WO1995030765A1

WO1995030765A1 - Method for identifying and monitoring patients at risk for systemic inflammatory conditions

Info

Publication number: WO1995030765A1
Application number: PCT/US1995/005462
Authority: WO
Inventors: Gus J. Slotman
Original assignee: Slotman Gus J
Priority date: 1994-05-06
Filing date: 1995-05-03
Publication date: 1995-11-16
Also published as: EP0758399A1; EP0758399A4; JPH10500210A

Abstract

A method of subclinically identifying and monitoring patients at risk for developing a systemic inflammatory condition using a systemic mediator-associated physiologic test profile is provided.

Description

METHOD FOR IDENTIFYING AND MONITORING PATIENTS AT RISK FOR SYSTEMIC INFLAMMATORY CONDITIONS

Background of the Invention

Physiologic insults triggering the onset of systemic inflammatory conditions including sepsis, Adult Respiratory Distress Syndrome (ARDS), Systemic Inflammatory Response Syndrome (SIRS) and Multiple Organ Dysfunction Syndrome (MODS) have been identified to include infection and its systemic effects, shock, trauma, inhalation injury, pancreatitis, hypertransfusion, drug overdose, and near- drowning among others. The host response manifested in each of these insults includes increased capillary permeability, organ failure, and death. The mechanism of the response involves diffuse pathologic activation of inflammatory mediators including, but not limited to, endotoxin, leukotrienes B₄, C₄, D₄ and E₄, prostacyclin and thromboxane A₂, activated granulocytes and complement components C3a and C5a, tumor necrosis factor, interleukin-1, interleukin-6, interleukin-8, and other cytokines, neutrophil elastase, platelet activating factor, nitric oxide, and oxide radicals. As a result of identifying these causative factors and recent advances in the fields of monoclonal antibodies and recombinant human protein technology, several novel adjuvant treatments have been developed for patients with systemic inflammatory conditions such as sepsis, ARDS, SIRS and MODS. Experimental results and preliminary clinical data suggest that antibodies against gram-negative endotoxin and tumor necrosis factor, human recombinant protein antagonists of interleukin-1 and other cytokines, and inhibitors of platelet activating factor may be beneficial in sepsis, ARDS, MODS and other manifestations of SIRS. Other mediator modifying drugs, such as the cyclo-oxygenase inhibitor ibuprofen, and ketoconazole, a potent antagonist of thromboxane synthetase and 5-lipoxygenase may also be effective in the treatment of ARDS. The promise of these new drugs in the treatment of ARDS, sepsis, MODS and SIRS, however, has not been realized in confirmatory trials of pre-clinical and Phase II testing. One of the primary reasons for these therapeutic failures is the inability of investigators to identify specifically patients most likely to benefit from these treatments at an early stage in the host response, before the pathologic mediator activation that causes the systemic inflammatory response is manifested overtly. Accurate subclinical diagnosis and prediction of organ failure, septic shock and gram-negative infection are even less feasible. Consequently, patients are enrolled in prospective investigations of new treatments for ARDS, sepsis, MODS and SIRS using entry criteria that uniformly reflect late, clinically obvious sequelae of the underlying pathophysiologic processes. Studies of potentially beneficial drugs then fail because patients are enrolled after irreversible tissue damage has occurred, or because so many "at risk" patients must be entered to capture the target population that a drug effect can not be demonstrated, or because the spectra of disease entities and of clinical acuity in the study groups are too variable.

The optimal approach to finding new treatments for ARDS, SIRS, MODS, sepsis and related conditions would be to test new therapeutics in specifically identified patients with high power, accurately predicted risk of developing ARDS, SIRS, MODS, sepsis or a related condition at a time when the acute pathophysiology is still subclinical. Although there are several physiologic scoring systems available which measure the severity of illness, the degree of sepsis, the severity of trauma, or the intensity of organ system dysfunction and are used by physicians to identify certain patient populations, these systems are all based upon obvious, late clinical manifestations of the underlying inflammatory phenomena. The predictive power, accuracy, and specificity of these systems, therefore, are limited. The Injury Severity Score (ISS) was devised in 1974 as an adaptation of the Abbreviated Injury Scale (AIS). The ISS is a measure of the severity of anatomic injury in victims of blunt trauma and has been found to correlate well with mortality. The score is obtained by summing the squares of the three highest values obtained in five body regions, with 0 points for no injury and 5 points for a critical lesion. The ISS is the most widely used system for grading the severity of an injury; however, it has been criticized as there is a systematic underprediction of death and there is no adjustment for age as a risk factor. The Hospital Trauma Index (HTI) is an adaptation of the ISS which contains both anatomic and physiologic elements in six body regions. A good correlation between ISS, HTI and AIS has been shown. The Glascow Coma Scale (GCS) was also introduced in

1974 as a simple, reliable and generally applicable method for assessing and recording altered levels of consciousness. Eye opening, best motor response and best verbal response are monitored and scored independently on a scale ranging from 3 (worst) to 15 (best). The GCS has shown good correlation with functional outcome of survivors and therefore has been incorporated into several other scoring systems.

The Trauma Score (TS) was developed in 1980 for rapid assessment and field triage of injured patients. The TS measures physiologic changes caused by injury. It consists of respiratory and hemodynamic information, combined with the GCS. The TS has been shown to have a high predictability of survival and death.

Physiologic (TS) and anatomic (ISS) characteristics are combined in the TRISS scoring method used to quantify probability of survival following an injury. The method was developed for evaluating trauma care but can be applied to individual patients to estimate the probability of survival. The Sepsis Severity Score (SSS) was developed in 1983 for grading the severity of surgical sepsis. The system consists of a 6-point scale in seven organ systems including lung, kidney, coagulation, cardiovascular, liver, GI tract and neurologic. The final score is calculated by adding the squares of the highest three values of the three organs with the most severe dysfunction. Studies have shown significantly different scores in survivors versus nonsurvivors and the score correlated well with the length of hospital stay in the survivor group.

The Polytrauma Score (PTS), developed in 1985, is an anatomic injury severity score including an age classification. The score is thought to be more practicable than the ISS while having good correlation with the ISS. The Multiple Organ Failure Score (MOF score), developed in 1985, grades the function or dysfunction of the seven main organ systems including the pulmonary, cardiovascular, hepatic, renal, central nervous, hematologic, and gastrointestinal systems. This score has been shown to correlate well with mortality outcome.

Also in 1985, APACHE II, a revised version of APACHE (Acute Physiologic And Chronic Health Evaluation) was presented. APACHE II is a disease classification system developed to stratify acutely ill patients admitted to the Intensive Care Unit. Increasing scores have been shown to correlate well with hospital death. The score consists of an acute physiology score (APS), and age score, and a chronic health score. The APS is determined from the most deranged physiologic values during the initial 24 hours after ICU admission. The APACHE system, however, has not consistently predicted mortality risk for trauma patients. APACHE III is the latest revision of APACHE but like its predecessors, the system relies only upon clinically evident data and, therefore, is useful only for predicting mortality risk in selected groups of critical3.y ill patients.

In a study performed by Roumen, R.M. et al., The Journal of Trauma 35(3) :349-355, 1993, the relative value of several of these scoring systems in conjunction with measurement of plasma lactate concentration was examined in relation to the development of ARDS, MODS, or both in patients with severe multiple trauma. It was concluded that scoring systems directly grading the severity of groups of trauma patients have predictive value for late and remote complications such as ARDS and MODS, where as scoring systems that grade the physiologic response to trauma, while related to mortality, have no predictive value.

The scoring systems such as APACHE, TRISS, the Sepsis Score and the Multiple Organ Failure Score rely upon overt clinical signs of illnesses and laboratory parameters obtained after the appearance of clinical signs and, thus, are only useful in predicting mortality in a patient.

In a study performed on trauma patients at Denver General Hospital in Colorado, Sauaia, A. et al., Arch Surg. 129:39-45, 1994, found that early independent predictors of postinjury multiple organ failure include age greater than 55 years, an Injury Severity Score greater than or equal to 25, and receipt of greater than 6 units of red blood cells in a 12 hour period. Subgroup analysis indicated that base deficit and lactate levels could add substantial predictive value. In the present invention, a method for identifying systemic inflammatory conditions such as ARDS, SIRS, sepsis and MODS at a subclinical stage is provided which is based upon the simultaneous measurement of the physiological clinical response to pro-inflammatory insults and the subclinical activation of biochemical and cellular inflammatory mediators. This Systemic Mediator Associated Response Test (SMART) is useful in diagnosing impending ARDS, bacteremia, sepsis, SIRS, organ failure, MODS and other acute conditions before clinical signs of these tissue level phenomena become apparent. A SMART patient profile can be generated and compared to established baseline values or to a patient's normal values to assess a patient's risk of developing a systemic inflammatory condition.

Summary of the Invention An object of the invention is to provide a method of subclinically identifying patients at risk for developing a systemic inflammatory condition which comprises measuring physiologic parameters in a patient, generating a systemic mediator-associated response test (SMART) profile for the patient from the measured physiologic parameters, and comparing this profile with an established control profile to identify patients at risk of developing a systemic inflammatory condition based on the comparison. Further diagnostic and predicted accuracy of this SMART profile is provided by serial measurements of physiological parameters which are compared to clinical database profile patterns of change related to the development of a systemic inflammatory condition. Treatment of patients at risk of developing a systemic inflammatory condition can be evaluated by monitoring changes in a patient's SMART profile. Another object of the invention is to provide a patient SMART profile generated from measured physiologic parameters in a patient.

Detailed Description of the Invention The development of systemic inflammatory conditions represents a significant portion of the morbidity incidence which occur in the intensive care unit (ICU) . The term "systemic inflammatory conditions" is used herein to describe conditions which result in a host response manifested by increased capillary permeability, organ failure, and death. Examples of systemic inflammatory conditions include, but are not limited to, ARDS, SIRS, sepsis and MODS. Systemic inflammatory conditions such as ARDS, SIRS and MODS are responsible for more than 70% of the ventilator days spent on the ICU. In addition, ARDS, SIRS, sepsis and MODS are primary causes of death following surgery in surgical ICU patients, thus placing a heavy burden on the health care system.

It is believed that systemic inflammatory conditions, particularly ARDS, SIRS and MODS, are the result of a severe generalized autodestructive inflammation. ARDS is manifested clinically by hypoxemia, hypocapnia, diffuse infiltrates on chest roentgenogram and normal or low left ventricular filling pressures. Circulating prostaglandins, activated complement and abnormal intravascular aggregation of neutrophils have been implicated as possible mediators of ARDS. Slot an et al., Arch Sxxrg. 121:271-274, 1986. Thromboxane B₂ (TxB), prostaglandin 6-keto-Flα (PGI), activated complement components C3a and C5a, and granulocyte aggregation (GA) were found to be significantly elevated in all critically ill patients as compared to normal controls. For patients with ARDS the ratios of TxB/PGI and C3a/C5a also were significantly greater than controls. Differences between patients with and without ARDS in this study, however, were significant only for increased GA and plasma C3a in ARDS. Circulating prostaglandins, activated complement, and pathologic neutrophil aggregation are also involved in the clinical response to injury and infection and in the hemodynamic dysfunction of septic and hypovolemic shock. PGI, activated complement components C3a and C5a, and GA responses were significantly increased in critically ill patients as compared to normal control values. Slotman, G.J. et al., Surgery 99(6):744-750, 1986. TxB levels were also found to be significantly elevated in patients with severe sepsis and septic shock. Treatments for systemic inflammatory conditions have failed to reach their full potential as early subclinical identification of appropriate patients to participate in clinical efficacy studies has proven most difficult. Physiologic scoring systems which are used by physicians to predict mortality in a patient have generally proven insufficient in predicting the onset of a systemic inflammatory condition subclinically.

In the present invention a method of subclinically identifying patients at risk for developing a systemic inflammatory condition is provided which comprises measuring physiologic parameters in the patient, generating a Systemic Mediator-Associated Response Test (SMART) profile for the patient from the measured physiologic parameters, and comparing said profile with an established control profile to identify patients at risk of developing a systemic inflammatory condition based on the comparison. In addition to identifying patients at risk, a method is provided to subclinically monitor changes in selected physiologic parameters in patients to evaluate a treatment of a systemic inflammatory condition which comprises determining selected physiologic parameters of a patient; generating a SMART profile for the patient from the determined physiologic parameters; monitoring changes in selected physiologic parameters from said profile in a response to a treatment; and comparing the changes in the profile with an established control profile to monitor the treatment of patients at risk of developing a systemic inflammatory condition based on the comparison. For purposes of this invention, a "control profile" can either be generated from a data base containing mean values for the measured physiologic parameters from a population of patients with similar conditions and/or injuries or profiles of changing parameters associated with a similar condition and/or injury, or can be generated from the same patient to compare and monitor changes in the measured physiologic parameters over time.

The SMART profile of the present invention is generated in the following manner. Physiologic parameters which include, but are not limited to, physical examination, vital signs, hemodynamic measurements and calculations, clinical laboratory tests, concentrations of acute inflammatory response mediators, platelet and granulocyte aggregometry, and endotoxin levels in a patient are determined. Specifically levels of prostaglandin 6-keto Flα (PGI)(the stable metabolite of prostacyclin), thromboxane B₂ (TxB) (the stable metabolite of thromboxane A₂), leukotrienes B₄, C₄, D₄ and E₄, interleukin-lβ, interleukin-6, interleukin- 8, tumor necrosis factor, neutrophil elastase, complement components C3 and C5a, platelet activating factor, nitric oxide metabolites and endotoxin levels are determined in a biological sample obtained from a patient at baseline and daily thereafter. As one of skill in the art will appreciate upon this disclosure, as other significant inflammatory response mediators are identified, they can also be measured and incorporated into the database as part of the SMART profile. Examples of biological samples include, but are not limited to, blood, plasma, serum, urine, bronchioalveolar lavage, sputum, and cerebrospinal fluid.

PGI, TxB, and the leukotrienes B₄, C₄, D₄ and E₄ are derived from polyunsaturated fatty acids via arachidonic acid. These molecules play an important role in smooth muscle contraction, affecting blood pressure, blood flow, the degree of bronchial constriction and uterine contraction. Thromboxane is a potent vasoconstrictor and enhancer of platelet aggregation. Other prostaglandins and the leukotrienes promote the inflammatory response. Leukotrienes act as chemotactic agents, attracting leukocytes to the site of inflammation. Tumor necrosis factor α (TNFα) is a cytokine primarily produced by activated macrophages. TNFα stimulates T-cell and B-cell proliferation and induces expression of adhesion molecules on endothelial cells. This cytokine also plays an important role in host defense to infection. Platelet activating factor mediates platelet homeostasis and interacts with cytokines such as TNFα. Imbalances in PAF can result in uncontrolled bleeding or clot formation and a shock-like hemodynamic and metabolic state. The interleukins lβ, 6, and 8 and complement components C3a and C5a also play a major role in host defense to infection and in the host inflammatory response. Increased cytokine and complement levels in a patient are indicative of an infection and/or inflammation. Neutrophil elastase is an enzyme which hydrolyzes elastin. Elastin is a fibrous mucoprotein that is a major connective tissue protein in tissues with elasticity. Nitric oxide helps to regulate smooth muscle tone possibly through interaction with the prostaglandins and cytokines. The presence of increased nitric oxide metabolites in a biological sample may be - 10 - indicative of an imbalance in protein degradation or impairment of renal function in a patient. The presence of endotoxin in a biological sample obtained from the patient is indicative of a Gram negative bacterial infection. Such infections can lead to the development of shock in a patient. Pathological imbalances of the dynamic equilibrium among these and other biologically active substances cause endothelial damage, increased capillary permeability, and the cascade of subclinical events that leads to systemic inflammatory conditions such as sepsis, ARDS, SIRS, and MODS. In addition, demographic variables are recorded at baseline. Complete blood count, platelet count, prothrombin time, partial thromboplastin time, fibrin degradation products and D-dimer, serum creatinine, lactic acid bilirubin, AST, ALT, and GGT are measured at baseline and daily thereafter while the patient remains at risk for developing a systemic inflammatory condition. Heart rate, respiratory rate, blood pressure and urine output are monitored daily. A full hemodynamic profile is recorded in patients with pulmonary artery catheters and arterial blood gases are performed in patients on ventilators. Chest X-rays and bacterial cultures are performed as clinically indicated.

Continuous, normally distributed variables are evaluated using analysis of variance. Where appropriate, statistical comparisons between subgroups are made using the t-test or the chi-squared equation for categorical variables. Relative risks of developing sepsis or multiple organ failure are computed using a least square regression and logistic regression. To develop the predictive equation, data is analyzed for statistical modeling using the Cox proportional hazards survival model, log (-log) survival and hazard ratios, and parametric (log-logistic, log-normal, log-gamma) and non-parametric (Kaplan-Meier) survival estimates. Further predictive modelling is performed using bootstrapping, Somer's Dyx rank correlation, and receiver operating characteristic curves. The Cox, log (-log), Kaplan Meier, and other analytical methods described herein are commonly used for determining survival or mortality. In the present invention, these analytical tools are applied to the endpoint of developing a systemic inflammatory condition, in addition to survival or mortality.

The invention is further illustrated by the following nonlimiting examples.

EXAMPLES

Example 1: Measurement of plasma levels of the leukotrienes, prostaglandins, cytokines, platelet activating factor and neutrophil elastase

Plasma levels of leukotrienes B4, C4, D4 and E4,

TxB, PGI, TNF-α, interleukin-lβ, interleukin-6, neutrophil elastase and platelet activating factor are measured using ELISA immunoassay techniques. A blood sample from a patient is collected in a sterile polypropylene tube containing EDTA, indomethacin, and ketoconazole and spun immediately at 1500 g for 10 minutes at 4°C. The supernatant is pipetted into individual aliquots for each assay and stored at -70°C until the assay is performed. Sandwich and single antibody ELISA assays specific for each compound are performed using commercially available ELISA kits. Standard curve and known spiked standards in the mid-range of the detectable limit for each compound are included on each ELISA plate. Percent recovery and intra- and inter-assay coefficients of variation are calculated to ensure quality control of each assay.

Example 2: Radioimmunoassay of Complement Components C3a and C5a Plasma levels of complement components C3a des arg and C5a des arg are measured by radioimmunoassay. Blood samples are collected from patients and prepared as described in Example 1. Radioimmunoassay of C3a and C5a are then performed with commercially available standards, trace compounds and antisera according to standard radioimmunoassay procedures. Percent recovery and intra-assay variation coefficients of variation are calculated to ensure quality control of each assay. Example 3: Quantification of Nitric Oxide

Plasma concentration of nitric oxide are analyzed quantitatively by measurement of nitrate and nitrite, the stable in-products of nitric oxide metabolism, as an index of nitric oxide synthesis. Blood samples are obtained and processed as described in Example 1. The resulting plasma is deproteinized with 0.5 M NaOH and 10% ZnS04. Plasma nitrite/nitrate levels are determined using an automated procedure based on the Greiss reaction (Green LC, et al., Anal Biochem 126:131-138, 1982).

Example 4: Measurement of Plasma Endotoxin

Levels of endotoxin in plasma sample are measured by the triple metric modification of the Limulus amebocyte lysate assay for endotoxin. Blood sample are collected and processed as described in Example 1. Quantitative endotoxin measurements are performed with commercially available standards in Limulus lysate assay reagent (Associates of Cape Cod, Woods Hole, MA).

Example 5: Platelet Aggregometry Measurement of platelet aggregometry is performed using an automatic dual channel platelet aggregometer with platelet rich plasma prepared by standard laboratory techniques. Blood samples collected from patients are anticoagulated with EDTA, indomethacin and ketoconazole and immediately spun at 100 rpm for 10 minutes. The resultant platelet-rich plasma is removed. The remaining samples are then spun at 3,000 rpm for 30 minutes to obtain platelet-poor plasma. The number of platelets in the platelet-rich plasma is determined. The platelet-rich plasma is then adjusted to approximately 250,000 to 300,000 platelets per ml of plasma with autologous platelet-poor plasma from the same patient to form a platelet suspension. After adjustment 0.45 ml of the platelet suspension is transferred to a siliconized cuvette containing a siliconized stirring bar and allowed to warm for two minutes to 37°C. After warming, 1 μM ADP in 0.05 ml Hank's balanced salt solution is added and the resulting changes in light transmission are recorded. Changes in light transmission after the addition of 1 μM ADP to platelet-rich plasma from control samples prepared from blood of normal volunteer donors are compared to those produced with plasma from patients and expressed as the percentage of the maximum light transmission response of control samples to 1 μM ADP.

Example 6: Granulocyte Aggregometry

Measurement of granulocyte aggregation is performed using an automatic dual channel platelet aggregometer with granulocyte-rich plasma. Granulocyte-rich plasma is prepared in accordance with standard laboratory techniques described by Craddock et al., J Cl±n Invest 60:260-264, 1977, and modified by Hammerchmidt et al., Blood 55(6):898-902, 1980. Blood samples from patients are collected in pyrogen-free polypropylene tubes containing EDTA, indomethacin and ketoconazole. The samples are spun at 1500 g for 10 minutes at 4°C and the supernatant fraction pipetted off. Granulocyte suspension are prepared from blood of normal volunteer donors. Blood is withdrawn into a syringe containing EDTA, indomethacin and ketoconazole. The blood samples are then diluted with buffered saline, pH 7.4, layered over a 1.075/1.10 density Percoll gradient (Pharmacia Inc. Piscataway, NJ), and spun at 400 g for 45 minutes. The supernatant is discarded. The cell button is resuspended in 0.83% NH4C1, incubated at 37°C for 6 minutes and spun at 400 g for 5 minutes. This procedure to the cell button is then repeated. Following the second centrifugation, the cell button is washed three times with phosphate buffered saline, spun against at 400 g for 5 minutes and the supernatant discarded. The cell button is then resuspended in Hank's balanced salt solution with 0.5% bovine serum albumin. The cell suspension is counted and diluted to obtain a final concentration of 1 to 1.5 x 10⁷ cells per ml. A 0.45 ml aliquot of the cell suspension is added to a siliconized cuvette containing a siliconized stirring bar in a platelet aggregometer and allowed to warm for two minutes to 37°C. After warming, 0.05 ml of plasma from a patient is added to the cuvette and the resulting changes in light transmission are recorded. Changes in light transmission following addition of plasma from a patient are compared to those changes produced using the same cell suspension stimulated by control plasma activated with zymosan. Preparation of zymosan-activated plasma (ZAP) is described in Example 7, infra . Values are expressed as a percent of the maximum light transmission recorded after addition of ZAP.

Example 7: Preparation of zymosan-activated plasma (ZAP)

Blood from normal volunteer donors is drawn into heparinized syringes and centrifuged at 2800 rpm for 10 minutes to separate the plasma fraction. Zymosan solution (20 mg/ml) is added to the plasma to a concentration of 2.0 mg/ml. The plasma is then incubated at 37°C for 30 minutes with tumbling. The suspension is then cooled to 4°C and spun at 2800 rpm for 10 minutes. The ZAP is removed and the zymosan button discarded.

Example 8: Measured physiologic parameters from patients with sepsis.

Physiologic parameters in nine septic patients were monitored for 4 days. Each of these patients suffered from most, if not all, of the following: a fever greater than 100.4°F; a heart rate greater than 90 beats/minute; a respiratory rate greater than 20 breaths/min or mechanical ventilation required; other clinical evidence to support a diagnosis of sepsis syndrome; profound systemic hypotension characterized by a systolic blood pressure of less than 90 mm mercury or a mean arterial pressure less than 70 mm mercury; clinical dysfunction of the brain, lungs, liver, or coagulation system; a hyperdynamic cardiac index and systemic vascular resistance, and systemic metabolic/lactic acidosis. Levels of thromboxane B2, prostaglandin 6-keto Flα (PGI), leukotrienes B₄, C₄, D₄ and E₄, interleukin-lβ, tumor necrosis factor α, and interleukin-6 were measured serially in plasma from these patients. Leukotriene B₄ and/or tumor necrosis factor α were detectable in only two patients. Plasma levels of thromboxane B₂, PGI, and the complements of leukotrienes C₄, D₄ and E₄ were elevated above normal and increased significantly from baseline during the first 72 hours.

Plasma levels of interleukin-lβ did not change from baseline, however, levels of interleukin-6 rose sequentially to 118% of the baseline values. In 10 additional patients who received a 72 hour infusion of human recombinant interleukin-1 antagonist, at 72 hours thromboxane B₂, PGI, leukotrienes C₄, D₄ and E₄, and interleukin-6 plasma levels were significantly lower. Interleukin-lβ was significantly increased in these patients when compared with septic patients who received only standard care. Retrospective data analysis of the overall study suggested survival benefit in patients who received the interleukin-1 antagonist which, in the sub-group studied above, had lower prostaglandin, leukotriene, and IL-6 levels and higher plasma interleukin-1.

Claims

What is claimed is:

1. A method of subclinically identifying patients at risk for developing a systemic inflammatory condition comprising: a) determining selected physiologic parameters of a patient; b) generating a systemic mediator-associated response test profile for the patient from the determined physiologic parameters; and c) comparing said profile with an established control profile to identify patients at risk of developing a systemic inflammatory condition based on the comparison.

2. The method of claim 1 wherein the systemic inflammatory condition identified is ARDS, SIRS, sepsis or MODS.

3. The method of claim 1 wherein the selected physiologic parameters comprise physical examination, vital signs, hemodynamic measurements, clinical laboratory tests, concentrations of acute inflammatory response mediators, platelet and granulocyte aggregometry, and endotoxin levels.

4. A method of subclinically monitoring changes in selected physiologic parameters in patients to assess a treatment of a systemic inflammatory condition comprising: a) determining selected physiologic parameters of a patient; b) generating a systemic mediator-associated response test profile for the patient from the determined physiologic parameters; c) monitoring changes in selected physiologic parameters from said profile in a response to a treatment; and d) comparing said changes in said profile with an established control profile to monitor treatment of patients at risk of developing a systemic inflammatory condition based on the comparison.

5. The method of claim 4 wherein the systemic inflammatory condition being treated is ARDS, SIRS, sepsis or MODS.

6. The method of claim 4 wherein the selected physiologic parameters comprise physical examination, vital signs, hemodynamic measurements, clinical laboratory tests, concentrations of acute inflammatory response mediators, platelet and granulocyte aggregometry, and endotoxin levels.

7. A patient systemic mediator-associated response test profile generated from selected physiologic parameters and demographic variables determined in a patient.

8. The patient systemic mediator-associated response test profile of claim 7 wherein the selected physiologic parameters comprise a physical examination, vital signs, hemodynamic measurements, clinical laboratory tests, concentrations of acute inflammatory response mediators, platelet and granulocyte aggregometry, and endotoxin levels.