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«INFLAMMATORY PROTEINS, GENETIC VARIATION, AND ENVIRONMENTAL INFLUENCES ON HEALTH CARE ASSOCIATED INFECTION DEVELOPMENT IN SEPSIS A Dissertation ...»

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Data were analyzed with SAS (Version 9.1) using standard statistical techniques, including chi-square, student’s t-test, correlations, and Cox regression modeling.

Univariate testing was performed on all continuous variables, and variables not normally distributed were either log transformed to achieve a normal distribution or nonparametric tests were performed. Chi-square tests with expected cell counts less than five were analyzed using Fisher’s Exact test. An alpha level of 0.05 was considered statistically significant. Each aim includes pre-specified research questions and assumes complete data for the primary variables of interest.

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This aim investigates whether baseline protein expression levels of proinflammatory cytokines, anti-inflammatory cytokines, or their ratios influence the development of subsequent HAI in patients with sepsis.

Chi-square (χ2) tests were performed to test the proportions of patients with and without high systemic inflammation (4th quartile, IL-6 vs. other quartiles) who develop one or more HAI. χ2 tests were performed to test the proportions of patients with and without high systemic inflammation (4th quartile, IL-10 vs. other quartiles) who develop one or more HAI. The ratio of IL-6:IL-10 were calculated and each participant categorized based on their ratio. A ratio greater than 1 indicates a more prominent proinflammatory response, a ratio less than one indicates a more prominent antiinflammatory response. Student’s t was performed to determine prominent inflammatory response among those who do and do not develop one or more HAI. Mean cytokine levels (IL-6, IL-10) and their ratio (IL-6:IL-10) will be compared using student’s t among participants who do and do not develop a HAI during their ICU stay.

1.1 Does an exaggerated pro-inflammatory response influence subsequent HAI development in patients with sepsis?

1.2 Does an exaggerated anti-inflammatory response influence subsequent HAI development in patients with sepsis?

1.3 Do the ratios of pro-inflammatory and anti-inflammatory cytokines influence subsequent HAI development in patients with sepsis?

1.4 Describe baseline cytokine patterns among patients with sepsis who do and do not develop subsequent HAI?

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This aim investigates the variance in cytokine genes to determine if they influence levels of protein expression or development of HAI.

ANOVAs were performed to determine the cytokine levels for each genotype.

Chi-square analysis were also used to compare differences in common polymorphisms among those with exaggerated inflammation (4th quartile) at baseline as well as among those who do and do not develop HAIs.

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This aim investigates the effects of protein expression levels, genetic variation, and environment on development of HAI.

A series of Cox regression analyses was performed among those who did and did not develop HAIs during ICU stay (or up to 28 days in those with a prolonged ICU stay) controlling for a number of potentially confounding variables including age, race, sex, severity of illness (APACHE II), baseline cytokines, ICU length of stay, invasive device score, steroid use, and potential confounders. Questions 3.1-3.7 were answered by univariate testing. Questions 3.8 and 3.9 were answered by multivariate testing.

3.1. What is the risk ratio to predict development of HAI for each 10 point increase in APACHE II?

3.2. What is the risk ratio to predict development of HAI for each additional invasive devise?

3.3. What is the risks ratio to predict development of HAI given IL-6 -174G genotype?

3.4. What is the risks ratio to predict development of HAI given IL-10 -1082G genotype?

3.5. What is the risk ratio to predict development of HAI for each 10 point increase in pro-inflammatory cytokine?

3.6. What is the risk ratio to predict development of HAI for each 10 point increase in anti-inflammatory cytokine?

3.7. What is the risk ratio to predict development of HAI for each 10 point increase in ratio of pro- to anti-inflammatory cytokine?

3.8. Which variables are the strongest predictors of HAI development?

3.9. What is the final regression model for HAI?

CHAPTER 4. RESULTS

Study results are presented in this chapter. We begin with a description of study recruitment and baseline demographics including details surrounding the initial sepsis or suspected sepsis event. Next, we provide a detailed description among subjects developing HAI in this study. We then discuss several ICU outcome variables based on development of HAI and based on exaggerated or not exaggerated pro- or antiinflammatory response. Lastly, results are described by each specific aim.

Recruitment

Screening occurred over an 18 month period from February 2009 until July 2010.

Recruitment details are shown in Figures 4-1 and 4-2. A total of 539 subjects were screened with 215 (39.9%) meeting inclusion criteria. Among all patients meeting inclusion criteria, 105 (48.8%) met study related exclusion criteria, 32 (14.9%) had other reasons for exclusion, and 78 (36.3%) were enrolled. Approximately seven patients were screened for each patient enrolled. Some of the other reasons for exclusion included improvement and early transfer out of ICU, death, prior study subjects, or out of the window when evaluated.





Demographics and Baseline Infections

Subject demographics and clinical characteristics are shown in Table 4-1. The study population consisted of older (65.5 ± 12.6) male (97.9%) veterans who were admitted to the ICU primarily from the emergency room (48.7%) or general medical ward (30.8%) with sepsis as a primary or underlying condition. This population included a high percentage with co-morbidities (93.6%) with less than half (43.6%) having diabetes. This population had a high severity of illness given their high APACHE II (20.6 ± 6.4) and organ failure scores. Fifty (64.1%) subjects had at least two organ failures at baseline.

Characteristics of baseline infection findings at ICU admission are shown in Table 4-2 and a rank percentage of baseline organisms identified is shown in Table 4-3.

Among all baseline cultures, Staphylococcus Coagulase Negative was the most common microorganism, followed by Pseudomonas aeruginosa and Escherica coli. The most common type of infections among the 99 baseline infections were pneumonia (35.4% CAP or HACP) and urinary tract infection (31.3%). All patients had been placed on empiric antibiotics for their definitive or suspected infections at baseline. No microorganisms were identified in 22 (28.2%) subjects. There were similar numbers of subjects with gram positive and gram negative infections. Blood-stream infection accompanied 32.0% of identified infections, with no source identified in 2 (3.4%) subjects with a blood stream infection. Hypothermia or hyperthermia was present in 58 subjects. Baseline

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Legend: Down facing arrows denote protocols changes. The first arrow represents a protocol clarification of SIRS criteria by adding 10% bands. The second arrow represents a protocol change to allow recruitment of MICU patients located in the SICU unit.

Table 4-1. Demographic and Clinical Characteristics.

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Note: Data are reported as mean ± standard deviation, median (interquartile range), or count (percentage).

* BMI denotes body mass index. BMI range 11.0 - 72.6.

† Hospital days prior to ICU admission are reported as median (IQR), range 0 - 260.

There were 22 (28.2%) patients who were in the hospital greater than 3 days and 4 (5.1%) who were hospitalized for more than 28 days.

‡ Other reasons for ICU admission include: 3 post code, 2 non ST elevation myocardial infarctions, 2 gastro-intestinal bleeding, 1 congestive heart failure, 1 diabetic ketoacidosis, 3 post-op (carotid endarterectomy, knee replacement, gastric-tube placement with peritonitis).

§ The Charlson Comorbitidy Index includes 19 medical conditions with weighted scores ranging from 1 to 6 for each condition and a total possible score of 0 - 37.116

Table 4-1. Continued.

‖ Two subjects transferred from the ward had no prior steroids given on the ward or recorded in BCMA, but it was discovered upon later chart review that they received 1 dose of steroids 1 mg/kg in the ER. These subjects have been retained in all analysis following an intention to treat principle.

Table 4-2. Baseline Infection Findings at ICU Admission.

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Note: Data are reported as mean ± standard deviation, median (interquartile range), or count (percentage). The number of subjects is less than 78 for the following variables: Creactive protein (n = 65), lactate (n = 64), timing to ICU admission (n = 72), timing to first antibiotics (n = 71).

* Type of infection includes all infections. There were a total of 99 suspected or definitive infections in 78 patients. The total number of infections in each category is shown. Gastrointestinal or intrabdominal infections include four with C-difficile colitis, five with peritonitis, and one with cholecystitis. Cardiovascular system infections include two with catheter related infection and one with endocarditis. Bone and joint infections include one with osteomylitis and one with septic arthritis. CNS infection includes one with encephalitis and one with meningitis. Urinary tract infection includes one case of toxic shock syndrome post urology procedure detecting an abscess.

† Temperature range from 93.5 to 104.3°F.

‡ Manual differential counts were only done in 51 subjects.

§ Fluid bolus range from 0 - 14 liters.

Table 4-3. Most Common Baseline Micro-organisms.

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Note: The number and percentage is shown. This table is based on all cultures completed up to day 3. Only organisms present in at least 5 cultures are shown. There were 22 (28.2%) subjects with no baseline organism identified.

lactate and CPR levels were elevated. Subjects received an average of 3.3 liters of fluid resuscitation on the day of ICU admission. In general, fluids were given as a rapid bolus in response to hypotension but precise timing of fluid resuscitation was not recorded.

The maximum volume received among participants was 14 liters in one patient, and there were 17 patients that did not require fluid resuscitation. Additionally, 25 (32.0%) required vasopressors and 34 (43.6%) required either conventional or non-invasive positive pressure ventilation at baseline. Median hours until first antibiotic and ICU admission were 1.5 and 4.6 hours, respectively.

Description of First Health Care Associated Infection

A total of 17 participants developed at least one HAI. Characteristics of the first HAI is shown in Table 4-4 and a rank percentages of organisms identified are shown in Table 4-5. Candida was responsible for 11 (64%) of all identified first HAIs. There were three species of Candida identified (Candida albicans, Candida glabrata, Candida tropicalis) in addition to others not identified. The second most frequent organism was Staphylococcus Coagulase Negative. The primary type of infection was bloodstream infection (47.1%) followed by pneumonia (23.5%) and urinary tract infection (17.6%).

Fever was present in approximately half (47%) who developed HAI and the average SIRS score was 2.1 ± 0.9. Fluid bolus was required in 4 (23.5%) with the volume ranging from 0.5 to 5 liters. Three participants (17.7%) required vasopressors to support blood pressure, and 10 (58.8%) had moderate organ failure in 2 or more organs.

Lactate and CPR levels were elevated.

Measureable environmental factors included invasive devices, staffing ratios, and receipt of blood products. All participants (100%) developing HAI had a central line, 88.2% had a Foley catheter, and 70.5% were receiving mechanical ventilation (median 8 days) at the time of first HAI. Three participants (17.7%) had at least one eight hour period with a nurse-to-patient ratio of more than 2:1 within 48 hours preceding the first HAI. Seven participants (41.2%) received blood products within 48 hours preceding the first HAI.

Differences in Variables among Those Who Did and Did Not Develop HAI

A summary of ICU outcomes is shown in Table 4-6 for all participants comparing those who did and did not develop HAI. There were several significant differences between those who did and did not develop HAI. Those who developed HAI had a higher number of invasive devices (p = 0.04) at ICU discharge as well as a higher cummulative invasive device score (p 0.0001). Those developeing HAI had a higher number of organs with at least moderate dysfuction (2.4 ± 2.3 vs. 1.1 ± 1.3, p = 0.04), required more use of vasopressors (64.7% vs. 27.9%, p=0.009) with more episodes of new shock (p = 0.003). Those developing HAI had an average ICU length of stay more Table 4-4. Description of First Health Care Associated Infection.

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Note: Data are reported as mean ± standard deviation, median (interquartile range), or count (percentage).

* Two patients had prior mechanical ventilation during this ICU stay but were off for more than 48 hours at the time of their HAI. One had received three days of MV and off five days when HAI developed; the other had been on MV five days, and off six days when HAI developed.

Table 4-5. First HAI Micro-organisms (Ranked).

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Candida species involved 11 (64%) of all 17 identified first HAIs.

* 2 HCAP, 3 fungemia. One Candida albicans was mixed with Klebsiella pneumoniae in the BAL.

† 2 blood stream infections, 1 HCAP, 1 Cardiovascular system infection –VASC.

Two Coagulate Negative Staphylococcus were mixed, one with Candida albicans in the BAL and the other with Candida tropicalis in the blood ‡ 2 fungemia § 2 UTI, 1 with fungemia ‖ UTI HCAP # VAP Table 4-6. Differences in Variables among Those Who Did and Did Not Develop Health Care Associated Infections.

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