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Original Research: CRITICAL CARE MEDICINE |

Influence of Gender on the Outcome of Severe Sepsis*: A Reappraisal FREE TO VIEW

Christophe Adrie, MD, PhD; Elie Azoulay, MD, PhD; Adrien Francais, PhD; Christophe Clec’h, MD; Loic Darques, MD; Carole Schwebel, MD; Didier Nakache, PhD; Samir Jamali, MD; Dany Goldgran-Toledano, MD; Maïté Garrouste-Orgeas, MD; Jean François Timsit, MD, PhD; for the OutcomeRea Study Group
Author and Funding Information

Affiliations: *From the Medical-Surgical ICU (Drs. Adrie and Darques), Delafontaine Hospital, Saint Denis; Medical ICU (Dr. Azoulay), Saint Louis Teaching Hospital, Paris; INSERM U823 (Drs. Francais and Timsit), Epidemiology of Cancer and Severe Illnesses, Albert Bonniot Institute, Grenoble; Medical-Surgical ICU (Dr. Clec’h), Avicenne Teaching Hospital, Bobigny; Medical ICU (Dr. Schwebel), Albert Michallon Teaching Hospital, Grenoble; Laboratory of Computer Sciences (Dr. Nakache), Centre National des Arts et Métiers, Paris; Medical-Surgical ICU (Dr. Jamali), Dourdan Hospital, Dourdan; Medical-Surgical ICU (Dr. Goldgran-Toledano), Gonesse Hospital, Gonesse; and Medical-Surgical ICU (Dr. Garrouste-Orgeas), Saint Joseph Hospital, Paris, France.,  A list of participants is given in the Appendix.

Correspondence to: Christophe Adrie, MD, PhD, Service de Réanimation Polyvalente, Hôpital Delafontaine, 2, rue du Dr Delafontaine, 93205 Sant Denis, France; e-mail: christophe.adrie@outcomerea.org


Affiliations: *From the Medical-Surgical ICU (Drs. Adrie and Darques), Delafontaine Hospital, Saint Denis; Medical ICU (Dr. Azoulay), Saint Louis Teaching Hospital, Paris; INSERM U823 (Drs. Francais and Timsit), Epidemiology of Cancer and Severe Illnesses, Albert Bonniot Institute, Grenoble; Medical-Surgical ICU (Dr. Clec’h), Avicenne Teaching Hospital, Bobigny; Medical ICU (Dr. Schwebel), Albert Michallon Teaching Hospital, Grenoble; Laboratory of Computer Sciences (Dr. Nakache), Centre National des Arts et Métiers, Paris; Medical-Surgical ICU (Dr. Jamali), Dourdan Hospital, Dourdan; Medical-Surgical ICU (Dr. Goldgran-Toledano), Gonesse Hospital, Gonesse; and Medical-Surgical ICU (Dr. Garrouste-Orgeas), Saint Joseph Hospital, Paris, France.,  A list of participants is given in the Appendix.


Chest. 2007;132(6):1786-1793. doi:10.1378/chest.07-0420
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Background: The influence of gender on survival of patients with severe sepsis is unclear. Earlier studies suggested better survival in women, possibly related to the sex-steroid profile.

Methods: To investigate whether mortality from severe sepsis was higher in men than in women and whether the difference varied with menopausal status, we studied 1,692 patients with severe sepsis included in the OutcomeRea database over an 8-year period. We conducted a nested case-control study, accurately matching men and women on three criteria: a death propensity score, age, and center. Subgroup analyses were performed on individuals ≤ 50 years old (men vs premenopausal women) and > 50 years old (men vs postmenopausal women).

Results: We matched 1,000 men to 608 women with severe sepsis before and after adjustment for confounding factors (ie, chronic respiratory failure; metastatic cancer; immunocompromised status; emergency surgery, acute respiratory failure, and shock at admission; urinary tract infection; and type of microorganism). Overall hospital mortality was significantly lower in women (adjusted odds ratio [OR], 0.75; 95% confidence interval [CI], 0.57 to 0.97; p = 0.02). In the group > 50 years old (481 women, 778 men), hospital mortality was significantly lower in women (OR, 0.69; 95% CI, 0.52 to 0.93; p = 0.014). Hospital mortality was not significantly different between men and women in the younger group (127 women, 222 men) [OR, 1.01; 95% CI, 0.52 to 1.97; p = 0.98]. Level of care, as assessed using the nine equivalents of nursing manpower use score, was identical in men and women.

Conclusions: Among individuals > 50 years old with severe sepsis, women have a lower risk of hospital mortality than men.

Figures in this Article

Severe sepsis remains a leading cause of death in industrialized countries, and the number of deaths caused by sepsis is increasing despite improved survival rates.12 Mortality ranges from 20 to 50% in patients with severe sepsis. The incidence of sepsis is lower among women in the US general population for all infection sources except the genitourinary tract.12 Men were more likely to have sepsis than women in each year of the 22-year period from 1979 through 2000, with a mean annual relative risk of 1.28.1 The influence of gender on mortality in patients with established sepsis is less clear. The greater immune system activity in women than in men is consistent with better survival in women with severe sepsis. Sex hormones3or sex-related gene polymorphisms45 may protect women against sepsis and death from sepsis. Differences in hormone profiles have been widely suggested as the cause of gender-based differences in the incidence and outcome of sepsis. In mice, proestrus females tolerated polymicrobial sepsis better than males,6and survival improved in males after testosterone receptor blockade.7 However, epidemiologic studies3,814 produced conflicting results, perhaps reflecting effects of age, case-mix differences, nature of the injury preceding sepsis development (eg, trauma or burns), infection source, comorbidities, and menopausal status. Another possible source of gender-based differences may be the reported lower use of invasive procedures in critically ill women compared to men, despite greater severity of illness in women and even after adjustment on age.15

The objective of our study was to clarify the influence of gender on survival of patients admitted to the ICU for severe community-acquired sepsis. We studied patients in a vast prospective database, and we used a propensity score to control for potential confounders. We then conducted a nested case-control study to investigate the hypothesis that men are at greater risk of death than premenopausal women.

Study Design and Data Source

We conducted a prospective observational study in a multicenter database (OutcomeRea; Rosny-sous-Bois, France) from January 1997 to September 2005. The database, fed by 12 French ICUs, contains data on daily disease severity, iatrogenic events, and nosocomial infections. A random sample of at least 50 patients > 16 years old and having ICU stays > 24 h was entered into the database each year. Each participating ICU chose to perform random sampling by taking either consecutive admissions in selected ICU beds all year long or consecutive admissions in all ICU beds in a given month.

Data Collection

Data were collected daily by senior physicians in the participating ICUs. For each patient, the investigators entered the data into a computer case-report form using data-capture software (VIGIREA; OutcomeRea) and imported all records into the OutcomeRea database. All codes and definitions were established prior to study initiation. The following information was recorded: age and sex, admission category (medical, scheduled surgery, or unscheduled surgery), origin (home, ward, or emergency department), and McCabe score.16Severity of illness was evaluated on the first ICU day using the simplified acute physiology score (SAPS) II,17logistic organ dysfunction (LOD) score,18and acute physiologic and chronic health evaluation II score.19 Knaus scale definitions were used to record preexisting chronic organ failures including respiratory, cardiac, hepatic, renal, and immune system failure.19The nine equivalents of nursing manpower use score (NEMS) was determined to measure the nursing workload for each patient, which was taken as an indicator of treatment intensity.20

Quality of the Database

For most of the study variables, the data-capture software immediately ran an automatic check for internal consistency, generating queries that were sent to the ICUs before incorporation of the new data into the database. In each participating ICU, data quality was checked by having a senior physician from another participating ICU review a 2% random sample of the study data. All the variables introduced in the analyses had a κ coefficient > 0.6 for qualitative variables and an interrater coefficient of 0.67 to 1, indicating good to excellent reproducibility.

Study Population

The presence or absence of infections was documented according to the standard definitions developed by the Centers for Disease Control and Prevention21; in addition, a quantitative protected plugged catheter culture showing ≥ 103 cfu/mL was used to diagnose pneumonia.22 Community-acquired infection was defined as infection manifesting before or within 48 h after hospital admission. Hospital-acquired infection was infection manifesting at least 48 h after hospital admission but before ICU admission. Infection sites were categorized as follows: pneumonia, peritonitis, urinary tract infection, exacerbation of COPD, primary bacteremia (excluding untreated Staphylococcus epidermidis), miscellaneous sites (mediastinitis, prostatitis, osteomyelitis, and others), and multiple sites. Lengths of ICU and hospital stays were computed starting from ICU admission.

Severe sepsis was defined as infection with two or more criteria for systemic inflammatory response syndrome and at least one criterion for organ dysfunction. Criteria for systemic inflammatory response syndrome included core temperature ≥ 38°C or ≤ 36°C, heart rate ≥ 90 beats/min, respiratory rate ≥ 20 breaths/min, Pco2 ≤ 32 mm Hg or use of mechanical ventilation, and peripheral leukocyte count ≥ 12,000/μL or ≤ 4,000/μL. Organ dysfunction was defined as follows: (1) cardiovascular system failure with a need for vasopressors and/or inotropic drugs, and/or a systolic BP < 90 mm Hg, and/or a drop in systolic BP > 40 mm Hg from baseline; (2) renal dysfunction with urinary output ≤ 700 mL/d in a patient not previously receiving hemodialysis for chronic renal failure; (3) respiratory dysfunction with a Pao2 < 70 mm Hg or mechanical ventilation or a Pao2/fraction of inspired oxygen ratio ≤ 250 (or < 200 in patients with pneumonia); (4) bone marrow failure with a platelet count < 80,000/μL; and (5) metabolic acidosis with a plasma lactate level ≥ 3 mmol/L.

End Points

The primary end points were all-cause ICU mortality and post-ICU mortality. Secondary end points were workloads within the first 2 days in the ICU.

Several analyses were planned. First, we assessed the influence of gender on hospital mortality in the overall population of patients with severe sepsis. We then looked at the influence of age by carefully matching male and female patients ≥ 50 years old and those > 50 years old. The 50-year cut-off was chosen to separate premenopausal and postmenopausal women.

Statistical Analysis

Results are expressed as numerical values and percentages for categorical variables, and as medians and first and third quartiles for continuous variables. For categorical data, gender comparisons in the overall cohort were based on χ2 tests or Fisher exact tests depending on sample size; for continuous data, Kruskal-Wallis or Wilcoxon tests were used. Since characteristics of severe sepsis may markedly influence the risk of death independently from gender, we developed a predictive model of death in the overall population, which was used as a matching criterion when selecting men and women.

Logistic regression was performed subsequently to identify independent risk factors for hospital mortality in men and women with severe sepsis.23 Because of colinearity, severity and organ failure scores were not introduced simultaneously in the models but, instead, tested consecutively and chosen according to the Akaike criterion. Calibration and discrimination of the final model were assessed using the Hosmer-Lemeshow χ2 test and C statistic, respectively.

We then designed a nested case-control study to compare female and male patients. This score was based on the results of the above-described multivariate logistic regression analysis. Using an algorithm (available at http://www.outcomerea.org/ehtm/matchmacro.pdf), we matched female and male patients based on three criteria: center, death propensity score24 (± 10%), and 10-year age group. Wald χ2 tests were used to determine the significance of each variable. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each parameter estimate, using conditional logistic regression. We then did a similar analysis comparing premenopausal women (≤ 50 years) to men matched on the propensity score. Finally, we adjusted the conditional logistic regression on variables not balanced between male and female patients and previously reported to be associated with mortality; p values < 0.05 were considered significant. Analyses were computed using statistical software (SAS 8.2; SAS Institute; Cary, NC).

Study Population

Of the 4,860 patients included in the database (all with ICU stays > 48 h), 1,692 met our criteria for severe sepsis; 63% were male and 37% were female (Fig 1 ). The women were older and had a higher rate of emergency surgery, lower organ dysfunction scores (LOD and sequential organ failure assessment), and similar SAPS II scores at hospital admission (Table 1 ). Chronic pulmonary dysfunction as assessed by Knaus definitions was more common in male patients, but all other comorbidities were evenly distributed between genders. Cardiovascular dysfunction was the leading organ dysfunction, with similar rates in men and women (67.3% vs 69.6%) and in patients who did and did not require vasopressor support (indicating septic shock, present in 53% of male and 54% of female patients). Respiratory failure was the only organ dysfunction that was significantly more common in men. Women had lower rates of pneumonia and of multiple sources of infection but a higher rate of urinary tract infection.

Severe Sepsis and Gender

We evaluated the effect of gender based on the variables that were independently associated with death in the multivariate logistic regression analysis (Table 2 ). We matched 1,000 men to 608 women in the overall population of patients with severe sepsis. After matching on risk factors for death and adjusting for confounding factors (ie, chronic respiratory failure; metastatic cancer; immunocompromised status; emergency surgery; acute respiratory failure and shock at hospital admission; urinary tract infection as the site of infection and E coli, S pneumoniae, and Enterobacter species as the causative microorganism), the risk of hospital death was lower in women (OR, 0.75; 95% CI, 0.57 to 0.97; p = 0.02) [Table 3 ].

When we separated the patients based on age ≤ 50 years or > 50 years, we found that mortality was significantly lower in women > 50 years old (postmenopausal, n = 481) than in men > 50 years old (n = 778) [OR, 0.69; 95% CI, 0.52 to 0.93] after adjusting for confounding variables (p = 0.014). Mortality was not significantly different between the 127 women and the 222 men ≤ 50 years of age (Table 3). These results remained unchanged when patients with early do-not-resuscitate (DNR) orders were excluded.

In the matched population, women had a lower rate of central venous line use, shorter mechanical ventilation times, and shorter ICU stay lengths; however, these differences were not significant after adjustment for confounding factors. Furthermore, workload as assessed by the NEMS score on day 1, day 2, and mean NEMS for day 1 and day 2 was not significantly different between men and women, indicating a similar level of care (Table 4 ).

Mortality from severe sepsis was higher in men than in women, after adjustment for confounding factors. This difference was due to higher mortality in men > 50 years old compared to same-age (postmenopausal) women; mortality was not significantly different between younger men and women. The level of care and rate of invasive procedures were similar in women and men.

Our findings agree with previous data showing a higher incidence of sepsis in men12 compared to women. Numerous studies1,3,814 have evaluated the influence of gender on survival in patients with established sepsis, with conflicting results. For instance, in surgical units, survival was better in women,3 better in men,14 or similar in men and women.8 Although differences in case-mix, as stated earlier, and sample size contributed to these discrepancies, the main factor was probably imperfect matching of male and female patients. An important strength of the present study is the use of a propensity score in a large cohort of patients (n = 1,692, predominantly medical patients), which allowed us to obtain two groups that were very accurately matched on confounding factors. We found that mortality was higher in men in the overall cohort of patients with severe sepsis.

Differences in level of care may lead to differences in survival between men and women. Several studies2527 showed that women were less likely than men to undergo intensive evaluation and invasive treatment for cardiovascular disease. Data from the United States indicate that women are more likely than men to receive recommended preventive and chronic care but less likely to receive recommended acute care.28 However, greater utilization of acute-care resources in men may be ascribable to a few widely used procedures, such as invasive procedures for cardiovascular disease, and may mask lower utilization of resources for specific acute disorders. In Austria, Valentin et al15 documented a higher level of care with greater use of invasive procedures in men compared to women admitted to ICUs for any reason. This gender difference was found in all age groups, including the oldest patients. Although disease severity was greater in women, survival was not significantly different, suggesting either an inappropriately high level of care in men or a better potential for survival in women masked by an inappropriately low level of care. Resource use according to gender may vary across health-care systems. In addition, Valentin et al15 studied the overall population of ICU patients, as opposed to patients with severe sepsis. In our study, the NEMS values suggested similar levels of care in men and women. This similar level of care may explain the higher survival rate in women in our study, in contradiction to the results reported by Valentin et al.15

As stated in the introduction, hypothesized mechanisms of gender-based differences in the response to sepsis would predict better survival in premenopausal women than in men. However, we found better survival in women > 50 years old (ie, postmenopausal) than in same-age men, with no significant survival difference between younger women and men. First, we cannot rule out that the absence of a significant gender-based mortality difference in our younger population was due to the small number of patients and lower fatality rate. Severe sepsis is far more common in older individuals than in younger age groups. Second, estrogens produced outside the ovaries may confer protection to postmenopausal women; the main source is probably the adrenal cortex, although T cells and macrophages or fat29 may also contribute to the high sex-steroid levels observed in women. The metabolism of the adrenal hormone dehydroepiandrosterone is a major determinant of sex-steroid status in postmenopausal women. Dehydroepiandrosterone is a very weak androgen but can be converted to either more potent androgens or estrogens by peripheral tissue enzymes (5α-reductase for conversion to dihydrotestosterone and aromatase for conversion to 17β-estradiol).29 Both advancing age and higher adipocyte mass are known to increase aromatase activity. The higher body mass index observed in women than men may have led to better protection as a result of greater aromatase activity in fat tissue via estrogen production.29Third, hormone replacement therapy used by some postmenopausal women may improve responses to infection, although this hypothesis needs evaluation. Fourth, in women, high levels of estrogen for years may eventually lead to health benefits becoming apparent only later in life, compared to men. Fifth, gender-based differences in cytokine secretion by peripheral blood mononuclear cells may lead to poorer outcomes in male patients.3031 Conceivably, these differences may be more marked in postmenopausal than premenopausal women, or their effects may be masked by counterbalancing factors in premenopausal women. Cytokine secretion differences between premenopausal and postmenopausal women with sepsis deserve to be investigated. Finally, differences in health-related behaviors between men and women over the life span may eventually lead to differences in outcomes late in life.

In a recent study,32 survival in elderly patients with severe infection was similar in men and women but varied with the sex-steroid profile. In this study, the absence of a gender difference may be ascribable to the smaller sample size and to the inclusion of patients with sepsis, as opposed to severe sepsis, in our study. Furthermore, confounding factors were not well taken into account.32We did not assay sex hormones in our study. However sex hormone profiles during severe sepsis may fail to reflect baseline hormone production, since severe sepsis is often preceded by several days of systemic inflammation, a process known to decrease testosterone levels3334 and to increase 17β estradiol synthesis via an increase in aromatase activity.3536

In conclusion, women with severe sepsis had a lower risk of hospital mortality than did men carefully matched on confounding variables. This difference was present only in the group of individuals > 50 years old and was not ascribable to differences in level of care. Further studies are required to evaluate whether or not there is a need for specific treatment depending on the gender.

Members of the OutcomeRea Study Group
Scientific Committee:

Jean-François Timsit (Hôpital Albert Michallon and INSERM U823, Grenoble, France); Pierre Moine (Surgical ICU, Denver, CO); Arnaud De Lassence (ICU, Hôpital Louis Mourier, Combes, France); Elie Azoulay (Medical ICU, Hôpital Saint Louis, Paris, France); Yves Cohen (ICU, Hôpital Avicenne, Bobigny, France); Maïté Garrouste-Orgeas (ICU Hôpital Saint-Joseph, Paris, France); Lilia Soufir (ICU, Hôpital Saint-Joseph, Paris, France); Jean-Ralph Zahar (Microbiology Department, Hôpital Necker, Paris, France); Christophe Adrie (ICU, Hôpital Delafontaine, Saint Denis, France); Adel Benali (Microbiology and Infectious Diseases, Hôpital Saint-Joseph, Paris France); Christophe Clec’h (ICU, Hôpital Avicenne, Bobigny, France); and Jean Carlet (ICU, Hôpital Saint-Joseph, Paris, France).

Biostatistical and Informatics Expertise:

Jean-Francois Timsit (Group of Epidemiology, INSERM U823, Grenoble, France); Sylvie Chevret (Medical Computer Sciences and Biostatistics Department, Hôpital Saint-Louis, Paris, France); Corinne Alberti (Medical Computer Sciences and Biostatistics Department, Robert Debré, Paris, France); Aurélien Vesin (Group of Epidemiology, INSERM U823, Grenoble, France); Adrien Francais (Group of Epidemiology, INSERM U823, Grenoble, France); Muriel Tafflet (Outcomerea, France); Frederik Lecorre (Supelec, France); and Didier Nakache (Conservatoire National des Arts et Métiers, Paris, France).

Investigators of the OutcomeRea Database:

Christophe Adrie (ICU, Hôpital Delafontaine, Saint Denis, France); Bernard Allaouchiche (surgical ICU, Hôpital Edouard Herriot, Lyon); Caroline Bornstain (ICU, Hôpital de Montfermeil, France); Alexandre Boyer (ICU, Hôpital Pellegrin, Bordeaux, France); Antoine Caubel (ICU, Hôpital Saint-Joseph, Paris, France); Christine Cheval (SICU, Hôpital Saint-Joseph, Paris, France); Marie-Alliette Costa de Beauregard (Nephrology, Hôpital Tenon, Paris, France); Jean-Pierre Colin (ICU, Hôpital de Dourdan, Dourdan, France); Anne-Sylvie Dumenil (Hôpital Antoine Béclère, Clamart France); Adrien Descorps-Declere (Hôpital Antoine Béclère, Clamart France); Jean-Philippe Fosse (ICU, Hôpital Avicenne, Bobigny, France); Samir Jamali (ICU, Hôpital de Dourdan, Dourdan, France); Christian Laplace (ICU, Hôpital Kremlin-Bicêtre, Bicêtre, France); Thierry Lazard (ICU, Hôpital de la Croix Saint-Simon, Paris, France); Eric Le Miere (ICU, Hôpital Louis Mourier,Combes, France); Laurent Montesino (ICU, Hôpital Bichat, Paris, France); Bruno Mourvillier (ICU, Hôpital Bichat, France); Benoît Misset (ICU, Hôpital Saint-Joseph, Paris, France); Delphine Moreau (ICU, Hôpital Saint-Louis, Paris, France); Etienne Pigné (ICU, Hôpital Louis Mourier, Combes, France); Carole Schwebel (CHU A Michallon, Grenoble, France); Gilles Troché (Hôpital Antoine, Béclère, Clamart France); Marie Thuong (ICU, Hôpital Delafontaine, Saint Denis, France); Guillaume Thierry (ICU, Hôpital Saint-Louis, Paris, France); Dany Toledano (CH Gonesse, France); Eric Vantalon (SICU, Hôpital Saint-Joseph, Paris, France); and François Vincent (ICU, Hôpital Avicenne, Bobigny, France).

Abbreviations: CI = confidence interval; DNR = do not resuscitate; LOD = logistic organ dysfunction; NEMS = nine equivalents of nursing manpower use score; OR = odds ratio; SAPS = simplified acute physiology score

OutcomeRea is supported by nonexclusive educational grants from Aventis Pharma, France, and Wyeth, as well as by public funds from the Centre National de la Recherche Scientifique.

The authors have no conflicts of interest to disclose.

Figure Jump LinkFigure 1. Flow diagram of the 1,692 patients with severe sepsis who formed the basis for the study and who were taken from the 4,860 patients included in the OutcomeRea database. Data are expressed as No. (%).Grahic Jump Location
Table Graphic Jump Location
Table 1. Baseline Characteristics of the 1,692 Patients With Severe Sepsis According to Gender*
* 

Data are presented as median (first and third quartiles) or No. (%). The total number of sites of infection is greater than the number of patients because some patients had infection at more than one site. APACHE = acute physiology and chronic health evaluation.

 

As there were 124 missing values in the height and/or weight measurements, body mass index was not taken into account in the logistic regression model of factors associated with death. A subgroup analysis of clusters without missing body mass index values produced a similar result.

 

Referred to the main symptom that led to ICU admission.

§ 

Organ dysfunction from severe sepsis (see text for definition).

 

Type of microorganism causing sepsis for all sites of infection. We specified only main types. Some patients had multiple microorganisms.

Table Graphic Jump Location
Table 2. Variables Independently Associated With Death in the Logistic Regression Analysis of Data From Patients With Severe Sepsis*
* 

The variables not found significant in the multivariate regression were age; shock; acute respiratory failure; exacerbation of COPD; McCabe score; peritonitis, primary bacteremia, or multiple sites of infection; chronic hepatic failure; hematologic malignancy; need for arterial and central venous lines; hemodialysis within the first 2 days, and type of microorganism (E coli, S pneumoniae, and Enterobacter species). Final model: Hosmer-Lemeshow of 11.3 (p = 0.18) indicated a good fit (C statistic = 0.80).

 

According to Knaus definitions.

Table Graphic Jump Location
Table 3. Influence of Gender on Mortality in Patients With Severe Sepsis*
* 

These results were obtained using conditional logistic regression with matching on age, death propensity score, and center.

 

Chronic respiratory failure; metastatic cancer; immunocompromised status; emergency surgery; acute respiratory failure and shock at hospital admission; urinary tract infection as a cause of sepsis; and type of microorganism (E coli, S pneumoniae, and Enterobacter species).

 

OR of death according to conditional logistic regression.

Table Graphic Jump Location
Table 4. Level of Care and Use of Invasive Procedures at Hospital Admission in the Cross-Matched Population of Patients With Severe Sepsis*
* 

Data are presented as No. (%) or median (first-third quartiles).

We are indebted to A. Wolfe, MD, for helping with this manuscript.

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Angstwurm, MW, Gaertner, R, Schopohl, J Outcome in elderly patients with severe infection is influenced by sex hormones but not gender.Crit Care Med2005;33,2786-2793. [PubMed]
 
Sam, AD, II, Sharma, AC, Lee, LY, et al Sepsis produces depression of testosterone and steroidogenic acute regulatory (StAR) protein.Shock1999;11,298-301. [PubMed]
 
Mechanick, JI, Nierman, DM Gonadal steroids in critical illness.Crit Care Clin2006;22,87-103. [PubMed]
 
Zhao, Y, Nichols, JE, Valdez, R, et al Tumor necrosis factor-α stimulates aromatase gene expression in human adipose stromal cells through use of an activating protein-1 binding site upstream of promoter 1.4.Mol Endocrinol1996;10,1350-1357. [PubMed]
 
Macdiarmid, F, Wang, D, Duncan, LJ, et al Stimulation of aromatase activity in breast fibroblasts by tumor necrosis factor α.Mol Cell Endocrinol1994;106,17-21. [PubMed]
 

Figures

Figure Jump LinkFigure 1. Flow diagram of the 1,692 patients with severe sepsis who formed the basis for the study and who were taken from the 4,860 patients included in the OutcomeRea database. Data are expressed as No. (%).Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1. Baseline Characteristics of the 1,692 Patients With Severe Sepsis According to Gender*
* 

Data are presented as median (first and third quartiles) or No. (%). The total number of sites of infection is greater than the number of patients because some patients had infection at more than one site. APACHE = acute physiology and chronic health evaluation.

 

As there were 124 missing values in the height and/or weight measurements, body mass index was not taken into account in the logistic regression model of factors associated with death. A subgroup analysis of clusters without missing body mass index values produced a similar result.

 

Referred to the main symptom that led to ICU admission.

§ 

Organ dysfunction from severe sepsis (see text for definition).

 

Type of microorganism causing sepsis for all sites of infection. We specified only main types. Some patients had multiple microorganisms.

Table Graphic Jump Location
Table 2. Variables Independently Associated With Death in the Logistic Regression Analysis of Data From Patients With Severe Sepsis*
* 

The variables not found significant in the multivariate regression were age; shock; acute respiratory failure; exacerbation of COPD; McCabe score; peritonitis, primary bacteremia, or multiple sites of infection; chronic hepatic failure; hematologic malignancy; need for arterial and central venous lines; hemodialysis within the first 2 days, and type of microorganism (E coli, S pneumoniae, and Enterobacter species). Final model: Hosmer-Lemeshow of 11.3 (p = 0.18) indicated a good fit (C statistic = 0.80).

 

According to Knaus definitions.

Table Graphic Jump Location
Table 3. Influence of Gender on Mortality in Patients With Severe Sepsis*
* 

These results were obtained using conditional logistic regression with matching on age, death propensity score, and center.

 

Chronic respiratory failure; metastatic cancer; immunocompromised status; emergency surgery; acute respiratory failure and shock at hospital admission; urinary tract infection as a cause of sepsis; and type of microorganism (E coli, S pneumoniae, and Enterobacter species).

 

OR of death according to conditional logistic regression.

Table Graphic Jump Location
Table 4. Level of Care and Use of Invasive Procedures at Hospital Admission in the Cross-Matched Population of Patients With Severe Sepsis*
* 

Data are presented as No. (%) or median (first-third quartiles).

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Asai, K, Hiki, N, Mimura, Y, et al Gender differences in cytokine secretion by human peripheral blood mononuclear cells: role of estrogen in modulating LPS-induced cytokine secretion in anex vivoseptic model.Shock2001;16,340-343. [PubMed]
 
Angstwurm, MW, Gaertner, R, Schopohl, J Outcome in elderly patients with severe infection is influenced by sex hormones but not gender.Crit Care Med2005;33,2786-2793. [PubMed]
 
Sam, AD, II, Sharma, AC, Lee, LY, et al Sepsis produces depression of testosterone and steroidogenic acute regulatory (StAR) protein.Shock1999;11,298-301. [PubMed]
 
Mechanick, JI, Nierman, DM Gonadal steroids in critical illness.Crit Care Clin2006;22,87-103. [PubMed]
 
Zhao, Y, Nichols, JE, Valdez, R, et al Tumor necrosis factor-α stimulates aromatase gene expression in human adipose stromal cells through use of an activating protein-1 binding site upstream of promoter 1.4.Mol Endocrinol1996;10,1350-1357. [PubMed]
 
Macdiarmid, F, Wang, D, Duncan, LJ, et al Stimulation of aromatase activity in breast fibroblasts by tumor necrosis factor α.Mol Cell Endocrinol1994;106,17-21. [PubMed]
 
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