Red cell distribution width predicts mortality in infective endocarditis




Summary


Background


Infective endocarditis (IE) is associated with significant morbidity and mortality. Red cell distribution width (RDW) is a recently recognized biomarker of adverse outcome in a number of acute and chronic conditions.


Aim


To investigate the relationship between RDW and 1-year survival in patients with IE.


Methods


Clinical records from two tertiary centres were used to analyze data from patients with definite IE. Clinical, echocardiographic and biochemical variables were evaluated along with RDW. One-year survival status after index hospitalization was identified for each patient.


Results


One hundred consecutive patients (mean age 47.8 ± 16.7 years; 61% men) with definite IE were enrolled. According to receiver operating characteristic curve analysis, the optimal RDW cut-off value for predicting mortality was 15.3% (area under the curve 0.70; P = 0.001). Forty-one patients (41%) died within 1 year; of these, 88% had RDW results > 15.3%. Univariate Cox proportional-hazards analysis showed that RDW > 15.3%, heart failure, renal failure, cardiac abscess, severe valvular regurgitation and presence of dehiscence were associated with increased mortality. Multivariable Cox proportional-hazards analysis revealed that renal failure (hazard ratio [HR] 3.21, 95% confidence interval [CI] 1.35–7.59; P = 0.008), heart failure (HR 2.77, 95% CI 1.1–6.97; P = 0.03) and RDW > 15.3% (HR 3.07, 95% CI 1.06–8.86; P = 0.03) were independent predictors of mortality in patients with IE.


Conclusion


According to our results, mortality is high in patients with IE. RDW is a promising biomarker for predicting 1-year survival rates in these patients.


Résumé


Justification


L’endocardite infectieuse est associée à une augmentation de la morbi-mortalité significative. La distribution érythrocytaire est un biomarqueur de description récente prédisant les complications dans différentes situations aiguës et chroniques.


Objectif


Évaluer la relation entre ce biomarqueur et la survie à un an chez des patients hospitalisés pour endocardite infectieuse.


Méthode


Les dossiers cliniques de deux centres tertiaires ont été utilisés pour analyser les informations à partir des dossiers de patients ayant une endocardite infectieuse certaine. Les données cliniques, échocardiographiques et biochimiques ont été évaluées parallèlement à l’évaluation de ce biomarqueur. La survie à un an après l’hospitalisation initiale a été identifiée pour chaque patient.


Résultats


Cent patients consécutifs (âge moyen 47,8 ± 16,7 ans ; 61 % d’hommes) ayant une endocardite infectieuse certaine ont été inclus. En utilisant l’analyse basée sur les surfaces sous la courbe ROC, la valeur seuil optimale pour ce biomarqueur prédisant la mortalité était de 15,3 % (surface sous la 0,70 ; p = 0,001). Quarante et un patients (41 %) sont décédés dans l’année. Parmi eux 88 % avaient un taux de biomarqueur > 15,3 %. L’analyse univariée selon le modèle proportionnel de Cox a montré qu’une valeur > 15,3, la présence d’une insuffisance cardiaque, d’une insuffisance rénale, d’un abcès cardiaque, une régurgitation valvulaire significative et la présence d’une déhiscence valvulaire étaient associées à une surmortalité. L’analyse multivariée selon le modèle de Cox a indiqué que l’insuffisance rénale ( hazard ratio [HR] 3,21, IC 95 % 1,35–7,59 ; p = 0,008), l’insuffisance cardiaque (HR 2,77, IC 95 % 1,1–6,97 ; p = 0,03) et le biomarqueur de distribution érythrocytaire > 15,3 % (HR 3,07 ; IC 95 % 1,06–8,86 ; p = 0,03).


Conclusion


Nos résultats suggèrent qu’il existe une surmortalité chez les patients ayant une endocardite infectieuse. Ce biomarqueur paraît intéressant pour prédire la survie à un an chez les patients hospitalisés pour endocardite infectieuse confirmée.


Background


Infective endocarditis (IE) is an endovascular infection of the heart that usually affects valvular structures and, with increasing frequency, implants within the heart, such as prosthetic valves or pacemaker electrodes. There have been significant improvements in the treatment of most cardiovascular diseases in recent decades; however, prognosis still remains poor in IE. The current in-hospital mortality rate is around 20%, while long-term mortality can be as high as 40% .


Identifying patients at increased risk of adverse outcomes is challenging due to the broad spectrum of the cardiac pathology and infecting organisms. Right-sided native-valve IE usually has a benign course, with even a short-term antibiotic regimen being sufficient, while prosthetic IE or device-related IE can be more severe, requiring different management strategies . The causative organism can differ depending on the history of surgery, drug abuse, healthcare contact, invasive procedures, immunosuppression and even geographical differences . Although some clinical predictors have been identified to estimate poor outcome, the course of the disease can still differ in each individual . A biomarker that predicts outcome would be helpful in clinical practice to identify high-risk patients that need more aggressive treatment.


Red cell distribution width (RDW) – a measure of red blood cell size heterogeneity – has been used traditionally in the differential diagnosis of anaemia, as it can increase in cases of haemolysis, blood transfusion or ineffective erythropoiesis. Recent studies have shown that elevated RDW is associated with adverse outcome in various clinical settings, including thromboembolic events, cardiovascular diseases and respiratory diseases . The prognostic implications of RDW in IE have not been studied. In the present study, we aimed to investigate the relationship between RDW and 1-year survival in patients with IE.




Methods


Study patients


Between January 2008 and January 2011, patients diagnosed with definite IE (according to the modified Duke criteria) at Cumhuriyet University Faculty of Medicine and Yuksek Ihtisas Education and Research Hospitals were enrolled in this study . Patients with chronic liver disease and those with a history of haematological disease other than anaemia (such as leukaemia, myeloproliferative diseases or bone marrow infiltration) were excluded. The prospective data of 100 consecutive IE patients were analysed retrospectively. In addition to RDW levels on admission, clinical, echocardiographic and laboratory findings were recorded for each subject. Predisposing heart diseases, including prosthetic valve, pre-existing valvular disease (rheumatic heart disease and degenerative valves), congenital heart disease, implantable cardiac device, nosocomial infection, previous history of IE, malignancy and immunosuppression were assessed.


Complications during hospitalization, such as heart failure, renal failure, abscess formation, embolic events (excluding cerebral), cerebrovascular events and surgical treatment for IE, were recorded. Duration of hospital stay and in-hospital mortality were noted. Cerebrovascular events were defined in case of the following presentations: intracranial haemorrhage; ischaemic stroke; or transient ischaemic attacks. Renal failure was defined by serum creatinine concentration > 2 mg/dL during hospital stay. Anaemia was defined according to the World Health Organization criteria (haemoglobin < 13 g/dL in men and < 12 g/dL in women). The study endpoint was the incidence of all-cause death within 1 year after index hospitalization. Clinical event data were collected during the follow-up period for all patients by reviewing medical files and by telephone contact. The study was performed in accordance with the Declaration of Helsinki for human research and was approved by the local ethics committee.


Laboratory


Blood samples were obtained after admission, following overnight fasting. Baseline RDW, haemoglobin, haematocrit, platelet count and white blood cell count values were measured using an automated haematology analyser. C-reactive protein, glucose and creatinine concentrations were measured accordingly. At least three sets of blood samples for cultures were obtained from each patient immediately after hospital admission. Any other available fluid, tissue (valves, vegetations or intracardiac abscesses removed at surgery) or foreign body samples (pacemaker leads, catheters) were used to isolate microorganisms.


Echocardiography


All patients underwent two-dimensional transthoracic echocardiography within 24 hours of admission. Echocardiographic examinations were performed with the Vivid 7 system (GE Healthcare, Wauwatosa, WI, USA) in two participating centres. Transoesophageal echocardiography was performed when image quality with transthoracic echocardiography was insufficient for an accurate diagnosis or in cases of high clinical suspicion of IE, prosthetic valve involvement and suspicion of complications. Vegetation, abscess formation and valvular destruction, such as perforation of leaflet and chordal rupture, were evaluated. Vegetation size was measured by using different echocardiographic windows; the maximal length was obtained. Existence of rocking motion of the prosthetic valve with an excursion of > 15° in at least one direction gave the diagnosis of dehiscence. Left ventricular ejection fraction was calculated by the modified Simpson’s method. Severe valvular regurgitation was identified according to guideline recommendations . Pulmonary artery systolic pressure was estimated by continuous wave Doppler imaging of the tricuspid regurgitation using the Bernoulli equation .


Statistics


Continuous variables were expressed as mean ± standard deviation or median with interquartile range; categorical variables were expressed as number and percentage. A chi-square test or Fisher’s exact test was performed to compare categorical variables. The normality of distributions of variables was assessed using the Kolmogorov-Smirnov test. Student’s t -test was used for normally distributed continuous variables; the Mann-Whitney U test was used when the distribution was skewed. The discrimination of RDW for 1-year survival was evaluated using the area under the receiver operating characteristic (ROC) curve. The optimal cut-off point for ROC curves was determined for maximizing the sensitivity and specificity of the RDW values. Patients with IE were categorized into two groups on the basis of the cut-off value. Kaplan-Meier cumulative survival curves were used to display survival in two patient subgroups and log-rank values were calculated to assess the statistical significance. Univariate Cox proportional-hazards analyses were used to evaluate the relationship between variables and overall mortality. Variables that had a P value < 0.1 in the univariate analysis were used in a multivariable Cox proportional-hazards model to determine the independent prognostic factors of mortality. The results of the regression analysis are presented as hazard ratios and 95% confidence intervals. All statistical analyses were performed using SPSS software version 17.0 (SPSS Inc., Chicago, IL, USA). A P value of 0.05 was considered statistically significant.




Results


One hundred patients, who met the inclusion criteria, with men comprising 61% of the cohort, were enrolled in our study. The mean age was 47.8 ± 16.7 years. The mean duration of hospital stay was 34.95 ± 19.4 days. Staphylococcus species were the most common microorganisms. Prosthetic valves were the prominent predisposing factor in the study cohort. There were 45 cases of prosthetic valve IE, 36 cases of native-valve IE, 10 cases of congenital heart disease-related IE and nine cases of device-related IE. Twenty-six patients died during the index hospitalization. Forty-one patients (41%) died within 1 year. Table 1 shows the differences between survivors and non-survivors regarding demographic, clinical and echocardiographic properties. Renal failure, heart failure, cardiac abscess and severe valvular regurgitation were significantly more common among non-survivors, whereas having surgery due to IE was associated with lower mortality.



Table 1

Baseline characteristics and outcomes of the study patients.













































































































































































































































































































All patients
( n = 100)
Mortality P
Alive
( n = 59)
Died
( n = 41)
Demographics and predisposing conditions
Female sex 39 (39) 26 (44) 13 (32) 0.21
Age (years) 47.83 ± 16.76 45.69 ± 16.07 50.09 ± 17.46 0.12
Prosthetic valve 45 (45) 24 (41) 21 (51) 0.29
Pre-existing valvular disease 27 (27) 12 (20) 15 (37) 0.07
Congenital cardiac disease 10 (10) 8 (14) 2 (5) 0.19
Cardiac device 9 (9) 4 (7) 5 (12) 0.48
Nosocomial infection 12 (12) 5 (9) 7 (17) 0.22
Previous IE 10 (10) 5 (9) 5 (12) 0.73
Haemodialysis 3 (3) 2 (3) 1 (2) 1
Other a 2 (2) 2 (3) 0 (0) 0.51
Affected valve
Aortic 39 (39) 21 (36) 18 (44) 0.4
Mitral 38 (38) 25 (42) 13 (32) 0.28
Tricuspid 9 (9) 5 (9) 4 (10) 1
Multiple 9 (9) 5 (9) 4 (10) 1
Echocardiography
Cardiac abscess 7 (7) 1 (2) 6 (15) 0.01
Severe valvular regurgitation 30 (30) 12 (20) 18 (44) 0.01
Vegetation ≥ 10 mm 61 (61) 34 (58) 27 (66) 0.40
Valvular destruction b 7 (7) 4 (7) 3 (7) 1
Dehiscence 7 (7) 2 (3) 5 (12) 0.11
Pulmonary artery pressure (mmHg) 42 (35–50) 42 (35–48) 44 (37.5–56) 0.22
Left ventricular ejection fraction (%) 58 (50–60) 60 (55–60) 55 (45–60) 0.13
Laboratory variables on admission
Red cell distribution width (%) 16.35 (14.4–18.65) 15.3 (14.2–17.9) 17.1 (15.75–19.1) 0.01
Haemoglobin (g/dL) 10.87 ± 2.21 11.18 ± 2.13 10.43 ± 2.27 0.09
C-reactive protein (mg/dL) 21.2 (7.15–76.95) 23.1 (7.3–69.6) 18.3 (6.04–84.3) 0.96
Creatinine (mg/dL) 0.92 (0.73–1.4) 0.87 (0.7–1.1) 1.3 (0.8–1.74) 0.004
Glucose (mg/dL) 98 (89–119.7) 98 (89.5–112.5) 101 (88–120) 0.85
White blood cell count (×10 3 /μL) 10 (7.5–14.45) 9.9 (7.4–13) 10.1 (7.65–15.7) 0.32
Platelet count (×10 3 /μL) 260.5 (172–329.2) 273 (207–379) 251 (147.5–307) 0.08
Microorganism
Staphylococcus aureus 19 (19) 10 (17) 9 (22) 0.53
Coagulase-negative Staphylococcus 15 (15) 9 (15) 6 (15) 0.93
Streptococcus species 15 (15) 12 (20) 3 (7) 0.07
Brucella species 9 (9) 7 (12) 2 (5) 0.11
Enterococcus species 7 (7) 2 (3) 5 (12) 0.3
Gram-negative Bacilli 1 (1) 1 (2) 0 (0) 1
Fungi 1 (1) 0 (0) 1 (2) 0.41
Culture negative 33 (33) 18 (31) 15 (37) 0.52
In-hospital outcome
Anaemia 68 (68) 39 (66) 29 (71) 0.65
Heart failure 20 (20) 3 (5) 17 (41) 0.0001
Renal failure 42 (42) 15 (25) 27 (66) 0.0001
Cerebrovascular events 15 (15) 8 (14) 7 (17) 0.62
Embolic events (excluding cerebral) 10 (10) 9 (15) 1 (2) 0.04
Surgery for IE 18 (18) 16 (27) 2 (5) 0.004
Spleen abscess 3 (3) 3 (5) 0 (0) 0.26
Brain abscess 3 (3) 3 (5) 0 (0) 0.26

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Jul 12, 2017 | Posted by in CARDIOLOGY | Comments Off on Red cell distribution width predicts mortality in infective endocarditis

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