Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories.
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ABSTRACT:
SUBMITTER: Bhavani SV
PROVIDER: S-EPMC6680307 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Although thrombocytopenia on admission to the ICU is associated with increased in-hospital mortality in septic patients, the role of longitudinally measured platelet counts, which are dynamically changing, is unclear. We aimed to identify patterns of dynamic platelet count trajectories and evaluate their association with outcomes and thrombocytopenia in septic patients. We tested the longitudinal platelet trajectory patterns of sepsis patients within the first four days of ICU admission in the MIMIC-IV database and their association with 28-day mortality, and independently validated our findings in the eICU-CRD database. Statistical methods used included multivariate regression, propensity score analysis, doubly robust estimation, gradient boosting model, and inverse probability weighting to ensure the robustness of our findings. A total of 22,866 septic patients were included in our study. The trajectory analysis categorizes patients into ascending (AS), stable (ST), or descending (DS) patterns. The risk of 28-day mortality was increased in the DS patients (OR = 2.464, 95%CI 1.895-3.203, p < 0.001) and ST patients (OR = 1.302, 95%CI 1.067-1.589, p = 0.009) compared to AS patients. The AS patients had lower ICU length of stay (2.36 vs. 4.32, p < 0.001) and 28-day maximum SOFA scores (5.00 vs. 6.00, p < 0.001) than the DS patients, but had more ventilator-free days within 28 days than the DS group (26.00 vs. 24.00, p < 0.001). The mediating effect of thrombocytopenia was significant (p < 0.001 for the average causal mediation effect (ACME)). Longitudinal platelet trajectory was associated with risk-adjusted 28-day mortality among patients with sepsis and was proportionally mediated through thrombocytopenia.
| S-EPMC11364765 | biostudies-literature
Project description:ObjectivesWe recently found that distinct body temperature trajectories of infected patients correlated with survival. Understanding the relationship between the temperature trajectories and the host immune response to infection could allow us to immunophenotype patients at the bedside using temperature. The objective was to identify whether temperature trajectories have consistent associations with specific cytokine responses in two distinct cohorts of infected patients.DesignProspective observational study.SettingLarge academic medical center between 2013 and 2019.SubjectsTwo cohorts of infected patients: 1) patients in the ICU with septic shock and 2) hospitalized patients with Staphylococcus aureus bacteremia.InterventionsClinical data (including body temperature) and plasma cytokine concentrations were measured. Patients were classified into four temperature trajectory subphenotypes using their temperature measurements in the first 72 hours from the onset of infection. Log-transformed cytokine levels were standardized to the mean and compared with the subphenotypes in both cohorts.Measurements and main resultsThe cohorts consisted of 120 patients with septic shock (cohort 1) and 88 patients with S. aureus bacteremia (cohort 2). Patients from both cohorts were classified into one of four previously validated temperature subphenotypes: "hyperthermic, slow resolvers" (n = 19 cohort 1; n = 13 cohort 2), "hyperthermic, fast resolvers" (n = 18 C1; n = 24 C2), "normothermic" (n = 54 C1; n = 31 C2), and "hypothermic" (n = 29 C1; n = 20 C2). Both "hyperthermic, slow resolvers" and "hyperthermic, fast resolvers" had high levels of G-CSF, CCL2, and interleukin-10 compared with the "hypothermic" group when controlling for cohort and timing of cytokine measurement (p < 0.05). In contrast to the "hyperthermic, slow resolvers," the "hyperthermic, fast resolvers" showed significant decreases in the levels of several cytokines over a 24-hour period, including interleukin-1RA, interleukin-6, interleukin-8, G-CSF, and M-CSF (p < 0.001).ConclusionsTemperature trajectory subphenotypes are associated with consistent cytokine profiles in two distinct cohorts of infected patients. These subphenotypes could play a role in the bedside identification of cytokine profiles in patients with sepsis.
| S-EPMC7837282 | biostudies-literature
Project description:ObjectiveMany healthcare systems employ population-based risk scores to prospectively identify patients at high risk of poor outcomes, but it is unclear whether single point-in-time scores adequately represent future risk. We sought to identify and characterize latent subgroups of high-risk patients based on risk score trajectories.Study designObservational study of 7289 patients discharged from Veterans Health Administration (VA) hospitals during a 1-week period in November 2012 and categorized in the top 5th percentile of risk for hospitalization.MethodsUsing VA administrative data, we calculated weekly risk scores using the validated Care Assessment Needs model, reflecting the predicted probability of hospitalization. We applied the non-parametric k-means algorithm to identify latent subgroups of patients based on the trajectory of patients' hospitalization probability over a 2-year period. We then compared baseline sociodemographic characteristics, comorbidities, health service use, and social instability markers between identified latent subgroups.ResultsThe best-fitting model identified two subgroups: moderately high and persistently high risk. The moderately high subgroup included 65% of patients and was characterized by moderate subgroup-level hospitalization probability decreasing from 0.22 to 0.10 between weeks 1 and 66, then remaining constant through the study end. The persistently high subgroup, comprising the remaining 35% of patients, had a subgroup-level probability increasing from 0.38 to 0.41 between weeks 1 and 52, and declining to 0.30 at study end. Persistently high-risk patients were older, had higher prevalence of social instability and comorbidities, and used more health services.ConclusionsOn average, one third of patients initially identified as high risk stayed at very high risk over a 2-year follow-up period, while risk for the other two thirds decreased to a moderately high level. This suggests that multiple approaches may be needed to address high-risk patient needs longitudinally or intermittently.
| S-EPMC6258600 | biostudies-literature
Project description:COVID-19-associated respiratory failure offers the unprecedented opportunity to evaluate the differential host response to a uniform pathogenic insult. Understanding whether there are distinct subphenotypes of severe COVID-19 may offer insight into its pathophysiology. Sequential Organ Failure Assessment (SOFA) score is an objective and comprehensive measurement that measures dysfunction severity of six organ systems, i.e., cardiovascular, central nervous system, coagulation, liver, renal, and respiration. Our aim was to identify and characterize distinct subphenotypes of COVID-19 critical illness defined by the post-intubation trajectory of SOFA score. Intubated COVID-19 patients at two hospitals in New York city were leveraged as development and validation cohorts. Patients were grouped into mild, intermediate, and severe strata by their baseline post-intubation SOFA. Hierarchical agglomerative clustering was performed within each stratum to detect subphenotypes based on similarities amongst SOFA score trajectories evaluated by Dynamic Time Warping. Distinct worsening and recovering subphenotypes were identified within each stratum, which had distinct 7-day post-intubation SOFA progression trends. Patients in the worsening suphenotypes had a higher mortality than those in the recovering subphenotypes within each stratum (mild stratum, 29.7% vs. 10.3%, p = 0.033; intermediate stratum, 29.3% vs. 8.0%, p = 0.002; severe stratum, 53.7% vs. 22.2%, p < 0.001). Pathophysiologic biomarkers associated with progression were distinct at each stratum, including findings suggestive of inflammation in low baseline severity of illness versus hemophagocytic lymphohistiocytosis in higher baseline severity of illness. The findings suggest that there are clear worsening and recovering subphenotypes of COVID-19 respiratory failure after intubation, which are more predictive of outcomes than baseline severity of illness. Distinct progression biomarkers at differential baseline severity of illness suggests a heterogeneous pathobiology in the progression of COVID-19 respiratory failure.
| S-EPMC8342520 | biostudies-literature
Project description:OBJECTIVES:To distinguish characteristics of Medicare beneficiaries who will have an acute inpatient admission for sepsis from those who have an inpatient admission without sepsis, and to describe their further trajectories during and subsequent to those inpatient admissions. DESIGN:Analysis of paid Medicare claims via the Centers for Medicare and Medicaid Services DataLink Project. SETTING:All U.S. acute care hospitals, excepting federal hospitals (Veterans Administration and Defense Health Agency). PATIENTS:Medicare beneficiaries, 2012-2018, with an inpatient hospital admission including one or more explicit sepsis codes. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Prevalent diagnoses in the year prior to the inpatient admission; healthcare contacts in the week prior to the inpatient admission; discharges, transfers, readmissions, and deaths (trajectories) for 6 months following discharge from the inpatient admission. Beneficiaries with no sepsis inpatient hospital admission for a year prior to an index hospital admission for sepsis were nearly indistinguishable by accumulated diagnostic codes from beneficiaries who had an index hospital admission without sepsis. Although the timing of healthcare services in the week prior to inpatient hospital admission was similar among beneficiaries who would be admitted for sepsis versus those whose inpatient admission did not include a sepsis code, the setting differed: beneficiaries destined for a sepsis admission were more likely to have received skilled nursing or unskilled nursing (e.g., nursing aide for activities of daily living) care. In contrast, comparing beneficiaries who had been free of any inpatient admission for an entire year and then required an inpatient admission, acute inpatient stays that included a sepsis code led to more than three times as many deaths within 1 week of discharge, with more admissions to skilled nursing facilities and fewer discharges to home. Comparing all beneficiaries who were admitted to a skilled nursing facility after an inpatient hospital admission, those who had sepsis coded during the index admission were more likely to die in the skilled nursing facility; more likely to be readmitted to an acute inpatient hospital and subsequently die in that setting; or if they survive to discharge from the skilled nursing facility, they are more likely to go next to a custodial nursing home. CONCLUSIONS:Although Medicare beneficiaries destined for an inpatient hospital admission with a sepsis code are nearly indistinguishable by other diagnostic codes from those whose admissions will not have a sepsis code, their healthcare trajectories following the admission are worse. This suggests that an inpatient stay that included a sepsis code not only identifies beneficiaries who were less resilient to infection but also signals increased risk for worsening health, for mortality, and for increased use of advanced healthcare services during and postdischarge along with an increased likelihood of an inpatient hospital readmission.
| S-EPMC7017944 | biostudies-literature
Project description:BackgroundHospitalized patients with severe COVID-19 follow heterogeneous clinical trajectories, requiring different levels of respiratory support and experiencing diverse clinical outcomes. Differences in host immune responses to SARS-CoV-2 infection may account for the heterogeneous clinical course, but we have limited data on the dynamic evolution of systemic biomarkers and related subphenotypes. Improved understanding of the dynamic transitions of host subphenotypes in COVID-19 may allow for improved patient selection for targeted therapies.Research questionWe examined the trajectories of host-response profiles in severe COVID-19 and evaluated their prognostic impact on clinical outcomes.Study design and methodsIn this prospective observational study, we enrolled 323 inpatients with COVID-19 receiving different levels of baseline respiratory support: (1) low-flow oxygen (37%), (2) noninvasive ventilation (NIV) or high-flow oxygen (HFO; 29%), (3) invasive mechanical ventilation (27%), and (4) extracorporeal membrane oxygenation (7%). We collected plasma samples on enrollment and at days 5 and 10 to measure host-response biomarkers. We classified patients by inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker, and subphenotype trajectories and outcomes during hospitalization.ResultsIL-6, procalcitonin, and angiopoietin 2 persistently were elevated in patients receiving higher levels of respiratory support, whereas soluble receptor of advanced glycation end products (sRAGE) levels displayed the inverse pattern. Patients receiving NIV or HFO at baseline showed the most dynamic clinical trajectory, with 24% eventually requiring intubation and exhibiting worse 60-day mortality than patients receiving invasive mechanical ventilation at baseline (67% vs 35%; P < .0001). sRAGE levels predicted NIV failure and worse 60-day mortality for patients receiving NIV or HFO, whereas IL-6 levels were predictive in all patients regardless of level of support (P < .01). Patients classified to a hyperinflammatory subphenotype at baseline (< 10%) showed worse 60-day survival (P < .0001) and 50% of them remained classified as hyperinflammatory at 5 days after enrollment.InterpretationLongitudinal study of the systemic host response in COVID-19 revealed substantial and predictive interindividual variability influenced by baseline levels of respiratory support.
| S-EPMC10798236 | biostudies-literature
Project description:RationaleSepsis is a leading cause of death and disability whose heterogeneity is often cited as a key impediment to translational progress.ObjectivesTo test the hypothesis that there are consequential and significant differences in sepsis outcomes that result from differences in a patient's clinical course leading up to sepsis hospitalization.MethodsWe conducted an observational cohort study of U.S. Health and Retirement Study (HRS) participants in Medicare (1998-2012) and U.S. Department of Veterans Affairs beneficiaries (2009). Using latent profile analysis, we identified patient subtypes based on trajectory of presepsis healthcare facility use. Subtypes were identified in the derivation cohort (1,512 sepsis hospitalizations among earlier HRS participants), then validated them in two additional cohorts (1,992 sepsis hospitalizations among later HRS participants; 32,525 sepsis hospitalizations among U.S. Department of Veterans Affairs beneficiaries). We measured the association between presepsis path and 90-day mortality using chi-square tests and multivariable logistic regression.ResultsWe identified three subtypes: low use of inpatient healthcare facilities, comprising 84% of the derivation cohort; rising use, 12%; and high use, 4%. The shape and distribution of presepsis trajectories were similar in all three cohorts. In the derivation cohort, 90-day mortality differed by presepsis trajectory as follows: 38% (low use), 63% (rising use), and 48% (high use) (P < 0.001). This association persisted in the validation cohorts (P < 0.001 for each). The rising use class remained an independent predictor of mortality after adjustment for potential confounders, including detailed physiologic data.ConclusionsIn national cohorts of patients with sepsis, we have shown that several distinct paths into sepsis exist. These paths, identified by trajectories of presepsis healthcare use, are predictive of 90-day mortality.
| S-EPMC6344453 | biostudies-literature
Project description:Time is a crucial parameter in the assessment of comorbidities in population-based studies, as it permits to identify more complex disease patterns apart from the pairwise disease associations. So far, it has been, either, completely ignored or only, taken into account by assessing the temporal directionality of identified comorbidity pairs. In this work, a novel time-analysis framework is presented for large-scale comorbidity studies. The disease-history vectors of patients of a regional Spanish health dataset are represented as time sequences of ordered disease diagnoses. Statistically significant pairwise disease associations are identified and their temporal directionality is assessed. Subsequently, an unsupervised clustering algorithm, based on Dynamic Time Warping, is applied on the common disease trajectories in order to group them according to the temporal patterns that they share. The proposed methodology for the temporal assessment of such trajectories could serve as the preliminary basis of a disease prediction system.
| S-EPMC5844976 | biostudies-literature
Project description:The Sepsis 6 is an internationally accepted management bundle that, when initiated within one hour of identifying sepsis, can reduce morbidity and mortality. This management bundle was advocated by the Scottish Patient Safety Programme as part of its Acute Adult campaign launched in 2008 and adopted by NHS Tayside in 2012. Despite this, the Emergency Department (ED) of Ninewells Hospital, a tertiary referral centre and major teaching hospital in Scotland, was displaying poor success in the Sepsis 6. We therefore set out to improve compliance by evaluating the application of all aspects of the NHS Tayside Sepsis 6 bundle within one hour of ED triage time, to identify what human factors may influence achieving the one hour The Sepsis 6 bundle. This allowed us to tailor a number of specific interventions including educational sessions, regular audit and personal feedback and check list Sepsis 6 sticker. These interventions promoted a steady increase in compliance from an initial rate of 51.0% to 74.3%. The project highlighted that undifferentiated patients create a challenge in initiating the Sepsis 6. Pyrexia is a key human factor-trigger for recognising sepsis with initial nursing assessment being vital in recognition and identifying the best area (resus) of the department to manage severely septic patients. EDs need to recognise these challenges and develop educational and feedback plans for staff and utilise available resources to maximise the Sepsis 6 compliance.
| S-EPMC4863434 | biostudies-other
Project description:Controlling human pathogenic bacteria is a worldwide problem due to increasing bacterial resistance. This has prompted a number of studies investigating peptides isolated from marine animals as a possible alternative for control of human pathogen infections. Clavanins are antimicrobial peptides isolated from the marine tunicate Styela clava, showing 23 amino acid residues in length, cationic properties, and also high bactericidal activity. In spite of clear benefits from the use of peptides, currently 95% of peptide properties have limited pharmaceutical applicability, such as low solubility and short half-life in the circulatory system. Here, nanobiotechnology was used to encapsulate clavanin A in order to develop nanoantibiotics against bacterial sepsis. Clavanin was nanostructured using EUDRAGIT(®) L 100-55 and RS 30 D solution (3:1 w:w). Atomic force, scanning electron microscopy and dynamic light scattering showed nanoparticles ranging from 120 to 372 nm in diameter, with a zeta potential of -7.16 mV and a polydispersity index of 0.123. Encapsulation rate of 98% was assessed by reversed-phase chromatography. In vitro bioassays showed that the nanostructured clavanin was partially able to control development of Staphylococcus aureus, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Furthermore, nanostructures did not show hemolytic activity. In vivo sepsis bioassays were performed using C57BL6 mice strain inoculated with a polymicrobial suspension. Assays led to 100% survival rate under sub-lethal sepsis assays and 40% under lethal sepsis assays in the presence of nanoformulated clavanin A until the seventh day of the experiment. Data here reported indicated that nanostructured clavanin A form shows improved antimicrobial activity and has the potential to be used to treat polymicrobial infections.
| S-EPMC4222983 | biostudies-literature