Markov cohort simulation study reveals evidence for sex-based risk difference in intensive care unit patients

Effect of Gender on Postoperative Morbidity and Mortality Outcomes: A Retrospective Cohort Study

Full extent of gender differences on postoperative outcomes has never been studied on large scale, specifically postoperative complications. This study aims to assess the effect of gender on 30-day morbidity and mortality after major surgery. A retrospective cohort study was carried out using data of patients undergoing major surgeries from the American College of Surgeons’ National Surgical Quality Improvement Program database between 2008 and 2011. Demographics, pre- and perioperative risk factors, as well as 30-day morbidities, both overall and specific, were reviewed. The 30-day mortality data were also assessed. Multivariate logistic regression analyses, basic (Adj1) and extended (Adj2), were used to assess the association between gender and outcomes. Out of 1,409,131 patients, 57.2 per cent were females. Females had lower prevalence of most system-specific risk variables. Overall morbidities were also lower in females versus males, even after adjustment for variables [total overall morbidity: ORadj2 = 0.9 (0.89–0.92), P < 0.0001] except in some cases such as after cardiac surgeries [ORadj2 = 1.29 (1.14–1.44), P < 0.0001] and vascular surgeries [ORadj2 = 1.14 (1.10–1.18), P < 0.0001], where overall morbidities of females were higher. Specific morbidities were also lower in females than in males in all types of complications except central nervous system-related postoperative complications [ORadj2 = 1.15 (1.08–1.22), P < 0.0001] and return to the operating room [ORadj2 = 1.06 (1.04–1.08), P < 0.0001]. The 30-day mortality rate for females was lower than males [ORadj2 = 0.99 (0.96–1.03), P = 0.94]. Female gender was associated with less perioperative morbidity and mortality versus males, but they did worse after cardiovascular procedures and had more central nervous system-related complications. These outcomes should be taken into consideration by surgeons and should be evaluated further in future studies.

Clinical course of sepsis, severe sepsis, and septic shock in a cohort of infected patients from ten Colombian hospitals

Background

Sepsis has several clinical stages, and mortality rates are different for each stage. Our goal was to establish the evolution and the determinants of the progression of clinical stages, from infection to septic shock, over the first week, as well as their relationship to 7-day and 28-day mortality.

Methods

This is a secondary analysis of a multicenter cohort of inpatients hospitalized in general wards or intensive care units (ICUs). The general estimating equations (GEE) model was used to estimate the risk of progression and the determinants of stages of infection over the first week. Cox regression with time-dependent covariates and fixed covariates was used to determine the factors related with 7-day and 28-day mortality, respectively.

Results

In 2681 patients we show that progression to severe sepsis and septic shock increases with intraabdominal and respiratory sources of infection [OR = 1,32; 95%IC = 1,20-1,46 and OR = 1.21, 95%CI = 1,11-1,33 respectively], as well as according to Acute Physiology and Chronic Health Evaluation II (APACHE II) [OR = 1,03; 95%CI = 1,02-1,03] and Sequential Organ Failure Assessment (SOFA) [OR = 1,16; 95%CI = 1,14-1,17] scores. The variables related with first-week mortality were progression to severe sepsis [HR = 2,13; 95%CI = 1,13-4,03] and septic shock [HR = 3,00; 95%CI = 1,50-5.98], respiratory source of infection [HR = 1,76; 95%IC = 1,12-2,77], APACHE II [HR = 1,07; 95% CI = 1,04-1,10] and SOFA [HR = 1,09; 95%IC = 1,04-1,15] scores.

Conclusions

Intraabdominal and respiratory sources of infection, independently of SOFA and APACHE II scores, increase the risk of clinical progression to more severe stages of sepsis; and these factors, together with progression of the infection itself, are the main determinants of 7-day and 28-day mortality.

Systems modeling and simulation applications for critical care medicine

Critical care delivery is a complex, expensive, error prone, medical specialty and remains the focal point of major improvement efforts in healthcare delivery. Various modeling and simulation techniques offer unique opportunities to better understand the interactions between clinical physiology and care delivery. The novel insights gained from the systems perspective can then be used to develop and test new treatment strategies and make critical care delivery more efficient and effective. However, modeling and simulation applications in critical care remain underutilized. This article provides an overview of major computer-based simulation techniques as applied to critical care medicine. We provide three application examples of different simulation techniques, including a) pathophysiological model of acute lung injury, b) process modeling of critical care delivery, and c) an agent-based model to study interaction between pathophysiology and healthcare delivery. Finally, we identify certain challenges to, and opportunities for, future research in the area.

Gender differences in mortality following non-cardiovascular surgery: an observational study

PURPOSE

Although inequality between males and females in cardiovascular surgery is well recognized, few studies have examined the influence of sex on mortality following non-cardiovascular surgery. The objective of the study was to determine whether there are differences in mortality between males and females following non-cardiovascular surgery and to ascertain to what extent preoperative risk factors explain these differences.

METHODS

This was an observational study of 39,433 consecutive non-cardiovascular inpatient surgical cases from non-sex-biased surgical services from 2003 to 2009. Data on the surgical procedure, patient risk factors, and outcomes was retrieved from the institutional Electronic Data Warehouse. The primary outcome was in-hospital mortality within 30 days of surgery. Multivariate analysis using logistic regression was conducted to determine the role of risk factors for mortality.

RESULTS

The 30-day mortality was 2.76% for males and 1.89% for females (odds ratio, 1.47; 95% confidence interval [CI], 1.29 to 1.69). Logistic regression showed that age, number of Charlson comorbidities, American Society of Anesthesiologists (ASA) classification, and emergent/urgent status were independent predictors of mortality (receiver operating characteristic area, 0.90). After adjustment for these factors, the odds ratio for male mortality was reduced to 1.31 (95% CI, 1.14 to 1.52).

CONCLUSION

Males present for non-cardiovascular surgery with a higher ASA classification, with more comorbidities, and more often emergently than females, providing a partial explanation of the observed difference in mortality.

Using hierarchical dynamic Bayesian networks to investigate dynamics of organ failure in patients in the Intensive Care Unit

In intensive care medicine close monitoring of organ failure status is important for the prognosis of patients and for choices regarding ICU management. Major challenges in analyzing the multitude of data pertaining to the functioning of the organ systems over time are to extract meaningful clinical patterns and to provide predictions for the future course of diseases. With their explicit states and probabilistic state transitions, Markov models seem to fit this purpose well. In complex domains such as intensive care a choice is often made between a simple model that is estimated from the data, or a more complex model in which the parameters are provided by domain experts. Our primary aim is to combine these approaches and develop a set of complex Markov models based on clinical data. In this paper we describe the design choices underlying the models, which enable them to identify temporal patterns, predict outcomes, and test clinical hypotheses. Our models are characterized by the choice of the dynamic hierarchical Bayesian network structure and the use of logistic regression equations in estimating the transition probabilities. We demonstrate the induction, inference, evaluation, and use of these models in practice in a case-study of patients with severe sepsis admitted to four Dutch ICUs.

Between prediction, education, and quality control: simulation models in critical care

Today, computer-aided strategies in social sciences are an indispensable component of teaching programs. In recent years, microsimulation modeling has gained attention in its ability to represent predicted physiological developments visually, thus providing the user with a full understanding of the impacts of a proposed scheme. There are several microsimulation models in human medicine, and they can be either dynamic or static. If the model is dynamic the course of variables changes over time; in contrast, in the static case time constancy is assumed. In critical care there have been several approaches to implement microsimulation models to predict outcome. This commentary describes current approaches for predicting disease progression by using dynamic microsimulation in pneumonia-related sepsis.

Use of dynamic microsimulation to predict disease progression in patients with pneumonia-related sepsis

Introduction

Sepsis is the leading cause of death in critically ill patients and often affects individuals with community-acquired pneumonia. To overcome the limitations of earlier mathematical models used to describe sepsis and predict outcomes, we designed an empirically based Monte Carlo model that simulates the progression of sepsis in hospitalized patients over a 30-day period.

Methods

The model simulates changing health over time, as represented by the Sepsis-related Organ Failure Assessment (SOFA) score, as a function of a patient's previous health state and length of hospital stay. We used data from patients enrolled in the GenIMS (Genetic and Inflammatory Markers of Sepsis) study to calibrate the model, and tested the model's ability to predict deaths, discharges, and daily SOFA scores over time using different algorithms to estimate the natural history of sepsis. We evaluated the stability of the methods using bootstrap sampling techniques.

Results

Of the 1,888 patients originally enrolled, most were elderly (mean age 67.77 years) and white (80.72%). About half (47.98%) were female. Most were relatively ill, with a mean Acute Physiology and Chronic Health Evaluation III score of 56 and Pneumonia Severity Index score of 73.5. The model's estimates of the daily pattern of deaths, discharges, and SOFA scores over time were not statistically different from the actual pattern when information about how long patients had been ill was included in the model (P = 0.91 to 0.98 for discharges; P = 0.26 to 0.68 for deaths). However, model estimates of these patterns were different from the actual pattern when the model did not include data on the duration of illness (P < 0.001 for discharges; P = 0.001 to 0.040 for deaths). Model results were stable to bootstrap validation.

Conclusion

An empiric simulation model of sepsis can predict complex longitudinal patterns in the progression of sepsis, most accurately by models that contain data representing both organ-system levels of and duration of illness. This work supports the incorporation into mathematical models of disease of the clinical intuition that the history of disease in an individual matters, and represents an advance over several prior simulation models that assume a constant rate of disease progression.

Protection from lethal endotoxic shock after testosterone depletion is linked to chromosome X

Men are considered more susceptible to sepsis after severe injury than are women, which has been attributed to a suppressing effect of male sex steroids on the inflammatory response. Moreover, the effect of sex steroids on the inflammatory process depends on the genetic background. The present study examined the genetic contribution to survival after endotoxic shock in mice depleted of testosterone by surgical castration. Six-week-old male mice, from strains A/J, AKR/J, C57BL/6J (B6), BALBc/J, DBA/2J, and C3H/HeN, were castrated (CX) or nonoperated (NoOp). Two weeks after surgery, mice were injected intraperitoneally with Escherichia coli lipopolysaccharide (15 mg/kg) and the frequency of mortality was monitored. CX A/J mice showed a significantly higher survival rate than NoOp mice, but this protective effect was not observed in the other strains. Administration of 5-alpha-dihydrotestosterone to CX A/J mice reverted the protection by CX. The protective effect of CX was also observed in crosses of female A/J and male B6 (AXB), but not female B6 and male A/J (BXA), suggesting that protection is linked to the A/J X chromosome. This possibility was corroborated by using consomic mice containing A/J chromosome X and the remaining chromosomes from B6. These results suggest that testosterone is a negative factor in the recovery from endotoxic shock, depending on the genetic background.

Sex differences in cytokine production and surface antigen expression of peripheral blood mononuclear cells after surgery

BACKGROUND

Several clinical and epidemiological studies have observed a better outcome after sepsis in women than in men. The purpose of this study was to determine if these sex differences are observed in cytokine responses and the surface antigen expression of monocytes. In addition, the clinical courses of male and female patients after gastrointestinal surgery were compared.

METHODS

A total of 25 patients with gastric carcinoma who underwent gastrectomy were enrolled in this study. Tumor necrosis factor-alpha (TNF-alpha), interleukin-10, and interferon-gamma (IFN-gamma) production by lipopolysaccharide-stimulated peripheral blood mononuclear cells (PBMCs) as well as the expression of Toll-like receptor-4 (TLR-4), TLR-2, human leukocyte antigen-D related (HLA-DR), and CD16 on monocytes in 16 men and 9 women on the day before surgery were compared with measurements on postoperative day (POD) 1. Furthermore, postoperative infectious complications, the development of systemic inflammatory response syndrome, and serum C-reactive protein levels on POD3 were compared.

RESULTS

TNF-alpha production of PBMCs and TLR-2 and CD16 expression on monocytes were significantly higher in women than in men before surgery. IFN-gamma production of PBMCs and HLA-DR expression on monocytes were significantly lower in men than in women on POD1. Furthermore, TNF-alpha production of PBMCs on POD1 was significantly increased, and both IFN-gamma production and HLA-DR expression were significantly decreased compared with that observed before surgery in men, but no corresponding significant changes were observed in women. In addition, C-reactive protein levels on POD3 were significantly higher in men than in women.

CONCLUSIONS

Both TNF-alpha and interleukin-10 production of PBMCs and both TLR-2 and CD16 expression on monocytes were significantly higher in women than in men on the day before surgery. Excessive TNF-alpha and suppressive IFN-gamma production of PBMCs, as well as a decrease in HLA-DR expression on monocytes, occurred more often in men than in women after surgery, suggesting that these factors all contribute to an increased susceptibility of men to develop systemic inflammatory response syndrome or postoperative infectious complications.

Simulation and critical care modeling

PURPOSE OF REVIEW

Decisions made in critical care are often complicated, requiring an in-depth understanding of the relations between complex diseases, available interventions, and patients with a wide range of characteristics. Standard modeling techniques such as decision trees and statistical modeling have difficulty in capturing these interactions as the complexity of the problem increases.

RECENT FINDINGS

Recent models in the literature suggest that simulation modeling techniques such as Markov modeling, Monte Carlo simulation, and discrete-event simulation are useful tools for analyzing complex systems in critical care. These simulation techniques are reviewed briefly, and examples from the literature are presented to demonstrate their usefulness in understanding real problems in critical care.

SUMMARY

Simulation models provide useful tools for organizing and analyzing the interactions between therapies, tradeoffs, and outcomes.

Effects of timing of thoracoscopic surgery for primary spontaneous pneumothorax on prognosis and costs

BACKGROUND

Primary spontaneous pneumothorax recurs frequently. Timing of video-assisted thoracoscopic surgery to prevent recurrence is controversial and long-term costs remain inconclusive.

METHODS

We constructed a Markov model to assess the effect of different timings for surgery on health status, costs, and cost effectiveness from the payers' perspective in Japan.

RESULTS

During 1-year follow-up, the proportions of patients who underwent surgery after the first and second drainage were 46% and 36%, respectively. Average 1-year cost for surgery at the first episode was highest (U.S. dollars 6556), followed by the second (U.S. dollars 2988) and the third (U.S. dollars 2532). Incremental cost for surgery at the first episode compared with the second and that at the second episode compared with the third were U.S. dollars 30564 and U.S. dollars 29915 per quality-adjusted life year, respectively. Sensitivity analyses showed utility and length of hospital stay for surgery have the strongest effect on incremental cost.

CONCLUSIONS

Thoracoscopic surgery at the first episode significantly increased costs, but could be acceptable from a cost-effectiveness perspective.

Efeitos da castração pós-natal sobre o tecido pulmonar após sepse experimental de origem abdominal em ratos

OBJETIVO: Avaliar os efeitos da castração pós-natal sobre o tecido pulmonar na sepse de origem abdominal induzida em ratos. MÉTODOS: Foram utilizados 33 ratos Wistar distribuídos em dois grupos: Grupo Controle (GC) = 5 machos adultos normais sem desafio séptico. Grupo Experimento (GE): 28 ratos submetidos a sepse por ligadura e perfuração de ceco (LPC) e distribuídos em três subgrupos: Subgrupo Macho (SgM): nove ratos machos adultos, sem castracão e submetidos a sepse por LPC. Subgrupo Fêmea (SgF): nove ratos fêmeas adultos normais submetidas a sepse por LPC. Subgrupo Castrado (SgC): dez ratos machos que no quarto dia de vida foram submetidos a orquiectomia bilateral e quando adultos à sepse por LPC. Após a LPC os animais foram observados até o óbito, realizada análise histomorfométrica do pulmão, observando-se o número de polimorfonucleares e mononucleares. RESULTADOS: 50% dos animais do SgC sobreviveram 24 horas, contra 33% do SgF e 0% do SgM, mostrando uma nítida influência da castração na resposta ao desafio séptico. O número de polimorfonucleares e mononucleares não foi diferente estatisticamente entre o SgC e CG, estando estatisticamente aumentados no SgM e SgF. CONCLUSÃO: Os animais castrados apresentaram uma maior tendência à sobrevida e menor alteração pulmonar.

Genetic background conditions the effect of sex steroids on the inflammatory response during endotoxic shock

OBJECTIVE

The contribution of gender to the mortality and morbidity of trauma patients is controversial. In addition, a genetic contribution has been recently indicated. The influence of these two variables was studied in a murine model of endotoxemia.

DESIGN

Prospective, controlled, and randomized animal study.

SETTING

A university research laboratory.

SUBJECTS

Female and male mice (6-8 wks old) were injected with lipopolysaccharide (15 mg/kg). Additionally, mice were gonadectomized and supplemented with 5-alpha-dihydrotestosterone (357 mg/day), 17-beta-estradiol (23.8 microg/day), or placebo for 21 days and injected with lipopolysaccharide. Tumor necrosis factor-alpha was measured in plasma samples obtained after 1.5 hrs of lipopolysaccharide injection.

MEASUREMENTS AND MAIN RESULTS

Higher tumor necrosis factor-alpha plasma levels were observed in C57BL/6J (B6) female mice as compared with males. Because this phenotype is not sex linked, we evaluated the role of sex steroids. Castrated male B6 mice showed higher lipopolysaccharide-induced tumor necrosis factor-alpha plasma levels than nonoperated controls. These lipopolysaccharide-induced tumor necrosis factor-alpha levels were further increased after the administration of 17-beta-estradiol to castrated B6 male mice as compared with nonoperated male or female mice. In addition, 17-beta-estradiol-supplemented castrated mice showed a higher frequency of mortality than castrated males without hormone replacement or nonoperated mice. Analysis of castrated male mice from other strains (A/J, DBA/2J, AKR/J, BALB/cJ) supplemented with 17-beta-estradiol presented the opposite effect, a reduction in lipopolysaccharide-induced tumor necrosis factor-alpha plasma levels.

CONCLUSIONS

These results suggest that sex steroids can modulate the inflammatory response and the outcome after injury in mice. The effect of sex steroids depends on the genetic background.