Literature DB >> 31814729

Scoring Of Post Stroke Pneumonia In Uttaradit Hospital.

Nichakarn Leangpanich1, Yanin Chuphanitsakun1, Kanyaros Pakaranodom1, Kunlachat Kerdjarern1, Watcharapol Poonual2.   

Abstract

BACKGROUND: Stroke is a disease which occurs when the blood supply to the brain is interrupted, depriving brain tissue of oxygen, resulting in cell death. The symptoms of stroke include: numbness, paraplegia, dysarthria, ataxia, etc. The most common complication is infection. The highest death rates among hospitalized stroke patients are from pneumonia.
OBJECTIVE: To develop a score for predicting post-stroke pneumonia infection and identify risk factors for patients with post-stroke pneumonia. STUDY
DESIGN: Retrospective case-control.
SETTING: Uttaradit hospital (the tertiary hospital), Thailand.
METHOD: A retrospective data study was conducted at Uttaradit hospital, Thailand from January 2014 to October 2018 in which all of the subjects were diagnosed with either stroke with pneumonia or without pneumonia by a physician. The selected 324 stroke patients were divided into two groups: 108 patients were stroke with pneumonia and 216 patients were stroke without pneumonia. This study involved data collection and analysis of study characteristics to develop a predictive score for post-stroke pneumonia.
RESULTS: This study identified risk factors and developed a score for predicting post-stroke pneumonia infection by using significant covariates (duration of admission; 1-10 days=0 points, 11-20 days=1 point, more than 20 days=2.5 points, Cardiovascular disease=1.5 points, Nasogastric tube=2 points, Urinary tract infection=1 point). This score was interpreted to three groups; low risk (<2 points), moderate risk (2.5-4 points), and high risk (>4 points). Sensitivity was 80.56% and specificity was 93.52%.
CONCLUSION: A simple prediction tool was developed that uses only four clinical variables to predict risk of post-stroke pneumonia with high sensitivity and specificity.
© 2019 Leangpanich et al.

Entities:  

Keywords:  pneumonia; risk factor; risk score; stroke

Year:  2019        PMID: 31814729      PMCID: PMC6863128          DOI: 10.2147/JMDH.S218654

Source DB:  PubMed          Journal:  J Multidiscip Healthc        ISSN: 1178-2390


Background

Stroke occurs when a blood vessel is either blocked by a clot or ruptured, causing damage to the brain tissue.1 That causes a variety of symptoms such as weakness or numbness of the face, arm, or leg, difficulty speaking or understanding speech, difficulty walking, and difficulty seeing with one or both eyes.2 Some stroke patients develop complications while hospitalized, which are mostly brain edema, pneumonia, urinary tract infection, seizures, clinical depression, bedsores, limb contractures, shoulder pain, and deep venous thrombosis (DVT).3 According to the literature review, the most common complications of stroke are post-stroke infection (30%). Rate of pneumonia and urinary tract infection after stroke were 10%.4 Pneumonia has a mortality rate of 35% of all post-stroke death.5,6 Symptoms of pneumonia may include fever, cough, and dyspnea.7 Meanwhile fever is usually hidden by using aspirin in a stroke patient,8 also cough is barely found in stroke patients as well.9 Dyspnea may be a result of underlying disease such as heart failure or COPD.10 The initially normal chest x-rays are more likely in pneumonia.11 Therefore, we developed a score for predicting post-stroke pneumonia infection with proper surveillance and management.

Objectives

To develop a score for predicting post-stroke pneumonia infection; To identify risk factors of patients with post-stroke pneumonia while admitted to Uttaradit hospital.

Methods

Study design: Retrospective case controlled. Population: stroke patients admitted at Uttaradit hospital between January 2014 and August 2018. Target population: 108 Stroke patients with pneumonia. (Pneumonia was recorded by the treating physician based on clinical symptoms of lung infection in combination with clinical signs such as rales on chest auscultation and chest X ray findings suggestive for pneumonia supported by laboratory tests such as complete blood count.) Control Population: 216 stroke patients without pneumonia. Exclusion Criteria: Community-acquired pneumonia patients. The study was designed as a case-control analysis of data from an academic affiliated community hospital that retrospectively collects data from stroke patients admitted at Uttaradit hospital between January 2014 and August 2018. The study was divided into two stroke patient groups: with or without pneumonia (108 and 216, respectively). The exclusion criteria was Community-acquired pneumonia.

Statistical Methods

From 6,088 stroke patients who were hospitalized in Uttaradit hospital between 2014–2018, stroke with pneumonia was diagnosed in 409, and 5,679 were stroke patients without pneumonia. A retrospective case-control study accumulated with a related literature review proved that atrial fibrillation12 is one of the predisposing risk factors among pneumonia statistically. So we used two independent proportions of the presence and absence of pneumonia in stroke patients by using power 90%, alpha=0.05, p1=0.249, p2=0.513, and the index to reference proportion is 1:2 which sampled 324 patients to 10 index cases, and 216 reference cases.

Variable Data

Independent variable: age group, sex, length of stay, lesion, NIHSS SCORE, underlying disease, medical treatment such as Endotracheal intubation, Nasogastric tube, Percutaneous gastrostomy, and Urinary catheter, other complications, eg, epileptic seizure, Sepsis, Urinary tract infection, Heart failure, and arrhythmia. Dependent variable: pneumonia in stroke patients.

Descriptive Statistics

Categorical data: count data and percentage were analyzed using the chi-squared test and Fisher’s exact test. Numerical data: Median, Interquartile Range was analyzed using student t-test or Wilcoxon rank-sum test.

Analytic Statistics

A univariable logistic regression model was used to analyze each explanatory variable, interpreted as odds ratio, 95% CI, and p-value. A multivariable logistic regression model was used to analyze all explanatory variables interpreted as odds ratio, 95% CI, and p-value.

Results

General Characteristics

General characteristics analysis from 324 stroke patients of whom 108 had pneumonia and 206 didn’t have pneumonia were not different between the groups in sex, age group, lesion of right hemisphere, both hemisphere, brain stem or cerebellum, and ventricle or sinus, Diabetes, atrial fibrillation, cardiovascular disease, Hyperlipidemia, and COPD. The stroke without pneumonia group had more lesions of the left hemisphere than the pneumonia group statistically. The length of stay, lesion at Basal ganglion or thalamus, and Hypertension were significantly higher in those stroke patients who had pneumonia (Table 1).
Table 1

General Characteristics Of Stroke Patients With Pneumonia Versus Without Pneumonia

General CharacteristicsStroke Patients With PneumoniaStroke Patients Without Pneumoniap-value
n%n%
Age group
 Less than 40 years32.8104.60.637
 40–80 years8780.617681.5
 More than 80 years1816.63013.9
 Mean (SD)67.2(13.1)65.3(14.3)
Sex
 Female5248.28941.20.235
 Male5651.812758.8
Length of stay, median (interquartile range)24(27)3(4)<0.001
Lesion
 Left hemisphere2826.08037.00.046
 Right hemisphere2624.06128.20.425
 Both hemisphere54.6146.50.504
 Brainstem or Cerebellum87.42712.50.164
 Basal ganglion and thalamus3936.13315.3<0.001
 Ventricle and sinus21.910.50.259
Hypertension
 No2624.0037.00.019
 Yes8276.013663.0
Diabetes mellitus
 No8982.417781.90.918
 Yes1917.63918.1
Atrial fibrillation
 No9688.919690.40.598
 Yes1211.1209.3
Cardiovascular disease
 No10294.421298.10.069
 Yes65.641.9
Hyperlipidemia
 No7165.711854.60.056
 Yes3734.39845.4
COPD
 No10698.22161000.110
 Yes21.800
General Characteristics Of Stroke Patients With Pneumonia Versus Without Pneumonia

Medical Treatment

In sites with pneumonia, endotracheal intubation, Nasogastric tube, and Urinary catheter were significantly higher than those sites without pneumonia (Table 2).
Table 2

Medical Treatment Of Stroke Patients With Pneumonia Versus Without Pneumonia

Medical TreatmentStroke Patients With PneumoniaStroke Patients Without Pneumoniap-value
n%n%
Endotracheal intubation
 No1816.717078.7<0.001
 Yes9083.34621.3
Nasogastric tube
 No87.417179.2<0.001
 Yes10092.64520.8
Urinary catheter
 No1211.117681.5<0.001
 Yes9688.94018.5
Medical Treatment Of Stroke Patients With Pneumonia Versus Without Pneumonia

Other Complications

Those stroke patients who developed pneumonia had significantly higher rates of epileptic seizure, Sepsis, Urinary tract infection, and Heart failure (Table 3).
Table 3

Other Complications Of Stroke Patients With Pneumonia Versus Without Pneumonia

Other ComplicationsStroke Patients With PneumoniaStroke Patients Without Pneumoniap-value
n%n%
Seizure
 No8982.420996.8<0.001
 Yes1918.673.2
Sepsis
 No8275.921298.2<0.001
 Yes2624.141.8
Urinary tract infection
 No8679.621398.6<0.001
 Yes2220.431.4
Heart failure
 No10092.621398.60.008
 Yes87.431.4
Arrhythmia
 No9991.720795.80.130
 Yes98.394.2
Other Complications Of Stroke Patients With Pneumonia Versus Without Pneumonia

Odds Ratio Of Pneumonia In Stroke Patients

The 40–80 years age groups of stroke patients had a 1.6-fold increaded odds of developing pneumonia. Likewise, a stay of 11–20 days and more than 20 days increased the odds 11.5- and 141.8-fold, respectively. The complications of cardiovascular disease and urinary tract infection increased the odds 3.1- and 18.2-fold, respectively. Meanwhile, stroke patients had a nasogastric tube had an increased risk of developing pneumonia of 47.5-fold (Table 4).
Table 4

Odd Ratio Of Developing Pneumonia In Stroke Patients

ORUnivariate AnalysisMultivariate Analysis
95% CIp-value95% CIp-value
Age group
 <40 years1.00
 40–80 years1.60.410–9.5360.4531.355–251.9940.029
 >80 years20.430–12.6640.3320.821–244.2130.068
Sex
 Female0.80.462–1.2340.2350.361–2.5180.922
 Male1.00
Length of stay
 0–10 days1.00
 11–20 days11.54.930–26.637<0.0011.670–17.0740.005
 >20 days141.845.027–567.248<0.00113.723–504.628<0.001
Lesion
 Left hemisphere0.20.003–3.5480.1170.536–253.6470.118
 Right hemisphere0.20.004–4.3430.1760.410–205.3280.162
 Both hemispheres0.20.003–4.5140.1630.034–22.2030.935
 Brainstem or Cerebellum0.10.002–3.3920.0980.247–151.9840.269
 Basal ganglion and thalamus0.60.010–11.9070.6700.771–428.3000.072
 Ventricle and sinus1.00
Hypertension
 No1.00
 Yes1.91.074–3.2590.0190.241–2.0070.503
Diabetes mellitus
 No1.00
 Yes1.00.498–1.8360.9180.353–4.3980.733
Atrial fibrillation
 No1.00
 Yes1.20.523–2.7580.5980.075–1.8430.225
Cardiovascular disease
 No1.00
 Yes3.10.719–15.3020.0691.342–157.2050.028
Hyperlipidemia
 No1.00
 Yes0.60.376–1.0390.0560.392–2.8520.912
Endotracheal intubation
 No1.00
 Yes18.59.777–35.640<0.0010.117–4.5900.739
Nasogastric tube
 No1.00
 Yes47.520.842–119.571<0.0013.361–36.966<0.001
Urinary catheter
 No1.00
 Yes35.216.985–76.290<0.0010.379–16.4240.342
Seizure
 No1.00
 Yes6.42.443–18.482<0.0010.660–24.4840.131
Sepsis
 No1.00
 Yes16.85.539–67.661<0.0010.570–15.4760.197
Urinary tract infection
 No1.00
 Yes18.25.208–96.311<0.0011.496–79.5640.018
Heart failure
 No1.00
 Yes5.71.320–33.7410.0050.490–97.9050.152
Arrhythmia
 No1.00
 Yes2.10.709–6.1350.1230.213–9.3800.719
Odd Ratio Of Developing Pneumonia In Stroke Patients

Score For Predicting Post-Stroke Pneumonia Infection

After analysis by multivariable logistic regression, there were four variables to make a score for predicting post-stroke pneumonia infection, which is Length of stay that divided into three intervals (1–10 days=0, 11–20 days=1, and more than 20 days=2.5), 1.5 points for cardiovascular disease, 2 points for nasogastric tube, and 1.5 points for urinary tract infection. The score was divided into three groups, those with lower than 2 points were defined as a lower risk group, while the medium risk group was counted for 2.5–4 points, and more than 4 points for the high risk group (Table 5) with 80.56% sensitivity and 93.52% specificity. There was a positive predictive value of 86.14 and a negative predictive value of 90.58.
Table 5

Score For Predicting Post-Stroke Pneumonia Infection

ProbabilityCategoriesScoreCase (n=108)Control (n=216)LHR+95% CIp-value
n%n%
Low0-22018.520193.10.200.134–0.300<0.001
Moderate2.5-42018.5125.63.331.693–6.5620.005
High4.5–7.56863.031.345.3314.601–140.754<0.001
Mean±SD3.9±1.60.6±1.1<0.001
Score For Predicting Post-Stroke Pneumonia Infection

Discussion

Risk factors of post-stroke pneumonia patients were identified and predicting score was developed with high sensitivity and specificity by using four variables that are easy and convenient for screening and setting priority to proper surveillance in stroke patients who are likely to have pneumonia. Stroke patients in the age group 40–80 years, longer length of stay, complications of cardiovascular disease and urinary tract infection, or nasogastric tube use increase the risk of developing pneumonia. It is possible that patients with a longer length of stay will have a longer time exposed to pathogens in the hospital. Elderly people tend to be more at risk of developing pneumonia because their immune system is weaker. The association with procedures such as nasogastric tube is possibly related to severe illness leading to prolonged bed rest. This study is limited in that the data cannot collect the variables of NIHSS score, smoking and alcohol use history, since this is a retrospective case controlled study and these data were not completely found in medical records, despite another study providing this; these are associated risk factors to develop post-stroke pneumonia statistically.12 Therefore this predicting score would cover all risk factors and may decrease accuracy. Moreover, this score will still not be used in general practice so it could not be confirmed to assess in other populations.

Conclusion

The score for predicting post-stroke pneumonia infection can be assessed as a screening program, but this study did not yet use in practice. However, interpretation was limited by missing some important data that leads to potential risk factors to generate a score. We suggest that the next study should require the prospective case control study for improving the quality of the data collection.
  9 in total

Review 1.  How is pneumonia diagnosed in clinical stroke research? A systematic review and meta-analysis.

Authors:  Amit K Kishore; Andy Vail; Angel Chamorro; Javier Garau; Stephen J Hopkins; Mario Di Napoli; Lalit Kalra; Peter Langhorne; Joan Montaner; Christine Roffe; Anthony G Rudd; Pippa J Tyrrell; Diederik van de Beek; Mark Woodhead; Andreas Meisel; Craig J Smith
Journal:  Stroke       Date:  2015-04-09       Impact factor: 7.914

2.  Aspirin compared with acetaminophen in the treatment of fever and other symptoms of upper respiratory tract infection in adults: a multicenter, randomized, double-blind, double-dummy, placebo-controlled, parallel-group, single-dose, 6-hour dose-ranging study.

Authors:  Claus Bachert; Alexander G Chuchalin; Reinhard Eisebitt; Vasiliy Z Netayzhenko; Michael Voelker
Journal:  Clin Ther       Date:  2005-07       Impact factor: 3.393

3.  Diagnostic value of chest radiographs in bedridden patients suspected of having pneumonia.

Authors:  Yaacov Esayag; Irina Nikitin; Jacob Bar-Ziv; Ruth Cytter; Irith Hadas-Halpern; Todd Zalut; Amos M Yinnon
Journal:  Am J Med       Date:  2010-01       Impact factor: 4.965

4.  An updated definition of stroke for the 21st century: a statement for healthcare professionals from the American Heart Association/American Stroke Association.

Authors:  Ralph L Sacco; Scott E Kasner; Joseph P Broderick; Louis R Caplan; J J Buddy Connors; Antonio Culebras; Mitchell S V Elkind; Mary G George; Allen D Hamdan; Randall T Higashida; Brian L Hoh; L Scott Janis; Carlos S Kase; Dawn O Kleindorfer; Jin-Moo Lee; Michael E Moseley; Eric D Peterson; Tanya N Turan; Amy L Valderrama; Harry V Vinters
Journal:  Stroke       Date:  2013-05-07       Impact factor: 7.914

5.  Comparison of cough reflex test against instrumental assessment of aspiration.

Authors:  Anna Miles; Sara Moore; Mary McFarlane; Fiona Lee; Jacqueline Allen; Maggie-Lee Huckabee
Journal:  Physiol Behav       Date:  2013-05-12

6.  Formal dysphagia screening protocols prevent pneumonia.

Authors:  Judith A Hinchey; Timothy Shephard; Karen Furie; Don Smith; David Wang; Sarah Tonn
Journal:  Stroke       Date:  2005-08-18       Impact factor: 7.914

7.  Predictors of pneumonia in acute stroke patients admitted to a neurological intensive care unit.

Authors:  Uwe Walter; Rupert Knoblich; Volker Steinhagen; Martina Donat; Reiner Benecke; Antje Kloth
Journal:  J Neurol       Date:  2007-03-14       Impact factor: 4.849

Review 8.  Post-stroke infection: a systematic review and meta-analysis.

Authors:  Willeke F Westendorp; Paul J Nederkoorn; Jan-Dirk Vermeij; Marcel G Dijkgraaf; Diederik van de Beek
Journal:  BMC Neurol       Date:  2011-09-20       Impact factor: 2.474

9.  Post-stroke pneumonia at the stroke unit - a registry based analysis of contributing and protective factors.

Authors:  Karl Matz; Leonhard Seyfang; Alexandra Dachenhausen; Yvonne Teuschl; Jaakko Tuomilehto; Michael Brainin
Journal:  BMC Neurol       Date:  2016-07-18       Impact factor: 2.474

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Journal:  Cureus       Date:  2021-05-24

Review 2.  The Neutrophil to Lymphocyte Ratio in Poststroke Infection: A Systematic Review and Meta-Analysis.

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