A Novel FAND Nomogram to Predict the Risk of Hospital-Acquired Pneumonia after Acute Ischemic Stroke with Mechanical Thrombectomy

Background: The timely prediction in the risk of in Acute (AIS) Mechanical thrombectomy (MT) treatment is of high priority, given the rise in AIS mortality as a result. Although prior extensive research has been conducted in HAP preventive management and therapeutics, ischemic stroke patients are still at serious risk of contracting In-hospital pneumonia infections following certain medical procedures like Mechanical thrombectomy, a care standard for AIS patients. The predictive accuracy of patients with higher infection risk and adjusting therapeutic strategies accordingly will not only provide an enhanced preventive measure perspective but also significantly improve patient outcomes. Hence, our study was aimed at the validation and development of a novel predictive tool for risk stratification and individualized predictions of HAP occurrence in AIS patients after MT therapy. Method: A multicenter retrospective study was executed with 405 AIS patients after undergoing MT treatment and admitted to the three Chinese stroke units. The major measure of outcome was to estimate the risk of HAP after MT through the integration of the following four predictors FBG, Age, NHISS, and Diastolic blood pressure (FAND) into a nomogram. Assessed on the multivariate logistic model, a nomogram was constructed, using the area under the receiver-operating characteristic curve to evaluate the discriminative performance and the Hosmer– Lemeshow test for risk prediction model calibration. Results: Age(OR:1039; 95%Cl 1.017-1.062; p=0.001), NIHSS(National Institutes of Health Stroke Scale) score on admission(OR:1.066; 95%Cl: 1.030-1.103); p< 0.0001), diastolic blood pressure(OR 1.023; 95% Cl 1.006-1.040: p=0.008), Fasting


Background
Acute ischemic stroke (AIS) is still a major cause of short and long term mortality and morbidity [1,2]. Mechanical thrombectomy (MT) as a medical procedure involving blood clot removal from blood vessels in the cerebral arteries has proven to be highly effective in AIS treatment [3]. However, post-therapeutic complications after MT for AIS treatment are frequent as a considerable amount of AIS-related deaths are directly attributed to suffered complications [4]. Hospital-acquired pneumonia (HAP) is defined as a lower respiratory tract infection in the lungs occurring roughly 48-72 hours after clinical admission and is rapidly emerging as a crucial patient safety concern [5]. HAP is the most dominant, dangerous and morbid AIS complication with an estimated mortality rate of about 30% and an 8 to 12% attributable mortality rate in stroke survivors; thereby increasing hospital admission time by about six days [6][7][8][9]. HAP incidence is, however, relative to the study population, considering the demographic increase in the elderly and longer life expectancy a further rise in the future number of patients experiencing complications after AIS is predictable [10]. The vast majority of comprehensive research conducted on HAP has primarily centered around diagnosis rather than eliminating infection prognosis which is equally important [11]. Although preventive intervention measures carried out by clinics show an impressive decrease in hospitalization and mortality rates, clinical complications have not been eliminated.
HAP infections still see an expected increase in the next few years. Hence, early prediction of HAP onset after AIS is of great significance in providing a reasonable approach to clinical and therapeutic management [12][13][14].
Gaining insight into important factors in the prognosis of this condition might be challenging but highly necessary in accurately predicting patient outcomes, suggesting reasonable clinical and treatment management approach, and giving patients and their loved ones a better understanding of AIS [3,15]. Regardless of several scores constructed with the aim of predicting pneumonia emergence in stroke patients such as ISAN score, the PANTHERIS score, A2DS2(Age, Atrial fibrillation [AF], Dysphagia, Sex, Stroke Severity using National Institutes of Health Stroke Scale [NIHSS] score), Chumbler's score, Functional Bedside Aspiration Screen (FBAS score) and Stroke-Associated Pneumonia Score(acute ischemic strokeassociated pneumonia score, AIS-APS) there is however still a restriction on the acculturative effect in clinical care practice by its moderate predictive performance [16][17][18][19][20][21].
A nomogram is a reliable statistical tool that generates individualized approximation, faster prognostic prediction and continuous probability estimation of certain outcomes in a given patient, which can be developed from the mathematical visualization of complex formula through Cox proportional hazards analysis or multivariate logistic regression and by the incorporation of some continuous variables as a scoring system [22][23][24]. Nomograms are an integral constituent of modern clinical intervention and have been extensively integrated and validated in a wide array of medical applications [25][26][27][28][29]. However, to date, no nomogram models had been found to predict the risk of HAP after AIS with MT in Chinese patients.
The purpose of this study was the advancing and validating a nomogram comprising variables promptly accessible at the patient time of admission for the individualized prediction of HAP after MT which could directly aid individual treatment for AIS patients and provide relevant therapeutic preventive measures for patients with a higher risk of HAP. Patients admitted with comprehensive clinical, demographic and laboratory information were solely considered for this research. The study's exclusion criteria were no diagnosis of in-hospital Pneumonia, age unknown or age <18, absence of FBG, anterior circulation stroke and TOAST, no Coronary heart disease medical history, therapy onset interval over 24h, incomplete data, and an unknown National Institutes of Health Stroke Scale(NIHSS) on admission.

Study design, participants, and procedures
The following were recorded, sex, age, medical history such as diabetes mellitus, hypertension, coronary artery disease, hyperlipidemia, transient ischemic stroke, previous cerebral infarction, atrial fibrillation, previous cerebral hemorrhage e.t.c, diastolic blood pressure, NIHSS score on admission and FBG(fasting blood glucose).
The diagnosis of HAP after AIS treatment with MT through antibiotic treatment stimulation following admission was the clinical outcome.

Statistical analysis
The median value and interquartile range were set as continuous variables while using the Mann-Whitney U-test for univariate comparison to explore the cohort differences. The expression of categorical variables was alternatively expressed as the division of events numbers by the total amount except unknown or missing cases. Proportional differences were assessed by the X^2 test or Fisher's exact test. The Condition Index (<30 considered as non-significant) and Variation Inflation Factor Analysis (VIF, <2 considered as non-significant) of variable co-linearity combinations were used in the analysis of multivariate logistic. In the multivariate model, calculation of the odds ratio and its 95% interval of confidence were carried out for significantly associated primary endpoint variables.
Model performance was assessed by the method of discrimination (which is utilizing the start score to unrelated or divides pneumonia patients from patients without pneumonia) or the calibration method (In-hospital pneumonia prediction distance relative to actual patient outcome). The predictive accuracy of the nomogram model was evaluated through the calculation of the area below the receiver operating characteristic curve (AUC-ROC). Visual assessment was used in the test cohort through a calibration plot to determine the similarities between actual outcomes and outcomes predicted where, probability predicted was plotted against recorded pneumonia. Using a 45° line as a perfect calibration indication, the match between the value predicted and the actual patient's risk was assessed. Furthermore, internal validation of the model was obtained with the use of 2000 bootstrap samples. Every test was two-sided and if the value of probability was < 0.05 was considered statistically significant.

Results
Data from a total number of 405 AIS patients admitted to the three Chinese stroke units and treated with MT was complied. Patients were excluded from the study research for no In-hospital Pneumonia diagnosis (n = 9, 2.2%), unknown NIHSS score on admission(n = 1; 0.2%), lack of FBG( n = 45; 11.1%), no anterior circulation stroke (n = 6; 1.5%), lack of TOAST (n = 11; 2.7%), no history with Coronary artery disease (n = 24; 5.9%), and patients <18 years old were also excluded from this research. Hence, the total number of only 305 patients with a complete data record useful in the nomogram generation participated in the study (Median age 72 years; IQR 62-79.5 years). The proportion of patients with inhospital Pneumonia was calculated as 64.9% (198/305).
All clinical, laboratory and demographic data generated from the study population were stated in Table 1 The nomogram generation was based on assigning a graphic preliminary score to each of the 4 independent predictors with a point range within 1-100 and then summed up to generate a total score. Finally, they were converted into an individual risk of HAP after MT treatment of AIS is expressed in percentage between the range of 0-100%. Predictions suggested a higher total nomogram score associated with higher probability of HAP after MT stroke treatment and a lower score associated with lower probability of HAP diagnosis after MT AIS treatment.

Discussion
Ischemic stroke continues to be a leading cause of death and disability. An astonishing 87 percent of all stroke cases are ischemic resulting in as many as 6.7 million deaths worldwide [30]. Irrespective of the exponential advancement of MT devices and extensive recognition of the procedure as an advanced surgical alternative in AIS therapy due to comparative simplicity and efficacy, patients are still at risk of acquiring postoperative in-hospital pneumonia. In-hospital pneumonia continues to pose a major threat clinically considering the significant increase in mortality through patient immobilization, fever and, organ failure as a result of shock. Over 50,000 deaths ( i.e. 1.6 deaths in 10,000 people) were reportedly due to pneumonia in the year 2015 alone [11]. The early prediction of In-Hospital pneumonia onset in AIS patients following MT treatment ought to be a prominent perspective on accurate and systematic therapeutic and clinical management [31][32][33][34].
Previous nomogram models and prognostic scores have identified Age and NHISS score as independent unfavorable outcome predictors in stroke patients. However, the categorization or dichotomization of predictors has been a major limitation as risk grouping system into 2 or 4 in independent continuous variables has proven to be statistically inefficient and significantly decrease predictive accuracy. Another important downside of dichotomization is the lack of in-category information incorporation often resulting in information diminution. In our study, a >80% risk limit relative to a 0.90 positive predictive value was derived from the nomogram, providing a more accurate HAP risk after AIS treatment with MT prognosis. The lower risk limit of <20% was obtained from the nomogram with a more negative predictive value of 0.66, permitting an accurate probability exclusion in HAP diagnosis after AIS treatment with MT. Our study results suggested that the score created using variables at time of admission was feasible and reliable. For instance, the FAND nomogram allocated a >95% adverse consequence probability in an 80-year-old patient(76 points) stroke patient, with diastolic blood pressure score of 112(48 points), FBG at a level of 12.5 (50 points) and NIHSS score of 25(50 points) and a score total of 224. Alternatively, the nomogram assigns a <10% probability to a 30-year-old (22.5 points) with diastolic blood pressure of 60 (13 points), FBG at a level of 4 (15 points) and NIHSS score of 5 (9 points) with a total score of 59.5 through score conversion into individual probability continuum, the FAND nomogram provides a more precise reclassification of HAP diagnostic outcome.
During the course of our study, we found that elderly patients 80 years old and above were predominantly at a particularly higher risk of HAP infection proving age to be a contributive factor to long-term mortality and pneumonia diagnosis in AIS patients [36]. These predispositions may be conveniently elucidated through medical conditions such as obstructive airway diseases or certain cardiovascular diseases such as high blood pressure, elevated cholesterol and coronary artery disease and also comorbid compromises in the immune system of the elderly. We also noticed an association between a higher NHISS score and impaired neurological and consciousness levels [37]. Patients experiencing severe neurological damage levels and those with consciousness level alterations have notably had a higher predisposition to In-hospital pneumonia diagnosis with previous study references.

Some other important factors associated with In-hospital Pneumonia after MT treatment in AIS patients include; the use of antibiotics and glucocorticoid, Charlson
Comorbidity Index (CCI) score and admission in the Intensive care unit(ICU). The management and functional evaluation of these several factors associated with hospital-acquired pneumonia diagnosis especially in elderly patients are recommended and a prime comprehensive possible-complication assessment ought to be carried out earlier in patient admission [38][39][40][41][42].
The FAND nomogram provided a functional decrease in the influence of alternative treatment prognosis since it was developed in compliance with data assembled from AIS patients treated with MT. Therefore, the nomogram could hold an advantage over previous models and prognostic scores comprehending the use of obsolete categorization in patient risk grouping for various risk predictor identification in prior models. Hence, providing better circumstantial information in the facilitation of timely detection in patients with a higher probability of acquiring In-hospital pneumonia aiding the relay of prognostic information to patients and their loved ones. The FAND nomogram acts as a visual tool beneficial in leading clinicians and patients to a better AIS treatment approach through individual stroke characterization and prognostications custom made to fit possible adverse effects.
Some research limitations were the comparatively small sample quantity and the retrospective nature of our study. Secondly, an important HAP predictor known as dysphasia was not included in the cohort and could influence the predictive accuracy of the model given dysphagia, age and NHISS score on admission is related to In-hospital pneumonia infection. Neuro-imaging predictors were also absent in this study, the presence of which could have provided higher discriminative performance and enhanced the nomogram's predictive accuracy in MT treated stroke patients. Also, during categorical grouping and predictive model generation, limited information on patient's ethnic, racial or geographical information was provided differences that could influence the HAP predictions.

Availability of data and materials
The data sets in this study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate
The study protocols were approved by the Ethics Committees of Nanjing First Hospital in accord with the Helsinki declaration and internal protocol. All patients have given their written informed consent.

Consent for publication
Not applicable.

Competing interests
The authors have declared that they have no conflicts of interest regarding the content of this article.   Figure 1 The nomogram presented a more dependable prognostic tool for the individualized prediction The FAND nomogram model bias-corrected calibration plot illustrates good agreement betwe