012) using consensus k means clustering applied to 29 variables. Reproducibility and correlation with biological parameters and clinical outcomes were assessed in a second database (2013-2014; n = 43 086 total patients and n = 31 160 unique patients), in a prospective cohort study of sepsis due to pneumonia (n = 583), and in 3 sepsis RCTs (n = 4737). EXPOSURES: All clinical and laboratory variables in the electronic health record. MAIN OUTCOMES AND MEASURES: Derived phenotype (α, β, γ, and δ) frequency, host-response biomarkers, 28-day and 365-day mortality, and RCT simulation outputs. RESULTS: The derivation cohort included 20 189 patients with sepsis (mean age, 64 SD, 17 years; 10 022 50% male; mean maximum 24-hour Sequential Organ Failure Assessment SOFA score, 3.9 SD, 2.4). The validation cohort included 43 086 patients (mean age, 67 SD, 17 years; 21 993 51% male; mean maximum 24-hour SOFA score, 3.6 SD, 2.0). Of the 4 derived phenotypes, the α phenotype was the most common (n = 6625; 33%) and included patients with the lowest administration of a vasopressor; in the β phenotype (n = 5512; 27%), patients were older and had more chronic illness and renal dysfunction; in the γ phenotype (n = 5385; 27%), patients had more inflammation and pulmonary dysfunction; and in the δ phenotype (n = 2667; 13%), patients had more liver dysfunction and septic shock. Phenotype distributions were similar in the validation cohort. There were consistent differences in biomarker patterns by phenotype. In the derivation cohort, cumulative 28-day mortality was 287 deaths of 5691 unique patients (5%) for the α phenotype; 561 of 4420 (13%) for the β phenotype; 1031 of 4318 (24%) for the γ phenotype; and 897 of 2223 (40%) for the δ phenotype. Across all cohorts and trials, 28-day and 365-day mortality were highest among the δ phenotype vs the other 3 phenotypes (P < .001). In simulation models, the proportion of RCTs reporting benefit, harm, or no effect changed considerably (eg, varying the phenotype frequencies within an RCT of early goal-directed therapy changed the results from >33% chance of benefit to >60% chance of harm). CONCLUSIONS AND RELEVANCE: In this retrospective analysis of data sets from patients with sepsis, 4 clinical phenotypes were identified that correlated with host-response patterns and clinical outcomes, and simulations suggested these phenotypes may help in understanding heterogeneity of treatment effects. Further research is needed to determine the utility of these phenotypes in clinical care and for informing trial design and interpretation.
•The marginal cost of renewable generation is deduced by generation uncertainty.•Value of single charging/discharging action for energy storage can be quantified.•A three-tiered optimization ...maximizes profits for participants within micro-grids.•The profits for owners and aggregators are cleared through a win-win framework.
The fast deployment of distributed energy resources in the electric power system has highlighted the need for an efficient energy trading transactive model, without the need for centralized dispatch. In this field, a particular challenge is the determination of an effective pricing scheme that is able to produce benefits for all participants. In this paper, a novel dynamic pricing methodology is presented, offering a market-oriented means to drive decentralized energy trading and to optimize financial benefits for owners of distributed energy resources. Firstly, a price-responsive model for each type of distributed energy resource is investigated. Particularly, the decoupled State of Charge function is proposed to calculate the value of a single charging/discharging action for energy storage systems. In addition, an adaptable three-tiered framework is designed, including micro-grid balancing, aggregator scheduling, and trading optimization. By launching Tier I, II, and III, the spot prices for participants are iteratively updated and optimized in inner-micro-grid, inner-aggregator, and inter-aggregators level. The framework is able to maximize the financial savings from renewable energy, and meanwhile, provide a dynamic price signal to assist stakeholders in determining response actions and trading strategies. A realistic case is simulated using Java Agent Development framework based multi-agent modeling. The results indicate that the presented methodology enables decentralized energy trading and permits easier marketization of micro-grids with a high share of distributed energy resources.
A concise, efficient and modular approach to the tylophora alkaloids is described, a family of potent cytotoxic agents that are equally effective against drug sensitive and multidrug resistant cancer ...cell lines. The advantages of the chosen route are illustrated by the total syntheses of the phenanthroquinolizidine cryptopleurine (1) and the phenanthroindolizidines (−)‐antofine (2), (−)‐tylophorine (3), and their only recently isolated congener (−)‐ficuseptine C (4). The key steps consist in a Suzuki cross‐coupling between a (commercial) boronic acid and a simple aryl‐1,2‐dihalide followed by elaboration of the resulting products into the corresponding 2‐alkynyl‐biphenyl derivatives 27, 33, 41 and 46. The latter undergo PtCl2‐catalyzed cycloisomerizations with formation of the functionalized phenanthrenes 28, 34, 42 and 47, which were transformed into the targeted alkaloids by a deprotection/Pictet–Spengler annulation tandem. Due to the flexibility and robust character of this approach, it might enable a systematic exploration of the pharmacological profile of this promising class of bioactive natural products.
Potent cytotoxicity against drug sensitive as well as multidrug resistant cancer cell lines is the most striking physiological property of various tylophora alkaloids. To facilitate a more systematic evaluation of this family of natural products, a flexible and concise synthesis route has been developed based on metal catalyzed cross‐coupling and cycloisomerization reactions as the key steps. The advantages of this approach are evident from the total synthesis of four representative members of this series (see graphic).
Background
Proposed phenotypes have recently been identified in cardiogenic shock (CS) populations using unsupervised machine learning clustering methods. We sought to validate these phenotypes in a ...mixed cardiac intensive care unit (CICU) population of patients with CS.
Methods
We included Mayo Clinic CICU patients admitted from 2007 to 2018 with CS. Agnostic K means clustering was used to assign patients to three clusters based on admission values of estimated glomerular filtration rate, bicarbonate, alanine aminotransferase, lactate, platelets, and white blood cell count. In‐hospital mortality and 1‐year mortality were analyzed using logistic regression and Cox proportional‐hazards models, respectively.
Results
We included 1498 CS patients with a mean age of 67.8 ± 13.9 years, and 37.1% were females. The acute coronary syndrome was present in 57.3%, and cardiac arrest was present in 34.0%. Patients were assigned to clusters as follows: Cluster 1 (noncongested), 603 (40.2%); Cluster 2 (cardiorenal), 452 (30.2%); and Cluster 3 (hemometabolic), 443 (29.6%). Clinical, laboratory, and echocardiographic characteristics differed across clusters, with the greatest illness severity in Cluster 3. Cluster assignment was associated with in‐hospital mortality across subgroups. In‐hospital mortality was higher in Cluster 3 (adjusted odds ratio OR: 2.6 vs. Cluster 1 and adjusted OR: 2.0 vs. Cluster 2, both p < 0.001). Adjusted 1‐year mortality was incrementally higher in Cluster 3 versus Cluster 2 versus Cluster 1 (all p < 0.01).
Conclusions
We observed similar phenotypes in CICU patients with CS as previously reported, identifying a gradient in both in‐hospital and 1‐year mortality by cluster. Identifying these clinical phenotypes can improve mortality risk stratification for CS patients beyond standard measures.
Cardiac Function Before Sepsis and Clinical Outcomes Iyer, Stuthi; Kennedy, Jason N; Jentzer, Jacob C ...
JAMA : the journal of the American Medical Association,
05/2024, Letnik:
331, Številka:
17
Journal Article
Recenzirano
This cohort study characterizes heterogeneity in cardiac function prior to sepsis and describes associations with hospitalization outcomes and mortality.
Excavations at Kenan Tepe by the Upper Tigris Archaeological Research Project (UTARP) revealed four phases of Ubaid period occupation. The goal of this paper is to place the final phase of occupation ...at the site, Kenan Tepe Ubaid phase 4 (KTU phase 4), into a broader regional context, and to situate the KTU phase 4 ceramic assemblage within the Ubaid to post-Ubaid transition (Late Chalcolithic 1) of greater Mesopotamia. Recent excavations and studies from throughout Greater Mesopotamia have highlighted the local variation of this transition. This paper will compare the materials from KTU phase 4 to other sites in the Upper Tigris region to provide an overview of regional character during this time in the Tigris Valley in southeastern Turkey. Additionally, I will present the results of the use-alteration analysis from the KTU phase 4 occupation to outline the function of ceramics and the daily practices of the inhabitants of Kenan Tepe. This analysis could aid in identifying regional variations of ceramic use that can highlight differences in social and economic organizations within communities during the Ubaid to post-Ubaid transition.
Sepsis is common, deadly, and heterogenous. Prior analyses of patients with sepsis and septic shock in New York State showed a risk-adjusted association between more rapid antibiotic administration ...and bundled care completion, but not an intravenous fluid bolus, with reduced in-hospital mortality. However, it is unknown if clinically identifiable sepsis subtypes modify these associations.
Secondary analysis of patients with sepsis and septic shock enrolled in the New York State Department of Health cohort from January 1, 2015 to December 31, 2016. Patients were classified as clinical sepsis subtypes (α, β, γ, δ-types) using the Sepsis ENdotyping in Emergency CAre (SENECA) approach. Exposure variables included time to 3-h sepsis bundle completion, antibiotic administration, and intravenous fluid bolus completion. Then logistic regression models evaluated the interaction between exposures, clinical sepsis subtypes, and in-hospital mortality.
55,169 hospitalizations from 155 hospitals were included (34% α, 30% β, 19% γ, 17% δ). The α-subtype had the lowest (N = 1,905, 10%) and δ-subtype had the highest (N = 3,776, 41%) in-hospital mortality. Each hour to completion of the 3-h bundle (aOR, 1.04 95%CI, 1.02-1.05) and antibiotic initiation (aOR, 1.03 95%CI, 1.02-1.04) was associated with increased risk-adjusted in-hospital mortality. The association differed across subtypes (p-interactions < 0.05). For example, the outcome association for the time to completion of the 3-h bundle was greater in the δ-subtype (aOR, 1.07 95%CI, 1.05-1.10) compared to α-subtype (aOR, 1.02 95%CI, 0.99-1.04). Time to intravenous fluid bolus completion was not associated with risk-adjusted in-hospital mortality (aOR, 0.99 95%CI, 0.97-1.01) and did not differ among subtypes (p-interaction = 0.41).
Timely completion of a 3-h sepsis bundle and antibiotic initiation was associated with reduced risk-adjusted in-hospital mortality, an association modified by clinically identifiable sepsis subtype.
Despite the popularity of boron and silicon allylation reagents in stereocontrolled synthesis, they suffer from a number of inherent limitations that have slowed down their development as synthetic ...tools for nucleophilic additions to carbonyl compounds and imine derivatives. These limitations are the low reactivity and diastereoselectivity of allyl trialkylsilane reagents, and the lack of catalytic systems for the activation and substoichiometric control of enantioselectivity in the additions of allyl boron reagents. To develop more efficient and general methods for the control of absolute stereochemistry in the resulting homoallylic alcohols, new approaches aimed at solving the problem of activation of allylic boron and silicon reagents are needed. This Minireview describes a number of recent approaches that have been devised to address this problem.
The activation of allyl boron and allyl silicon reagents is a subject of much current interest. Recent strategies are based on increasing the reactivity of the reagents by varying the remaining substituents on the boron or silicon center, or by using a Lewis acid or a Lewis base additive to accelerate reactions with carbonyl compounds or imine derivatives to make homoallylic alcohols and amines in a stereocontrolled fashion (see scheme).
The integration of an ever-growing proportion of large-scale distributed renewable generation has increased the probability of maloperation of the traditional RoCoF and vector shift relays. With ...reduced inertia due to nonsynchronous penetration in a power grid, system-wide disturbances have forced the utility industry to design advanced protection schemes to prevent system degradation and avoid cascading outages leading to widespread blackouts. This paper explores a novel adaptive nonlinear approach applied to islanding detection, based on wide-area phase-angle measurements. This is challenging since the voltage phase angles from different locations exhibit not only strong nonlinear but also time-varying characteristics. The adaptive nonlinear technique, called moving window kernel principal component analysis, is proposed to model the time-varying and nonlinear trends in the voltage-phase angle data. The effectiveness of the technique is exemplified using DigSilent simulated cases and real test cases recorded from the Great Britain and Ireland power systems by the OpenPMU project.
All of medicine aspires to be precise, where a greater understanding of individual data will lead to personalized treatment and improved outcomes. Prompted by specific examples in oncology, the field ...of critical care may be tempted to envision that complex, acute syndromes could bend to a similar reductionist philosophy-where single mutations could identify and target our critically ill patients for treatment. However, precision medicine faces many challenges in critical care. These include confusion about terminology, uncertainty about how to divide patients into discrete groups, the challenges of multi-morbidity, scale, and the need for timely interventions. This review addresses these challenges and provides a translational roadmap spanning preclinical work to identify putative treatment targets, novel designs for clinical trials, and the integration of the electronic health record to implement precision critical care for all.
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