Joint modeling in presence of informative censoring on the retrospective time scale with application to palliative care research.

Joint modeling of longitudinal data such as quality of life data and survival data is important for palliative care researchers to draw efficient inferences because it can account for the associations between those two types of data. Modeling quality of life on a retrospective from death time scale is useful for investigators to interpret the analysis results of palliative care studies which have relatively short life expectancies. However, informative censoring remains a complex challenge for modeling quality of life on the retrospective time scale although it has been addressed for joint models on the prospective time scale. To fill this gap, we develop a novel joint modeling approach that can address the challenge by allowing informative censoring events to be dependent on patients' quality of life and survival through a random effect. There are two sub-models in our approach: a linear mixed effect model for the longitudinal quality of life and a competing-risk model for the death time and dropout time that share the same random effect as the longitudinal model. Our approach can provide unbiased estimates for parameters of interest by appropriately modeling the informative censoring time. Model performance is assessed with a simulation study and compared with existing approaches. A real-world study is presented to illustrate the application of the new approach.

Clinical Trajectories of Acute Kidney Injury in Surgical Sepsis: A Prospective Observational Study.

OBJECTIVE: To characterize endothelial function, inflammation, and immunosuppression in surgical patients with distinct clinical trajectories of AKI and to determine the impact of persistent kidney injury and renal non-recovery on clinical outcomes, resource utilization, and long-term disability and survival. SUMMARY OF BACKGROUND DATA: AKI is associated with increased healthcare costs and mortality. Trajectories that account for duration and recovery of AKI have not been described for sepsis patients, who are uniquely vulnerable to renal dysfunction. METHODS: This prospective observational study included 239 sepsis patients admitted and enrolled between January 2015 and July 2017. Kidney Disease: Improving Global Outcomes (KDIGO) and Acute Disease Quality Initiative (ADQI) criteria were used to classify subjects as having no AKI, rapidly reversed AKI, persistent AKI with renal recovery, or persistent AKI without renal recovery. Serial biomarker profiles, clinical outcomes, resource utilization, and long-term physical performance status and survival were compared among AKI trajectories. RESULTS: Sixty-two percent of the study population developed AKI. Only one-third of AKI episodes rapidly reversed within 48 hours; the remaining had persistent AKI, among which 57% did not have renal recovery by discharge. One-year survival and proportion of subjects fully active 1 year after sepsis was lowest among patients with persistent AKI compared with other groups. Long-term mortality hazard rates were 5-fold higher for persistent AKI without renal recovery compared with no AKI. CONCLUSIONS: Among critically ill surgical sepsis patients, persistent AKI and the absence of renal recovery are associated with distinct early and sustained immunologic and endothelial biomarker signatures and decreased long-term physical function and survival.

Early Biomarker Signatures in Surgical Sepsis.

INTRODUCTION: Sepsis has complex, time-sensitive pathophysiology and important phenotypic subgroups. The objective of this study was to use machine learning analyses of blood and urine biomarker profiles to elucidate the pathophysiologic signatures of subgroups of surgical sepsis patients. METHODS: This prospective cohort study included 243 surgical sepsis patients admitted to a quaternary care center between January 2015 and June 2017. We applied hierarchical clustering to clinical variables and 42 blood and urine biomarkers to identify phenotypic subgroups in a development cohort. Clinical characteristics and short-term and long-term outcomes were compared between clusters. A naïve Bayes classifier predicted cluster labels in a validation cohort. RESULTS: The development cohort contained one cluster characterized by early organ dysfunction (cluster I, n = 18) and one cluster characterized by recovery (cluster II, n = 139). Cluster I was associated with higher Acute Physiologic Assessment and Chronic Health Evaluation II (30 versus 16, P < 0.001) and SOFA scores (13 versus 5, P < 0.001), greater prevalence of chronic cardiovascular and renal disease (P < 0.001) and septic shock (78% versus 17%, P < 0.001). Cluster I had higher mortality within 14 d of sepsis onset (11% versus 1.5%, P = 0.001) and within 1 y (44% versus 20%, P = 0.032), and higher incidence of chronic critical illness (61% versus 30%, P = 0.001). The Bayes classifier achieved 95% accuracy and identified two clusters that were similar to development cohort clusters. CONCLUSIONS: Machine learning analyses of clinical and biomarker variables identified an early organ dysfunction sepsis phenotype characterized by inflammation, renal dysfunction, endotheliopathy, and immunosuppression, as well as poor short-term and long-term clinical outcomes.

Old Mice Demonstrate Organ Dysfunction as well as Prolonged Inflammation, Immunosuppression, and Weight Loss in a Modified Surgical Sepsis Model.

OBJECTIVES: Our goal was to "reverse translate" the human response to surgical sepsis into the mouse by modifying a widely adopted murine intra-abdominal sepsis model to engender a phenotype that conforms to current sepsis definitions and follows the most recent expert recommendations for animal preclinical sepsis research. Furthermore, we aimed to create a model that allows the study of aging on the long-term host response to sepsis. DESIGN: Experimental study. SETTING: Research laboratory. SUBJECTS: Young (3-5 mo) and old (18-22 mo) C57BL/6j mice. INTERVENTIONS: Mice received no intervention or were subjected to polymicrobial sepsis with cecal ligation and puncture followed by fluid resuscitation, analgesia, and antibiotics. Subsets of mice received daily chronic stress after cecal ligation and puncture for 14 days. Additionally, modifications were made to ensure that "Minimum Quality Threshold in Pre-Clinical Sepsis Studies" recommendations were followed. MEASUREMENTS AND MAIN RESULTS: Old mice exhibited increased mortality following both cecal ligation and puncture and cecal ligation and puncture + daily chronic stress when compared with young mice. Old mice developed marked hepatic and/or renal dysfunction, supported by elevations in plasma aspartate aminotransferase, blood urea nitrogen, and creatinine, 8 and 24 hours following cecal ligation and puncture. Similar to human sepsis, old mice demonstrated low-grade systemic inflammation 14 days after cecal ligation and puncture + daily chronic stress and evidence of immunosuppression, as determined by increased serum concentrations of multiple pro- and anti-inflammatory cytokines and chemokines when compared with young septic mice. In addition, old mice demonstrated expansion of myeloid-derived suppressor cell populations and sustained weight loss following cecal ligation and puncture + daily chronic stress, again similar to the human condition. CONCLUSIONS: The results indicate that this murine cecal ligation and puncture + daily chronic stress model of surgical sepsis in old mice adhered to current Minimum Quality Threshold in Pre-Clinical Sepsis Studies guidelines and met Sepsis-3 criteria. In addition, it effectively created a state of persistent inflammation, immunosuppression, and weight loss, thought to be a key aspect of chronic sepsis pathobiology and increasingly more prevalent after human sepsis.

Prognostic value of NT-proBNP levels in the acute phase of sepsis on lower long-term physical function and muscle strength in sepsis survivors.

BACKGROUND: Sepsis survivors often develop chronic critical illness (CCI) and demonstrate the persistent inflammation, immunosuppression, and catabolism syndrome predisposing them to long-term functional limitations and higher mortality. There is a need to identify biomarkers that can predict long-term worsening of physical function to be able to act early and prevent mobility loss. N-terminal pro-brain natriuretic peptide (NT-proBNP) is a well-accepted biomarker of cardiac overload, but it has also been shown to be associated with long-term physical function decline. We explored whether NT-proBNP blood levels in the acute phase of sepsis are associated with physical function and muscle strength impairment at 6 and 12 months after sepsis onset. METHODS: This is a retrospective analysis conducted in 196 sepsis patients (aged 18-86 years old) as part of the University of Florida (UF) Sepsis and Critical Illness Research Center (SCIRC) who consented to participate in the 12-month follow-up study. NT-proBNP was measured at 24 h after sepsis onset. Patients were followed to determine physical function by short physical performance battery (SPPB) test score (scale 0 to12-higher score corresponds with better physical function) and upper limb muscle strength by hand grip strength test (kilograms) at 6 and 12 months. We used a multivariate linear regression model to test an association between NT-proBNP levels, SPPB, and hand grip strength scores. Missing follow-up data or absence due to death was accounted for by using inverse probability weighting based on concurrent health performance status scores. Statistical significance was set at p ≤ 0.05. RESULTS: After adjusting for covariates (age, gender, race, Charlson comorbidity index, APACHE II score, and presence of CCI condition), higher levels of NT-proBNP at 24 h after sepsis onset were associated with lower SPPB scores at 12 months (p < 0.05) and lower hand grip strength at 6-month (p < 0.001) and 12-month follow-up (p < 0.05). CONCLUSIONS: NT-proBNP levels during the acute phase of sepsis may be a useful indicator of higher risk of long-term impairments in physical function and muscle strength in sepsis survivors.

Myeloid-derived suppressor cell function and epigenetic expression evolves over time after surgical sepsis.

BACKGROUND: Sepsis is an increasingly significant challenge throughout the world as one of the major causes of patient morbidity and mortality. Central to the host immunologic response to sepsis is the increase in circulating myeloid-derived suppressor cells (MDSCs), which have been demonstrated to be present and independently associated with poor long-term clinical outcomes. MDSCs are plastic cells and potentially modifiable, particularly through epigenetic interventions. The objective of this study was to determine how the suppressive phenotype of MDSCs evolves after sepsis in surgical ICU patients, as well as to identify epigenetic differences in MDSCs that may explain these changes. METHODS: Circulating MDSCs from 267 survivors of surgical sepsis were phenotyped at various intervals over 6 weeks, and highly enriched MDSCs from 23 of these samples were co-cultured with CD3/CD28-stimulated autologous T cells. microRNA expression from enriched MDSCs was also identified. RESULTS: We observed that MDSC numbers remain significantly elevated in hospitalized sepsis survivors for at least 6 weeks after their infection. However, only MDSCs obtained at and beyond 14 days post-sepsis significantly suppressed T lymphocyte proliferation and IL-2 production. These same MDSCs displayed unique epigenetic (miRNA) expression patterns compared to earlier time points. CONCLUSIONS: We conclude that in sepsis survivors, immature myeloid cell numbers are increased but the immune suppressive function specific to MDSCs develops over time, and this is associated with a specific epigenome. These findings may explain the chronic and persistent immune suppression seen in these subjects.

A new conceptual model of global ocean heat uptake.

We formulate a new conceptual model, named "MT2", to describe global ocean heat uptake, as simulated by atmosphere-ocean general circulation models (AOGCMs) forced by increasing atmospheric CO2, as a function of global-mean surface temperature change T and the strength of the Atlantic meridional overturning circulation (AMOC, M). MT2 has two routes whereby heat reaches the deep ocean. On the basis of circumstantial evidence, we hypothetically identify these routes as low- and high-latitude. In low latitudes, which dominate the global-mean energy balance, heat uptake is temperature-driven and described by the two-layer model, with global-mean T as the temperature change of the upper layer. In high latitudes, a proportion p (about 14%) of the forcing is taken up along isopycnals, mostly in the Southern Ocean, nearly like a passive tracer, and unrelated to T. Because the proportion p depends linearly on the AMOC strength in the unperturbed climate, we hypothesise that high-latitude heat uptake and the AMOC are both affected by some characteristic of the unperturbed global ocean state, possibly related to stratification. MT2 can explain several relationships among AOGCM projections, some found in this work, others previously reported: ∙ Ocean heat uptake efficiency correlates strongly with the AMOC. ∙ Global ocean heat uptake is not correlated with the AMOC. ∙ Transient climate response (TCR) is anticorrelated with the AMOC. ∙ T projected for the late twenty-first century under high-forcing scenarios correlates more strongly with the effective climate sensitivity than with the TCR.

Estimating Ocean Heat Uptake Using Boundary Green's Functions: A Perfect-Model Test of the Method.

Ocean heat uptake is caused by "excess heat" being added to the ocean surface by air-sea fluxes and then carried to depths by ocean transports. One way to estimate excess heat in the ocean is to propagate observed sea surface temperature (SST) anomalies downward using a Green's function (GF) representation of ocean transports. Taking a "perfect-model" approach, we test this GF method using a historical simulation, in which the true excess heat is diagnosed. We derive GFs from two approaches: (a) simulating GFs using idealized tracers, and (b) inferring GFs from simulated CFCs and climatological tracers. In the model world, we find that combining simulated GFs with SST anomalies reconstructs the Indo-Pacific excess heat with a root-mean-square error of 26% for depth-integrated changes; the corresponding number is 34% for inferred GFs. Simulated GFs are inaccurate because they are coarse grained in space and time to reduce computational cost. Inferred GFs are inaccurate because observations are insufficient constraints. Both kinds of GFs neglect the slowdown of the North Atlantic heat uptake as the ocean warms up. SST boundary conditions contain redistributive cooling in the Southern Ocean, which causes an underestimate of heat uptake there. All these errors are of comparable magnitude, and tend to compensate each other partially. Inferred excess heat is not sensitive to: (a) small changes in the shape of prior GFs, or (b) additional constraints from SF6 and bomb 14C.

Prevalence of multiple sclerosis and treatment utilization in a large, highly diverse population.

BACKGROUND: Despite advances in algorithms for identifying people with MS (PwMS) in large data sets, limited data exists on regional prevalence, or prevalence and care in minority populations. OBJECTIVES: To report the 7-year (01/01/2012-12/31/2018) prevalence and demographics of MS and disease-modifying therapy (DMT) utilization in a large, diverse population. METHODS: This retrospective analysis used the OneFlorida Data Trust, which captures health data from >15 million Floridians across 10 constituent organizations. A validated algorithm identified subjects with MS. DMTs were identified using RxNorm concept unique identifiers and National Drug Codes. Results were stratified across age, sex, race-ethnicity, and location. RESULTS: Of 6,638,649 adults in the database, the algorithm identified 9681 PwMS. Overall prevalence per 100,000 was 145.83. MS prevalence was considerable in women of all races and ethnicities ranging from 138.86 to 253.76 per 100,000. 52.6% of PwMS had one or more DMT prescription. DMT prescription was more likely in Hispanic PwMS. CONCLUSION: Prevalence analysis of the OneFlorida Data Trust revealed a substantial burden of disease in women of all races and ethnicities. Variation in treatment utilization among demographic subgroups underscores the need for additional studies to assess health care disparities in MS at the population level.

MarZIC: A Marginal Mediation Model for Zero-Inflated Compositional Mediators with Applications to Microbiome Data.

BACKGROUND: The human microbiome can contribute to pathogeneses of many complex diseases by mediating disease-leading causal pathways. However, standard mediation analysis methods are not adequate to analyze the microbiome as a mediator due to the excessive number of zero-valued sequencing reads in the data and that the relative abundances have to sum to one. The two main challenges raised by the zero-inflated data structure are: (a) disentangling the mediation effect induced by the point mass at zero; and (b) identifying the observed zero-valued data points that are not zero (i.e., false zeros). METHODS: We develop a novel marginal mediation analysis method under the potential-outcomes framework to address the issues. We also show that the marginal model can account for the compositional structure of microbiome data. RESULTS: The mediation effect can be decomposed into two components that are inherent to the two-part nature of zero-inflated distributions. With probabilistic models to account for observing zeros, we also address the challenge with false zeros. A comprehensive simulation study and the application in a real microbiome study showcase our approach in comparison with existing approaches. CONCLUSIONS: When analyzing the zero-inflated microbiome composition as the mediators, MarZIC approach has better performance than standard causal mediation analysis approaches and existing competing approach.

IFAA: Robust Association Identification and Inference for Absolute Abundance in Microbiome Analyses.

The target of inference in microbiome analyses is usually relative abundance (RA) because RA in a sample (e.g., stool) can be considered as an approximation of RA in an entire ecosystem (e.g., gut). However, inference on RA suffers from the fact that RA are calculated by dividing absolute abundances (AAs) over the common denominator (CD), the summation of all AA (i.e., library size). Because of that, perturbation in one taxon will result in a change in the CD and thus cause false changes in RA of all other taxa, and those false changes could lead to false positive/negative findings. We propose a novel analysis approach (IFAA) to make robust inference on AA of an ecosystem that can circumvent the issues induced by the CD problem and compositional structure of RA. IFAA can also address the issues of overdispersion and handle zero-inflated data structures. IFAA identifies microbial taxa associated with the covariates in Phase 1 and estimates the association parameters by employing an independent reference taxon in Phase 2. Two real data applications are presented and extensive simulations show that IFAA outperforms other established existing approaches by a big margin in the presence of unbalanced library size. Supplementary materials for this article are available online.

Delayed interhospital transfer of critically ill patients with surgical sepsis.

BACKGROUND: Suboptimal triage of critically ill patients with surgical sepsis may contribute to adverse outcomes. Patients transferred to a tertiary care center after spending 24 hours or longer at an outside facility were compared with patients who had early triage to a tertiary care center with the null hypothesis that management parameters and outcomes would be similar between groups. METHODS: This prospective observational cohort study included 308 patients treated for surgical sepsis in a surgical intensive care unit at a tertiary care center. Patients transferred after spending more than 24 hours at an outside facility (n = 69) were compared with patients who were directly admitted or transferred within 24 hours (n = 239). Patient characteristics, management parameters, and outcomes were compared between groups. This study was registered at ClinicalTrials.gov (NCT02276066). RESULTS: Average outside facility length of stay in the delayed transfer group was 43 hours. Delayed transfer patients had higher sequential organ failure assessment (7 vs. 5, p = 0.003) and APACHE II scores (19 vs. 16, p = 0.007) on admission. The interval between admission and source control was significantly longer in the delayed transfer group (12.1 hours vs. 1.0 hours, p = 0.009). The incidence of nosocomial infection was significantly higher in the delayed transfer group (41% vs. 23%, p = 0.005). Delayed transfer was independently associated with a 10-day increase in hospital length of stay. Delayed transfer patients were less likely to be discharged home (22% vs. 59%, p < 0.001) and suffered twofold higher in-hospital mortality (14.5% vs. 7.1%, p = 0.056). CONCLUSION: Patients with surgical sepsis who spent more than 24 hours at an outside facility prior to transfer had greater initial illness severity, longer intervals between admission and source control, and more nosocomial infections compared with patients who had early triage to a tertiary care center. LEVEL OF EVIDENCE: Care management/therapeutic, Level IV; Epidemiologic/prognostic, Level III.

Stabilization of ATF5 by TAK1-Nemo-like kinase critically regulates the interleukin-1ß-stimulated C/EBP signaling pathway.

Interleukin-1ß (IL-1ß) is a key proinflammatory cytokine that initiates several signaling cascades, including those involving CCAAT/enhancer binding proteins (C/EBPs). The mechanism by which IL-1ß propagates a signal that activates C/EBP has remained elusive. Nemo-like kinase (NLK) is a mitogen-activated protein kinase (MAPK)-like kinase associated with many pathways and phenotypes that are not yet well understood. Using a luciferase reporter screen, we found that IL-1ß-induced C/EBP activation was positively regulated by NLK. Overexpression of NLK activated C/EBP and potentiated IL-1ß-triggered C/EBP activation, whereas knockdown or knockout of NLK had the opposite effect. NLK interacted with activating transcription factor 5 (ATF5) and inhibited the proteasome-dependent degradation of ATF5 in a kinase-independent manner. Consistently, NLK deficiency resulted in decreased levels of ATF5. NLK cooperated with ATF5 to activate C/EBP, whereas NLK could not activate C/EBP upon knockdown of ATF5. Moreover, TAK1, a downstream effector of IL-1ß that acts upstream of NLK, mimicked the ability of NLK to stabilize ATF5 and activate C/EBP. Thus, our findings reveal the TAK1-NLK pathway as a novel regulator of basal or IL-1ß-triggered C/EBP activation though stabilization of ATF5.