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Age-related differences in symptoms, diagnosis and prognosis of bacteremia
BMC Infectious Diseasesvolume 13, Article number: 346 (2013)
Elderly patients are at particular risk for bacteremia and sepsis. Atypicalpresentation may complicate the diagnosis. We studied patients withbacteremia, in order to assess possible age-related effects on the clinicalpresentation and course of severe infections.
We reviewed the records of 680 patients hospitalized between 1994 and 2004.All patients were diagnosed with bacteremia, 450 caused by Escherichiacoli and 230 by Streptococcus pneumoniae. Descriptiveanalyses were performed for three age groups (< 65 years,65–84 years, ≥ 85 years). In multivariate analyses age wasdichotomized (< 65, ≥ 65 years). Symptoms werecategorized into atypical or typical. Prognostic sensitivity of CRP and SIRSin identifying early organ failure was studied at different cut-off values.Outcome variables were organ failure within one day after admission andin-hospital mortality.
The higher age-groups more often presented atypical symptoms (p <0.001),decline in general health (p=0.029), and higher in-hospital mortality(p<0.001). The prognostic sensitivity of CRP did not differ between agegroups, but in those ≥ 85 years the prognostic sensitivity oftwo SIRS criteria was lower than that of three criteria. Classical symptomswere protective for early organ failure (OR 0.67, 95% CI 0.45-0.99), andrisk factors included; age ≥ 65 years (OR 1.65, 95% CI1.09-2.49), comorbid illnesses (OR 1.19, 95% CI 1.02-1.40 per diagnosis),decline in general health (OR 2.28, 95% CI 1.58-3.27), tachycardia (OR 1.50,95% CI 1.02-2.20), tachypnea (OR 3.86, 95% CI 2.64-5.66), and leukopenia (OR4.16, 95% CI 1.59-10.91). Fever was protective for in-hospital mortality (OR0.46, 95% CI 0.24-0.89), and risk factors included; age ≥ 65years (OR 15.02, 95% CI 3.68-61.29), ≥ 1 comorbid illness (OR2.61, 95% CI 1.11-6.14), bacteremia caused by S.pneumoniae (OR 2.79, 95% CI 1.43-5.46), leukopenia (OR 4.62,95% CI 1.88-11.37), and number of early failing organs (OR 3.06, 95% CI2.20-4.27 per failing organ).
Elderly patients with bacteremia more often present with atypical symptomsand reduced general health. The SIRS-criteria have poorer sensitivity foridentifying organ failure in these patients. Advanced age, comorbidity,decline in general health, pneumococcal infection, and absence of classicalsymptoms are markers of a poor prognosis.
The incidence of sepsis in humans has been shown to increase with age [1–3]. Elderly patients are at particular risk for bacteremia and sepsis owingto multiple factors such as comorbid illnesses, immunosenescence, malnutrition,instrumentation and institutionalization . Previous studies have identified age as an independent risk factor fordeath due to sepsis [3, 5, 6] and for severe bloodstream infections [7–12], although conflicting results are also reported .
The clinical presentation of sepsis is often atypical in elderly patients,complicating and potentially delaying diagnosis . A decline in general health and unspecific functional deterioration,such as reduced ability to perform daily tasks, may be the only symptoms of severeillness, including sepsis . Possible effects of age-related biological changes upon the clinicalcourse or prognosis of sepsis are not well described. In addition, it is not knownwhether atypical presentation is predictive of severe sepsis or death whenestablished criteria for sepsis and organ failure are used.
To address the special challenges regarding clinical evaluations of elderly patientswith severe infection we studied 1) the clinical presentation and severity relatedto age, 2) age linked differences in prognostic sensitivity of C-reactive protein(CRP) and systemic inflammatory response syndrome (SIRS) for early organ failure,and 3) whether age and age-related clinical presentation are additional risk factorsfor early organ failure and death, in a mixed group of patients withcommunity-acquired bacteremia caused by E. coli or S.pneumoniae.
Patients and setting
This study was conducted at Aker University Hospital in Oslo, Norway, between1994 and 2004. During the study period, the hospital had 350 beds and served apopulation of 500,000 people for urology and abdominal vascular surgery, and180,000 people for internal medicine, general surgery and psychiatry.
Medical records for all adult (≥ 16 years) patients admitted duringthe study period with culture-verified bacteremia due to E.coli or S. pneumoniae infection were retrievedfrom the hospital’s bacteriology laboratory database. Patients who hadmore than one episode of bacteremia during the study period were registered onlyonce in the study. As we wanted to study community-acquired infections, weincluded only patients who had blood cultures drawn on the day of or day afterhospital admission. Only patients with medical records available were includedin the study.
The following clinical data on comorbidities, risk factors for infection,diagnoses, signs and symptoms were extracted from medical records for allpatients included in the study.
Comorbid illnesses specified in the medical records were extracted andcategorized using a predefined list. Malignant disease was registered in casesof cancer or hematological malignancy. Alcoholism was registered whenaccompanied by organ involvement or social decompensation. Chronic renal failurewas registered if repeated creatinine values > 500 μmol/L in precedingadmissions, differentiated as severe if combined with dialysis or medicationspecific for renal failure, and as moderate chronic if neither dialysis normedication specific for renal failure was recorded. Heart failure andcardiomyopathy were both registered as heart failure.
Risk factors for infection included having an indwelling urinary catheter,surgical procedure at site of infection within the two weeks prior to admission,obstruction of the gastrointestinal or urinary tracts, and chronic inflammation.Medication with implicit risk for infection included use of corticosteroids≥ a dose equivalent to 10 mg prednisolone per day, chemotherapy in the twoweeks before admission or other immunosuppressive medication on a dailybasis.
Tentative diagnoses by the admitting physicians were categorized into infection,non-specific diagnoses (including delirium and acute deterioration in theability to perform daily tasks), organ-specific diagnoses not indicating aninfection (i.e. myocardial infarction, acute abdominal pain, acute asthma), andmissing/others.
Symptoms indicative of infection preceding admission were dichotomized into“classical symptoms” and “atypical symptoms”.“Classical symptoms” included fever/chills, localized pain,nausea/vomiting, diarrhea, cough, dyspnea, expectoration, urinary urgency,painful voiding, hematuria, skin rash, coma, and seizures, whereas“atypical symptoms” included malaise, falls, dizziness, syncope,unsteadiness, immobility, acute urinary or fecal incontinence, paresis, speakingdifficulties, and confusion.
Signs of infection in the emergency department (ED) included decline in generalhealth if recorded. Findings during the physical examination indicative oflocalized pathology were recorded, and markers of systemic inflammatory responsesyndrome (SIRS) were registered according to international standards . The SIRS criteria include body temperature more than 38.0°C orless than 36.0°C; heart rate more than 90 beats per minute; tachypneamanifested by a respiratory rate more than 20 breaths per minute or as a partialpressure of CO2 below 4.30 kPa; and a white blood cell count greaterthan 12,000/mm3 or below 4,000/mm3. The SIRS criteria wereconsidered not met if data were not recorded. We used two alternative cut pointsfor SIRS, ≥ 2 criteria met (SIRS-2) and ≥ 3 criteria met (SIRS-3).Cut points from the Simplified Acute Physiology Score (SAPS)  were used to define hypothermia (body temperature less than36.0°C), fever (body temperature ≥ 38.5°C), leukocytosis(leukocyte counts above 15,000/mm3), and leukopenia (leukocyte countsbelow 3,000/mm3). C-reactive protein (CRP) values from blood samplesdrawn on the day of admission were categorized at 80 mg/L, which is applicablefor predicting sepsis in patients with SIRS , and 200 mg/L, which is the suggested level for differentiatinginfection from other causes of shock . We included new-onset atrial fibrillation as a marker of severeinfection, as described previously .
Presumed primary site of infection was identified by one of the clinicallytrained authors (ALW) based on the medical history, symptoms, physicalexamination, blood tests, X-rays, specimen cultures from other body sites thanblood, biopsies from surgical procedures, and autopsies. The sites of infectionwere categorized into urinary tract, lower respiratory tract, other (i.e.gastrointestinal tract, liver, pancreas and biliary tract, central nervoussystem), or inconclusive.
Criteria for organ failure
Criteria for organ failure within one day after admission are presented in theAdditional file 1. Whenever possible, criteria weredefined according to the Sequential Organ Failure Assessment (SOFA) score system(cut point 2 or 3) . Indicators for organ dysfunction, defined in the diagnostic criteriafor sepsis in 2001  and for severe sepsis and septic shock in 1992 , were also used. Criteria for acute renal failure were adjusted tothe modified risk, injury, failure, loss and end-stage kidney (RIFLE) criteria , and on clinical presentation. Since the central nervous system isincluded in organ failure scoring systems for use in sepsis , we included impaired consciousness as an indicator of organ failure.However, signs of delirium were not included, because data on this state werenot routinely collected upon admission. Data on liver and hematological markersas well as markers of peripheral perfusion such as serum lactate were notsystematically registered in patient records, and were therefore excluded.
Date of death
Date of death during hospitalization was extracted from patient records. Foranalytical purposes, mortality was classified into early hospital mortality(within ≤ 3 days of admission), and in-hospital deathwithin 14 days of admission. Prior to the data extraction process survivalafter discharge from hospital had been confirmed through the National PopulationRegister by the medical record staff. If death had occurred after the indexstay, they had put the date onto the records.
In order to study any systematic differences in clinical presentation related tothe oldest patients, descriptive analyses were performed for three age groups(< 65 years, 65–84 yearsand ≥ 85 years). In the multivariate analyses, however,age was dichotomized (< 65 and ≥ 65) based on preliminaryanalyses. Categorical variables were presented as absolute numbers andpercentages and compared using Chi-squared tests. Normally distributed numericalvariables were compared using one-way ANOVA, and non-normal variables usingKruskal-Wallis tests and Mann–Whitney tests. The number of“classical” symptoms was dichotomized at three symptoms,“atypical” symptoms were dichotomized at one symptom.
Non-parametric correlation analysis (Spearman rho) was performed to study therelationship between CRP value at admission and the number of failing organswithin one day of admission. The associations between organ failure anddifferent cut-points of CRP and different number of SIRS criteria were exploredusing Chi-squared tests.
In order to identify factors recorded upon admission to the ED independentlyassociated with either early organ failure or in-hospital death (truncated at14 days after admission to hospital), variables significantly associatedwith these outcomes (p < 0.05) in bivariate analyses were enteredinto binary logistic regression models. Ordinal factors not linearly associatedwith either of the two outcomes were dichotomized. For variable selection, weused backward stepwise removal of variables based on likelihood-ratio judgments.Model summary given in Nagelkerke R square and model of fit given by the Hosmerand Lemeshow test were applied. We also tested for any interactions between thedichotomized age variable and the other factors in the full main effects models.To obtain the logit of the two outcomes when interactions were active, the macroModprobe developed and adjusted to SPSS by Hayes and Matthes was applied . However, since the statistical power of interaction analyses isgenerally low, the effects of interacting variables on outcomes are presentedonly as directions rather than graphically or by numbers.
One-year survival by number of early failing organs, bacterial species, and agewere analyzed using Kaplan Meier survival analysis, applying the log-rank test.A Kaplan Meier plot was used to present the results graphically. All analyseswere performed with SPSS 17.0 software (SPSS, Chicago, IL).
The study was approved by the South-East Norway Regional Committee for Ethics inMedical Research. The Norwegian Data Inspectorate gave permission to carry outthe study without the patient consent. Dispensation of professionalconfidentiality was given by the Norwegian Directorate of Health.
Between 1994 and 2004, 1150 patients had a blood culture positive for eitherE. coli or S. pneumoniae. Of these, 759 hadthe positive blood culture drawn on the day of admission or the following day. For79 patients the clinical data was either unavailable or inadequate for analyses. Intotal, a cohort of 680 patients was eligible for the study.
Table 1 presents basic characteristics, comorbid illnessesand clinical presentation by age group. The two oldest age groups had more comorbidillnesses and were more often admitted with non-specific tentative diagnoses thanthe youngest group. The two oldest age groups also differed from the youngest groupby less frequently having “classical” symptoms and more frequentlyhaving “atypical” symptoms. In addition, the two oldest age groupspresented more often with decline in general health, new-onset atrial fibrillationand reduced consciousness than the youngest group. Table 2 describes severity of infection by age group. The mean number offailing organs within one day after admission was significantly higher in the middlegroup than in the youngest age group. For the two oldest age groups, the site ofinfection was more difficult to determine than the youngest group. Furthermore, thetwo oldest age groups died earlier after admission and had higher in-hospital andone-year mortality than the youngest group.
The CRP values at admission were significantly correlated to the number of failingorgans within one day after admission (rs = 0.13,p = 0.001). Figure 1 shows the prognosticsensitivity with 95% confidence intervals of initial CRP value and of SIRS atdifferent cut-off values in predicting ≥1 organ failure by age group. Theprognostic sensitivity of a CRP value above 200 mg/L was lower in the middleage group than in the youngest group, whereas no age-associated differences wereseen at cut-off value 80 mg/L. The prognostic sensitivity of SIRS-2 was lowerthan that of SIRS-3 for the two oldest age groups, but not for the youngest agegroup.
In Table 3, predictors for early organ failure availableat admission are presented. Sufficient data on organ failure were available for 632patients. As can be seen, age over 65 years, number of comorbid illnesses, more thanthree “classical” symptoms present, decline in general health, tachypneaand/or hyperventilation, and leukopenia remained as independent and statisticallysignificant predictors in the multivariate model. The model contributed moderatelyto the prediction of having one or more failing organs (Nagelkerke R2 =0.289), and fitted the data well (χ2 = 9.42, p = 0.30). Advanced agesignificantly reduced the effect of tachypnea and/or hyperventilation and the numberof comorbid illnesses on the risk for early organ failure.
Table 4 shows risk factors for in-hospital death within 14days after admission. Age over 65 years, comorbidity, bacteraemia with pneumococci(rather than E. coli), leukopenia and number of failing organswithin one day after admission all remained as independent risk factors for death,whereas having fever was protective. The model contributed moderately to theprediction of hospital mortality (Nagelkerke R2 = 0.428), and fitted thedata well (χ2 = 3.2, p = 0.92). Advanced age significantly increasedthe effect of type of bacterium on hospital mortality. Type of tentative diagnosesbefore admission was not associated with mortality, whereas having “atypicalsymptoms” was significant only in bivariate analysis.
Figure 2 displays Kaplan Meier plots of one-year survivalcurves by age group, number of failing organs and microbial agent. There weresignificant differences in one-year survival for age and number of failing organs(p < 0.001 for both), but not for type of bacteria(p = 0.75).
In this material, comprising nearly 700 patients with bacteraemia caused byE. coli or S. pneumoniae, several resultsindicate that age affects the clinical presentation, diagnostic markers, and outcomeof severe infection.
Elderly patients more often presented with “atypical” symptoms likeconfusion, falls, malaise, incontinence and immobility, whereas“classical” symptoms of infection were more common among youngerpatients. The ED doctor’s impression of decline in general health was also amore frequent sign among the older patients. This reflects the general perception ingeriatric care , but has, to our knowledge, not previously been confirmed in a largecohort of bacteremic patients. Older patients die earlier during hospitalizationthan younger patients , and are more rarely transferred to an intensive care unit (ICU) , both also found in our study. We speculate whether advanced age to someextent reduces the chances of patients receiving proper clinical monitoring andtimely antibiotic treatment. In contrast, in our results there was no associationbetween age and the degree of missing data for bilirubin, arterial lactate andinternational standardized ratio (results not shown), indicating that the adequacyof monitoring was the same, irrespective of age.
Despite the efforts to broaden the understanding of sepsis diagnosis beyond SIRS,this entity is still used as rule in criteria for transfer to ICU and for aggressivetreatment. Elderly patients’ subtle presentation of infection makes thesensitivity of SIRS a matter of concern. Studies of the prognostic value of SIRS insepsis are scarce due to the fact that SIRS itself is generally part of theinclusion criteria. One study of ICU-patients with bacteremia caused byPseudomonas aeruginosa and Enterococcus found no differencesin SIRS between elderly and younger patients . In our material, the sensitivity for organ failure of three SIRScriteria was lower than that of two criteria in the elderly, whereas the confidenceintervals overlapped in the younger patients. If absence of SIRS is used as anexclusion criterion for tight observation and aggressive treatment, a prognosticsensitivity of about 60% is hardly satisfactory, and this finding is clearlyclinically relevant.
The usefulness of CRP in sepsis diagnosis has been questioned . A recent meta-analysis on a mixed group of ICU patients found that earlyCRP did not predict outcome, whereas CRP at Day 2 following admission did . Another study recently found that CRP is a useful marker of sepsisresolution . In our study, CRP at cut-off value 80 m mg/L was not associated toin-hospital mortality within 14 days after admission, whereas CRP at cut-off value200 mg/L was, but only in the univariate analysis. Interestingly, we found that thesensitivity of a high CRP-level in the diagnosis of organ failure in bacteraemia islower in elderly patients than in younger patients.
Age was clearly associated with both early organ failure and in-hospital mortality,reflecting the findings of other studies [3, 5, 6]. It is possible that these findings could have been confounded byage-associated clinical presentation hampering the diagnostic work-up and thetimeliness of treatment, rather than age being considered a risk factor in itself.Early diagnosis of sepsis is a prerequisite for early goal directed therapy, whichimproves outcome . Decline in functional status, together with fever, defined by lowercut-off values than those used in SIRS and SAPS [15, 16], are important criteria for suspecting infection in older patients . Decline in functional status includes new or increasing confusion,incontinence, falling, deteriorating mobility, reduced food intake, or failure tocooperate with staff, which partly corresponds to “atypical symptoms”assessed in our study. It might constitute a problem that such “softvariables” are not included in mortality-prediction rules for elderly EDpatients with infection . Our study indicates that such clinical presentations may be associatedwith severity of infection, though not statistically significant in the multivariatefull model.
A subtle presentation may complicate the diagnosis of infections in elderly patients . In our material, clinical judgment on general health in the EDindependently predicted organ failure. The International Sepsis DefinitionConference in 2001 acknowledged the value of clinical judgment: “Few,if any, patients in the early stages of the inflammatory responseto infection are diagnosed with sepsis via four arbitrary criteria.Instead the clinician goes to the bedside, identifies a myriad ofsymptoms and regardless of an evident infection declares the patient to“look septic” . The updated Surviving Sepsis Campaign guidelines acknowledge clinicaljudgment even stronger: “Recommendations from these guidelines cannotreplace the clinician’s decision-making capability whenhe or she is provided with at patients’ unique set of clinicalvariables”. However, studies on the effectiveness of clinicaljudgment in predicting prognosis are scarce. Several studies on severe infection andsepsis did not include “soft” variables, and instead focused onbiomarkers and score systems.
Traditionally, prognostication in critical illness has relied heavily upon measuresof acute physiological derangements upon admission to ICU, as scoring systems do notintegrate pre-hospital functional status, severity of comorbid illness, disabilityor frailty . Cancer, diabetes or cardiovascular disease are the most importantfactors for health-related quality of life after critical illness . Comorbidity, quantified by the Charlson comorbidity index, is aprognostic factor for in-hospital mortality . In our study, the number of comorbid illnesses and comorbiditydichotomized at ≥ 1 illness were independently associated to early organfailure and in-hospital mortality, respectively.
The main strength of the study was that patients were recruited non-selectively andfrom a mixed group of hospital patients. All patients who were admitted to thehospital over more than a decade were included in the study population. A majorweakness is that data were retrospectively collected. Thus, systematic informationon adequacy of antimicrobial treatment was missing and was therefore omitted fromthe analyses. Furthermore, the validity of the estimated number of failing organsmay be uncertain. We may have overestimated organ failure because we did not excludefailure in the organ that was considered primary source for infection. Conversely,organ failure may also have been underestimated because data on liver function andhematological markers as well as markers of peripheral perfusion wereunsystematically registered and therefore excluded. The survival curve by number offailing organs (the middle part of Figure 2), however, isvery similar to 1-year survival curves found by others . We identified leukopenia as a risk factor for poor prognosis in themultivariate models, which corresponds well with neutropenia being one of theclinical risk factors for mortality in sepsis found in several trials . We believe these findings support the importance of the“geriatric-focused results” found in our study.
Elderly patients with bacteremia more often present with atypical symptoms andreduced general condition. SIRS have poorer sensitivity for identifying severeinfection in these patients, and should be less emphasized when assessing the riskof sepsis in elderly patients. Advanced age and comorbidity are risk factors forboth early organ failure and in-hospital mortality. An uncertain clinicalpresentation, however, does not seem associated with in-hospital mortality.Irrespective of age, simple observations such as the subjective judgment of declinein general health, as well as single aspects of SIRS such as tachypnea,hyperventilation and leukopenia, alongside with indicators of organ failure, arecrucial when evaluating patients with possible severe infection. Because theclinical presentation is often atypical in advanced age, these clinical evaluationsmay be seen as keys to safer care for elderly patients with severe infection.
● high age and comorbidity are risk factors for pooroutcome in severe infection.
● reduced general health at admittance is underestimatedas a prognostic tool.
SystemicInflammatory Response Syndrome
≥ 2 SIRS-criteria
Simplified Acute Physiology Score
Sequential Organ Failure Assessment
Risk, Injury, Failure, Loss,End-stage kidney
Intensive Care Unit.
Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR: Epidemiology of severe sepsis in the United States: analysis of incidence,outcome, and associated costs of care. Crit Care Med. 2001, 29 (7): 1303-1310. 10.1097/00003246-200107000-00002.
Flaatten H: Epidemiology of sepsis in Norway in 1999. Crit Care. 2004, 8 (4): R180-R184. 10.1186/cc2867.
Martin GS, Mannino DM, Moss M: The effect of age on the development and outcome of adult sepsis. Crit Care Med. 2006, 34 (1): 15-21. 10.1097/01.CCM.0000194535.82812.BA.
Girard TD, Opal SM, Ely EW: Insights into severe sepsis in older patients: from epidemiology toevidence-based management. Clin Infect Dis. 2005, 40 (5): 719-727. 10.1086/427876.
Knaus WA, Harrell FE, Fisher CJ, et al: The clinical evaluation of new drugs for sepsis. A prospective study designbased on survival analysis. JAMA. 1993, 270 (10): 1233-1241. 10.1001/jama.1993.03510100083038.
Nasa P, Juneja D, Singh O, Dang R, Arora V: Severe sepsis and its impact on outcome in elderly and very elderly patientsadmitted in intensive care unit. J Intensive Care Med. 2011, 27 (3): 179-183.
Harbarth S, Ferriere K, Hugonnet S, Ricou B, Suter P, Pittet D: Epidemiology and prognostic determinants of bloodstream infections insurgical intensive care. Arch Surg. 2002, 137 (12): 1353-1359. 10.1001/archsurg.137.12.1353.
Kalin M, Ortqvist A, Almela M, et al: Prospective study of prognostic factors in community-acquired bacteremicpneumococcal disease in 5 countries. J Infect Dis. 2000, 182 (3): 840-847. 10.1086/315760.
Laupland KB, Gregson DB, Zygun DA, Doig CJ, Mortis G, Church DL: Severe bloodstream infections: a population-based assessment. Crit Care Med. 2004, 32 (4): 992-997. 10.1097/01.CCM.0000119424.31648.1E.
Laupland KB, Davies HD, Church DL, et al: Bloodstream infection-associated sepsis and septic shock in critically illadults: a population-based study. Infection. 2004, 32 (2): 59-64. 10.1007/s15010-004-3064-6.
Torres JM, Cardenas O, Vasquez A, Schlossberg D: Streptococcus pneumoniae bacteremia in a community hospital. Chest. 1998, 113 (2): 387-390. 10.1378/chest.113.2.387.
Wu HS, Wang FD, Tseng CP, Wu TH, Lin YT, Fung CP: Characteristics of healthcare-associated and community-acquired Klebsiellapneumoniae bacteremia in Taiwan. J Infect. 2012, 64 (2): 162-168. 10.1016/j.jinf.2011.11.005.
Garnacho-Montero J, Garcia-Garmendia JL, Barrero-Almodovar A, Jimenez-Jimenez FJ, Perez-Paredes C, Ortiz-Leyba C: Impact of adequate empirical antibiotic therapy on the outcome of patientsadmitted to the intensive care unit with sepsis. Crit Care Med. 2003, 31 (12): 2742-2751. 10.1097/01.CCM.0000098031.24329.10.
Banerjee J: The frail old person in the emergency department. Oxford Desk Reference: Geriatric medicine. Edited by: HACS, Gosney M. 2012, Oxford: Oxford Univdersity Press, 48-49.
Bone RC, Balk RA, Cerra FB, et al: Definitions for sepsis and organ failure and guidelines for the use ofinnovative therapies in sepsis. The ACCP/SCCM Consensus ConferenceCommittee. American College of Chest Physicians/Society of Critical CareMedicine. Chest. 1992, 101 (6): 1644-1655. 10.1378/chest.101.6.1644.
Le Gall JR, Loirat P, Alperovitch A, et al: A simplified acute physiology score for ICU patients. Crit Care Med. 1984, 12 (11): 975-977. 10.1097/00003246-198411000-00012.
Sierra R, Rello J, Bailen MA, et al: C-reactive protein used as an early indicator of infection in patients withsystemic inflammatory response syndrome. Int Care Med. 2004, 30 (11): 2038-2045. 10.1007/s00134-004-2434-y.
Best Practice: Diagnostic tests; shock. BMJ Evidence Center. 2012, http://bestpractice.bmj.com/best-practice/monograph/1013/diagnosis/tests.html,
Kindem IA, Reindal EK, Wester AL, Blaasaas KG, Atar D: New-onset atrial fibrillation in bacteremia is not associated with C-reactiveprotein, but is an indicator of increased mortality duringhospitalization. Cardiology. 2008, 111 (3): 171-180. 10.1159/000121600.
Vincent JL, De MA, Cantraine F, et al: Use of the SOFA score to assess the incidence of organ dysfunction/failure inintensive care units: results of a multicenter, prospective study. Workinggroup on “sepsis-related problems” of the European Society ofIntensive Care Medicine. Crit Care Med. 1998, 26 (1): 1793-1800.
Levy MM, Fink MP, Marshall JC, et al: 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med. 2003, 31 (4): 1250-1256. 10.1097/01.CCM.0000050454.01978.3B.
Mehta RL, Kellum JA, Shah SV, et al: Acute kidney injury network: Report of an initiative to improve outcomes inacute kidney injury. Crit Care. 2007, 11 (2): R31-10.1186/cc5713.
Bernard GR: Quantification of organ dysfunction: seeking standardization. Crit Care Med. 1998, 26 (11): 1767-1768. 10.1097/00003246-199811000-00001.
Hayes AF, Matthes J: Computational procedures for probing interactions in OLS and logisticregression: SPSS and SAS implementations. Behav Res Methods. 2009, 41 (3): 924-936. 10.3758/BRM.41.3.924.
High KB: Infection in the elderly. Hazzard’s geriatric medicine and gerontology. Edited by: Halter JB. 2010, New York: McGraw Medical, 1507-1515. 6
Marra AR, Bar K, Bearman GM, Wenzel RP, Edmond MB: Systemic inflammatory response syndrome in nosocomial bloodstream infectionswith Pseudomonas aeruginosa and Enterococcus Species: comparison of elderlyand nonelderly patients. J Am Geriatr Soc. 2006, 54 (5): 804-808. 10.1111/j.1532-5415.2006.00698.x.
Silvestre J, Povoa P, Coelho L, et al: Is C-reactive protein a good prognostic marker in septic patients?. Int Care Med. 2009, 35 (5): 909-913. 10.1007/s00134-009-1402-y.
Zhang Z, Ni H: C-reactive protein as a predictor of mortality in critically ill patients: ameta-analysis and systematic review. Anaesth Int Care. 2011, 39 (5): 854-861.
Povoa P, Teixeira-Pinto AM, Carneiro AH: C-reactive protein, an early marker of community-acquired sepsis resolution:a multi-center prospective observational study. Crit Care. 2011, 15 (4): R169-10.1186/cc10313.
Rivers E, Nguyen B, Havstad S, et al: Early goal-directed therapy in the treatment of severe sepsis and septicshock. N Engl J Med. 2001, 345 (19): 1368-1377. 10.1056/NEJMoa010307.
High KP, Bradley SF, Gravenstein S, et al: Clinical practice guideline for the evaluation of fever and infection inolder adult residents of long-term care facilities: 2008 update by theInfectious Diseases Society of America. Clin Infect Dis. 2009, 48 (2): 149-171. 10.1086/595683.
Caterino JM, Kulchycki LK, Fischer CM, Wolfe RE, Shapiro NI: Risk factors for death in elderly emergency department patients withsuspected infection. J Am Geriatr Soc. 2009, 57 (7): 1184-1190. 10.1111/j.1532-5415.2009.02320.x.
Flaatten H: Intensive care in the very old: are we prepared?. Acta Anaesthesiol Scand. 2007, 51 (5): 519-521. 10.1111/j.1399-6576.2007.01299.x.
McDermid RC, Stelfox HT, Bagshaw SM: Frailty in the critically ill: a novel concept. Crit Care. 2011, 15 (1): 301-10.1186/cc9297.
Orwelius L, Nordlund A, Nordlund P, et al: Pre-existing disease: the most important factor for health related quality oflife long-term after critical illness: a prospective, longitudinal,multicentre trial. Crit Care. 2010, 14 (2): R67-10.1186/cc8967.
Poses RM, McClish DK, Smith WR, Bekes C, Scott WE: Prediction of survival of critically ill patients by admissioncomorbidity. J Clin Epidemiol. 1996, 49 (7): 743-747. 10.1016/0895-4356(96)00021-2.
Shapiro N, Howell MD, Bates DW, Angus DC, Ngo L, Talmor D: The association of sepsis syndrome and organ dysfunction with mortality inemergency department patients with suspected infection. Ann Emerg Med. 2006, 48 (5): 583-590. 10.1016/j.annemergmed.2006.07.007. 590,
Barriere SL, Lowry SF: An overview of mortality risk prediction in sepsis. Crit Care Med. 1995, 23 (2): 376-393. 10.1097/00003246-199502000-00026.
The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2334/13/346/prepub
Thanks to MD Ingvild A. Kindem and MD Eva K. Reindal for assisting in datagathering, to Professor Aage Tverdal for statistical advice and to ProfessorHans Flaatten for reviewing the manuscript and providing valuable input. Specialthanks also to Emily MacDonald for thorough revision and valuable inputs to theMS language.
The study was performed without specific funding.
The authors declare that they have no competing interests.
ALW participated in the concept and design of the study, gathered data onbacteraemia, serum markers of infection, clinical data on presentation of infection,performed the analyses and participated substantially in the writing of themanuscript. OD participated in concept and design, interpretation of the data andwriting of the manuscript. KKM participated in design and writing of the manuscript.URD assisted in the data interpretation and participated substantially in thewriting of the manuscript. TBW participated in design, data analysis andsubstantially in the writing of the manuscript. All authors read and approved thefinal manuscript.