Predictors and Outcomes of Pneumonia in Patients With Spontaneous Intracerebral Hemorrhage

Alsumrain, Mohammad; Melillo, Nicholas; DeBari, Vincent A.; Kirmani, Jawad F.; Moussavi, Mohammad; Doraiswamy, Vikram; Katapally, Ram; Korya, Daniel; Adelman, Marc; Miller, Richard A.

doi:10.1177/0885066612437512

Cited by 52 publications

(34 citation statements)

References 36 publications

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“…Ventilator-associated pneumonia is its own entity and assumed to be caused by mechanical ventilation itself and other risk factors that substantially differ from those identified for the development of poststroke pneumonia. 34 Second, our data do not allow for firm conclusions concerning the temporal sequence of events. Several studies indicate that pneumonia precedes mechanical ventilation, 35 thus making pneumonia a possible "risk factor" for mechanical ventilation and not necessarily vice versa.…”

Section: Discussionmentioning

confidence: 77%

Development of a Clinical Score (A ² DS ² ) to Predict Pneumonia in Acute Ischemic Stroke

Höffmann

Malzahn

Harms

et al. 2012

Stroke

190

163

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; for the Berlin Stroke Register and the Stroke Register of Northwest Germany Background and Purpose-Poststroke pneumonia is a potentially preventable complication after stroke associated with poor outcome. We developed and externally validated a prognostic score for predicting risk of pneumonia after ischemic stroke. Methods-The prognostic score was developed based on clinical data routinely collected after admission from the Berlin Stroke Register, Germany. The association of demographics, comorbidities, and clinical characteristics with poststroke pneumonia was investigated using multivariable logistic regression analyses. Independent predictors of poststroke pneumonia were translated into a point scoring system based on the corresponding regression coefficients. The predictive properties of the developed prognostic score were externally validated using an independent data set from the Stroke Register Northwest-Germany. Results-Between 2007 and 2009, 15 335 patients with ischemic stroke were registered within the Berlin Stroke Register.The observed rate of pneumonia in hospital was 7.2%. A 10-point score was derived for prediction of poststroke pneumonia (Age Ն75 yearsϭ1, Atrial fibrillationϭ1, Dysphagiaϭ2, male Sexϭ1, stroke Severity, National Institutes of Health Stroke Scale 0 -4ϭ0, 5-15ϭ3, Ն16ϭ5; A 2 DS 2 ). The proportion of pneumonia varied between 0.3% in patients with a score of 0 point to 39.4% in patients with a score of 10 points. The score demonstrated excellent discrimination (C-statistic 0.84; 95% CI, 0.83-0.85) and calibration (McFadden R 2 ϭ0.21). Prediction, discrimination, and calibration properties were reproduced in the validation cohort consisting of 45 085 patients with ischemic stroke. Conclusions-The

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Section: Discussionmentioning

confidence: 77%

Development of a Clinical Score (A ² DS ² ) to Predict Pneumonia in Acute Ischemic Stroke

Höffmann

Malzahn

Harms

et al. 2012

Stroke

190

163

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“…We chose not to include variables related to in-hospital management and those not routinely collected, such as mechanical ventilation, 19,26 prophylactic use of acid-suppressive medications, 27,28 and swallowing test, 8,29 despite the fact that these factors might influence the development of SAP after ICH. This model therefore predicts the expected risk of SAP after ICH at presentation.…”

Section: Discussionmentioning

confidence: 99%

Risk Score to Predict Hospital-Acquired Pneumonia After Spontaneous Intracerebral Hemorrhage

Ji¹,

Shen²,

Pan³

et al. 2014

Stroke

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S pontaneous intracerebral hemorrhage (ICH) accounts for 10% to 15% of all strokes and is one of the leading causes of stroke-related mortality and morbidity worldwide. Patients with ICH are generally at risk of developing stroke-associated pneumonia (SAP) during acute hospitalization. Evidence has shown that SAP not only increases the length of hospital stay (LOS) and medical cost 1,2 but also is an important risk factor of mortality and morbidity after acute stroke. 3,4 Several risk factors for SAP have been identified, such as older age, 4-12 male sex, 5,6,10,11,13 current smoking, 12 diabetes mellitus, 6 hypertension, 14 atrial fibrillation, 7,10,12 congestive heart failure, 7,12,13,15 chronic obstructive pulmonary disease, 8,[12][13][14] preexisting dependency, 8,12,13,16 stroke severity, 5,6,8,12,17,18 dysphagia, [8][9][10][11][12]14,[18][19][20] and blood glucose. 12 Meanwhile, based on these risk factors, a few risk models have been developed for SAP after acute ischemic stroke. [8][9][10][11][12] Currently, no valid scoring system is available for predicting SAP after ICH in routine clinical practice or clinical trial. We hypothesized that there might be some common grounds for the development of pneumonia after acute ischemic stroke and ICH, and those predictors for SAP after acute ischemic stroke might also be useful for predicting SAP after ICH. For clinical practice, an effective risk-stratification and prognostic model for SAP after ICH would be helpful to identify vulnerable patients, allocate relevant medical resources, and implement tailored preventive strategies. In addition, for clinical trial, it could be used in nonrandomized studies to control for case-mix variation and in controlled studies as a selection criterion.Background and Purpose-We aimed to develop a risk score (intracerebral hemorrhage-associated pneumonia score, ICH-APS) for predicting hospital-acquired stroke-associated pneumonia (SAP) after ICH. Methods-The ICH-APS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Variables routinely collected at presentation were used for predicting SAP after ICH. For testing the added value of hematoma volume measure, we separately developed 2 models with (ICH-APS-B) and without (ICH-APS-A) hematoma volume included. Multivariable logistic regression was performed to identify independent predictors. The area under the receiver operating characteristic curve (AUROC), Hosmer-Lemeshow goodness-of-fit test, and integrated discrimination index were used to assess model discrimination, calibration, and reclassification, respectively. Results-The SAP was 16.4% and 17.7% in the overall derivation (n=2998) and validation (n=2000) cohorts, respectively.A 23-point ICH-APS-A was developed based on a set of predictors and showed good discrimination in the overall derivation (AUROC, 0.75; 95% confidence interval, 0. Ji et al Risk Score to Predict SAP After ICH 2621In the study, we aimed to ...

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“…[6][7][8] Other cases of stroke that precede IE may reflect the presence of shared risk factors for both stroke and IE, such as cardiac valve surgery, or poststroke risk factors that may predispose to IE, such as poststroke immunodepression or use of central venous catheters after stroke. [20][21][22][23][24][25] The nature of our data prevents us from determining the mechanistic basis for these findings, but future analyses should aim to delineate the specific pathophysiologic processes underlying the complex relationship between IE and stroke.…”

Section: Figure Temporal Relationship Between Infective Endocarditis mentioning

confidence: 98%

Temporal relationship between infective endocarditis and stroke

et al. 2015

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Objective: Stroke frequently complicates infective endocarditis (IE). However, the temporal relationship between these diseases is uncertain.Methods: We performed a retrospective study of adult patients hospitalized for IE between July 1, 2007, and June 30, 2011, at nonfederal acute care hospitals in California. Previously validated diagnosis codes were used to identify the primary composite outcome of ischemic or hemorrhagic stroke during discrete 1-month periods from 6 months before to 6 months after the diagnosis of IE. The odds of stroke in these periods were compared with the odds of stroke in the corresponding 1-month period 2 years earlier, which was considered the baseline risk of stroke.Results: Among 17,926 patients with IE, 2,275 strokes occurred within the 12-month period surrounding the diagnosis of IE. The risk of stroke was highest in the month after diagnosis of IE (1,640 vs 17 strokes in the corresponding month 2 years prior). This equaled an absolute risk increase of 9.1% (95% confidence interval 8.6%-9.5%) and an odds ratio of 96.5 (95% confidence interval 60.1-166.0). Stroke risk was significantly increased beginning 4 months before the diagnosis of IE and lasting 5 months afterward. Similar temporal patterns were seen when ischemic and hemorrhagic strokes were considered separately. Conclusions:The association between IE and stroke persists for longer than previously reported.Most diagnoses of stroke and IE are made close together in time, but a period of heightened stroke risk becomes apparent several months before the diagnosis of IE and lasts for several months afterward. Infective endocarditis (IE) occurs in 1.7 to 6.2 per 100,000 people per year in the United States and Europe.1 Stroke often complicates IE, affecting approximately 16% to 25% of patients with IE.2,3 Cerebral embolism heralding or following a diagnosis of IE substantially increases morbidity and mortality.3-5 However, knowledge is limited regarding the time period during which patients with IE face a heightened stroke risk, with reports ranging from as early as 40 days before IE is recognized to as late as 5 weeks after the start of antibiotic treatment.3,4,6-8 Recent data suggest that IE may increase stroke risk for even longer periods of time, as one European cohort study reported that patients had a moderately increased risk of embolic events up to 180 days after community-acquired bacteremia. 9 We hypothesized that the risk of stroke in the setting of IE persists for longer than current data suggest. Therefore, we sought to better delineate the time period during which patients diagnosed with IE face an increased stroke risk.METHODS Study design. We performed a retrospective study of the temporal relationship between IE and stroke diagnoses using administrative claims data from California. The California Office of Statewide Health Planning and Development collects data about all emergency department (ED) visits and hospital stays at nonfederal acute care hospitals in California. After quality checking, these...

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Predictors and Outcomes of Pneumonia in Patients With Spontaneous Intracerebral Hemorrhage

Abstract: Mechanical ventilation, tube feeding, dysphagia, and tracheostomy are exposures associated with increased risk of the development of pneumonia in patients with sICH. Pneumonia is associated with an increase in morbidity, length of stay, and mortality among patients with sICH.

Cited by 52 publications

References 36 publications

Development of a Clinical Score (A ² DS ² ) to Predict Pneumonia in Acute Ischemic Stroke

Development of a Clinical Score (A ² DS ² ) to Predict Pneumonia in Acute Ischemic Stroke

Risk Score to Predict Hospital-Acquired Pneumonia After Spontaneous Intracerebral Hemorrhage

Temporal relationship between infective endocarditis and stroke

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Predictors and Outcomes of Pneumonia in Patients With Spontaneous Intracerebral Hemorrhage

Abstract: Mechanical ventilation, tube feeding, dysphagia, and tracheostomy are exposures associated with increased risk of the development of pneumonia in patients with sICH. Pneumonia is associated with an increase in morbidity, length of stay, and mortality among patients with sICH.

Cited by 52 publications

References 36 publications

Development of a Clinical Score (A 2 DS 2 ) to Predict Pneumonia in Acute Ischemic Stroke

Development of a Clinical Score (A 2 DS 2 ) to Predict Pneumonia in Acute Ischemic Stroke

Risk Score to Predict Hospital-Acquired Pneumonia After Spontaneous Intracerebral Hemorrhage

Temporal relationship between infective endocarditis and stroke

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Product

Resources

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Development of a Clinical Score (A ² DS ² ) to Predict Pneumonia in Acute Ischemic Stroke

Development of a Clinical Score (A ² DS ² ) to Predict Pneumonia in Acute Ischemic Stroke