Stroke Severity Versus Dysphagia Screen as Driver for Post-stroke Pneumonia

Abstract

Background and Purpose: Post-stroke pneumonia is a feared complication of stroke as it is associated with greater mortality and disability than in those without pneumonia. Patients are often kept “Nil By Mouth” (NBM) after stroke until after receiving a screen for dysphagia and declared safe to resume oral intake. We aimed to assess the proportional contribution of stroke severity and dysphagia screen to pneumonia by borrowing idea from coalition game theory on fair distribution of marginal profit (Shapley value).Method: Retrospective study of admissions to the stroke unit at Monash Medical Center in 2015. Seventy-five percent of data were partitioned into training set and the remainder (25%) into validation set. Variables associated with pneumonia (p < 0.1) were entered into Shapley value regression and conditional decision tree analysis.Results: In 2015, there were 797 admissions and 617 patients with ischemic and hemorrhagic stroke (age 69.9 ± 16.2, male = 55.0%, National Institute of Health Stroke Scale/NIHSS 8.1 ± 7.9). The frequency of pneumonia was 6.6% (41/617). In univariable analyses NIHSS, time to dysphagia screen, Charlson comorbidity index (CCI), and age were significantly associated with pneumonia but not weekend admission. Shapley value regression showed that the largest contributor to the model was stroke severity (72.8%) followed by CCI (16.2%), dysphagia screen (3.8%), and age (7.2%). Decision tree analysis yielded an NIHSS threshold of 14 for classifying people with (27% of 75 patients) and without pneumonia (2.5% of 308 patients). The area under the ROC curve for training data was 0.83 (95% CI 0.75–0.91) with no detectable difference between the training and test data (p = 0.4). Results were similar when dysphagia was exchanged for the variable dysphagia screen.Conclusion: Stroke severity status, and not dysphagia or dysphagia screening contributed to the decision tree model of post stroke pneumonia. We cannot exclude the chance that using dysphagia screen in this cohort had minimized the impact of dysphagia on development of pneumonia.

Network Mapping of Time to Antithrombotic Therapy Among Patients With Ischemic Stroke and Transient Ischemic Attack (TIA)

“…It is possible that the lower frequency of dysphagia screen (38%) might related to shorter time to antithrombotics in our patients with TIA. It is not clear that dysphagia screen is necessary in patients with TIA as these patients have resolution of neurological deficit and low probability of getting pneumonia ( 13 ). Furthermore, among patients discharged to an outpatient TIA pathway, the frequency of early aspirin was 92.2% ( 24 ).…”

“…We retrospectively assessed data relating to time to antithrombotic therapy in patients admitted to the stroke unit at Monash Health over a 12-month period in 2015. Data from this cohort on pneumonia has been published recently ( 13 ). In brief, we performed retrospective review of the medical records, extracting demographic data, age and gender, admission diagnoses, time to triage, imaging, and time to administration of antithrombotics, information on dysphagia screen and nil by mouth (NBM) status.…”

Percutaneous endoscopic gastrostomy feeding effects in patients with neurogenic dysphagia and recurrent pneumonia

“… 24 CCI has proven to be a significant risk factor for post-stroke or hospital-acquired pneumonia but not significant in this study due to the small number of subjects. 25 , 26 Dysphagia has been reported in patients with stroke (8.1–80%), with Parkinson’s disease (11–81%), and with traumatic brain injury (27–30%), as well as in older adult patients with community-acquired pneumonia (91.7%). 27 Therefore, the occurrence of dysphagia is more important than the precise neurological disease category, and early diagnosis of dysphagia has been shown to be helpful in preventing pneumonia.…”

Advanced age promotes colonic dysfunction and gut‐derived lung infection after stroke

“…A retrospective cohort design was used, where all information was obtained from scanned medical and electronic records available at the time of data collection. All patients primarily admitted for an acute stroke to Monash Medical Centre between 16 January 2015 and 10 February 2016 were enrolled and the data present here is a subset of a recent published clinical study (Phan et al, ). Multivariable logistic regression was used to determine the association between stroke and the presence of infection after adjusting for confounding factors.…”