Predictive Value of T-Eat-10 and Nuffe-tr for Aspiration Pneumonia in Nursing Home Residents: A Cross-sectional Study

Predictive Value of T-Eat-10 and Nuffe-tr for Aspiration Pneumonia in Nursing Home Residents: A Cross-sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Predictive Value of T-Eat-10 and Nuffe-tr for Aspiration Pneumonia in Nursing Home Residents: A Cross-sectional Study Melih Gaffar GOZUKARA, Sema Nur ERYILMAZ ALKAN, Ruveyda GURKAN YUKSEL, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9009756/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: Aging is associated with physiological changes that increase vulnerability to malnutrition and oropharyngeal dysphagia, both of which are prevalent in nursing homes and major risk factors for aspiration pneumonia. This study aimed to evaluate the predictive value of the Turkish Eating Assessment Tool (T-EAT-10) and the Nutritional Form for the Elderly (NUFFE-TR) for aspiration pneumonia in nursing home residents. Methods: This cross-sectional study included 415 residents aged 65 and older in Ankara, Turkey. Data were collected via face-to-face interviews using a sociodemographic form, the 10-item T-EAT-10 for dysphagia screening, and the 12-item NUFFE-TR for malnutrition risk assessment. Aspiration pneumonia history was obtained from medical records. Logistic regression and Receiver Operating Characteristic (ROC) analyses were performed to identify independent predictors and determine optimal diagnostic thresholds. Results: The prevalence of aspiration pneumonia was 10.1%. Residents with aspiration pneumonia had significantly higher median T-EAT-10 (24.0 vs. 4.0; p < 0.001) and NUFFE-TR (11.0 vs. 3.0; p < 0.001) scores. In multivariate logistic regression, the T-EAT-10 total score emerged as the only independent predictor of aspiration pneumonia (OR = 1.125, 95% CI [1.069–1.184], p < 0.001). ROC analysis showed excellent discriminative ability for the T-EAT-10 (AUC = 0.886, p 12 (sensitivity: 80.95%, specificity: 83.11%). Conclusions: The T-EAT-10 is a practical and highly effective screening tool for identifying aspiration pneumonia risk in institutionalized elderly populations. A clinical threshold of >12 is recommended for identifying high-risk residents, which is substantially higher than the standard dysphagia screening cut-off. Systematic screening using T-EAT-10 and NUFFE-TR should be integrated into routine geriatric care in nursing homes to improve preventive strategies. Oropharyngeal dysphagia Malnutrition Aspiration pneumonia Nursing home T-EAT-10 NUFFE-TR Figures Figure 1 Figure 2 INTRODUCTION Aging is associated with progressive physiological changes that increase vulnerability to nutritional deficiencies and swallowing dysfunction. Among older adults residing in nursing homes, these two conditions — malnutrition and oropharyngeal dysphagia — are particularly prevalent and frequently coexist, placing residents at heightened risk for serious respiratory complications, most notably aspiration pneumonia. Aspiration pneumonia arises when oropharyngeal secretions or food material is aspirated into the lower respiratory tract, triggering an infectious and inflammatory response. It is one of the leading causes of morbidity and mortality in institutionalized elderly populations, and its clinical burden has increased substantially over recent decades as the global nursing home population has grown. Oropharyngeal dysphagia is now widely recognized as a major geriatric syndrome. Its prevalence among nursing home residents exceeds 50% in some reports, driven by age-related sarcopenia of the swallowing musculature, neurological comorbidities such as stroke and dementia, and polypharmacy [ 1 ]. The pathophysiological consequences of dysphagia are twofold: impaired efficacy of swallowing leads to inadequate nutrient and fluid intake, predisposing residents to malnutrition and dehydration, while impaired safety of swallowing — characterized by delayed laryngeal vestibule closure and reduced pharyngeal clearance — results in aspiration of material into the airway, ultimately precipitating aspiration pneumonia [ 1 ]. In elderly nursing home residents with dysphagia, aspiration pneumonia has been reported to occur in 43–50% of cases within the first year, carrying a mortality rate of up to 45%. Malnutrition, a second major geriatric syndrome in this population, compounds these risks. Studies in Dutch nursing homes have demonstrated that residents with clinically relevant swallowing problems are 1.5 times more likely to be malnourished than those without dysphagia [ 2 ]. In that national prevalence study of 6,349 residents, approximately 12% had swallowing problems, 10% were malnourished, and nearly one in five problematic swallowers was concurrently malnourished. Beyond dysphagia, malnutrition itself impairs respiratory muscle strength, immune function, and mucociliary clearance — all of which further elevate susceptibility to pulmonary infections including aspiration pneumonia. The bidirectional relationship between dysphagia and malnutrition thus creates a self-reinforcing cycle that accelerates functional decline in nursing home residents. Given this clinical burden, early and reliable screening for both dysphagia and malnutrition risk is essential in nursing home settings. The Eating Assessment Tool-10 (EAT-10) is a validated, patient-reported 10-item instrument developed to screen for dysphagia symptom severity. It is widely used in clinical practice due to its brevity and ease of administration, with a score of ≥ 3 indicating abnormal swallowing function [ 3 ]. The Turkish adaptation of the EAT-10 (T-EAT-10) has been validated for use in Turkish-speaking populations [ 4 ]. Alongside dysphagia screening, nutritional risk assessment is equally critical. The Nutritional Form for the Elderly (NUFFE) is a malnutrition screening instrument specifically developed for older adults, encompassing functional, social, nutritional, and health-related determinants of dietary intake without requiring anthropometric measurements or laboratory parameters [ 5 ]. Its Norwegian version (NUFFE-NO) demonstrated a Cronbach's alpha of 0.77 and a strong concurrent validity correlation with the Mini Nutritional Assessment (rs = − 0.74), supporting its psychometric robustness for institutional screening [ 6 ]. The Turkish version of the NUFFE (NUFFE-TR) was subsequently adapted and validated in a 12-item structure following removal of items with low factor loadings [ 7 ]. Despite the well-established clinical relationship between dysphagia, malnutrition, and aspiration pneumonia, few studies have prospectively examined the independent predictive value of standardized screening tools for aspiration pneumonia in nursing home populations. Most prior research has focused on the association between dysphagia and malnutrition as outcomes in themselves, rather than evaluating the utility of brief screening instruments in predicting aspiration pneumonia — a clinically critical endpoint. Furthermore, studies conducted in nursing home settings using both dysphagia and nutritional screening tools concurrently remain sparse, and none have evaluated the T-EAT-10 and NUFFE-TR together in this context. The present cross-sectional study therefore aimed to examine the predictive value of the T-EAT-10 and NUFFE-TR for aspiration pneumonia in a large sample of nursing home residents aged 65 years and over in Ankara, Turkey. Secondary objectives included determining the optimal diagnostic cut-off value for the T-EAT-10 in identifying residents at risk for aspiration pneumonia, and exploring sociodemographic and clinical characteristics associated with aspiration pneumonia occurrence. To our knowledge, this is the first study to evaluate the combined screening utility of T-EAT-10 and NUFFE-TR as predictors of aspiration pneumonia in Turkish nursing home residents. MATERIALS AND METHODS This study is a cross-sectional, descriptive-analytical research conducted to examine the levels of dysphagia and malnutrition risk in geriatric individuals residing in nursing homes. In Ankara province, a total of 2,963 people reside in 49 nursing homes (37 private, 10 public, and 2 municipal). In the study, with a malnutrition prevalence of 50%, The minimum required sample size was calculated as 408 participants, based on an estimated malnutrition prevalence of 50%, with a 3% margin of error and a 95% confidence level. Ethics approval for this study was obtained from Ankara Yıldırım Beyazıt University Health Sciences Ethics Committee dated 22.04.2024 with decision number 04.701. The research was conducted in accordance with the ethical principles of the Declaration of Helsinki (2013 revision). The data collection process was completed with a total of 415 participants between July 15 - September 15, 2024. The study population consisted of individuals aged 65 and over residing in the relevant nursing homes. The inclusion criteria for the study were defined as being 65 years of age or older, residing in a nursing home for at least one month, being able to communicate verbally, and being willing to participate in the study. The exclusion criteria were determined as having a consciousness disorder or severe cognitive impairment, acute infection or severe systemic disease, and anatomical abnormality preventing swallowing assessment. A total of 415 individuals meeting these specified criteria were included in the study. Data Collection Tools Data were collected through face-to-face interviews conducted by physicians participating in the research team. The interviews were conducted in quiet and appropriate environments within the nursing homes, with each interview lasting approximately 15–20 minutes. This approach constitutes one of the study's strengths, enhancing data reliability. 1) Sociodemographic and Clinical Information Form With the form prepared by researchers based on literature, participants' age group, gender, duration of nursing home stay, denture use, smoking, and history of aspiration pneumonia were queried. Aspiration pneumonia history within the last 3 years was obtained retrospectively from the patients' medical and nursing home records. 2) Turkish Eating Assessment Tool (T-EAT-10) The Turkish Eating Assessment Tool [ 4 ] (T-EAT-10) is a 10-item instrument developed by Demir et al. to evaluate the severity of dysphagia symptoms and the individual's self-perceived dysphagia risk status over Eating Assessment Tool [ 3 ] in Turkish language. A score of 3 or above on the scale is considered abnormal. The scale comprises 10 questions through which patients self-report their swallowing problems. A 5-point Likert-type scoring system ranging from 0 (No problem) to 4 (Severe problem) is employed for each item. The minimum obtainable score from the scale is 0, while the maximum is 40. The validity and reliability of the Turkish version of the scale were established by Demir and colleagues [ 4 ]. T-EAT-10 has been demonstrated to be a practical and reliable tool that can be completed in approximately 2 minutes. A score of 3 or higher (≥ 3) obtained from the scale is considered abnormal and indicates that the individual is at risk for dysphagia. An elevation in the score signifies an increase in the severity of swallowing difficulty symptoms [ 3 , 4 ]. 3) Nutritional Form for the Elderly (NUFFE-TR) The original version of this scale, developed to assess the nutritional status of elderly individuals, was introduced to the literature in Swedish (Nutritional Form for the Elderly - NUFFE). The scale is a malnutrition screening tool that does not require anthropometric measurements or biochemical parameters and can be readily implemented in clinical nursing care [ 5 ]. The original scale comprises 15 items encompassing nutritional history, dietary assessment, and general evaluation. The items employ an ordinal scale structure with three options specific to each question (0, 1, 2) [ 5 ]. The Turkish validity and reliability study of the scale was conducted by Kamarlı Altun and colleagues. Following the analyses, three items (N6, N8, N14) were removed from the scale due to low factor loadings, resulting in a 12-item structure for NUFFE-TR [ 7 ]. The minimum score obtainable from the 12-item Turkish version is 0, and the maximum score is 24. In the scale, the most favorable option is scored as 0, the intermediate option as 1, and the unfavorable option as 2 points. As the total score obtained from the scale increases, the individual's malnutrition risk and nutritional inadequacy level escalate [ 7 ]. Statistical Analysis Statistical analyses were performed using IBM SPSS Statistics, Version 27.0 (IBM Corp., Armonk, NY, USA) [ 8 ]. Categorical data were presented as frequency (n) and percentage (%), while continuous variables were presented as mean ± standard deviation and median (min-max). The normality assumption was tested using the Kolmogorov-Smirnov test. Since continuous variables did not show normal distribution, non-parametric tests were used. Mann-Whitney U test was used for comparisons between two independent groups. A binary logistic regression model was established to determine independent predictors of dysphagia risk. Model fit was evaluated with the Hosmer-Lemeshow test. Statistical significance level was accepted as p < 0.05. Roc Analysis was calculated with MedCalc® Statistical Software version 23.4.4 (MedCalc Software Ltd, Ostend, Belgium) [ 9 ]. RESULTS Sociodemographic and Clinical Characteristics A total of 415 nursing home residents aged 65 years and older were included in the study. Of the participants, 227 (54.7%) were female and 188 (45.3%) were male. The majority of residents fell into the 75–84 age group (n = 194, 46.7%), followed by the 65–74 group (n = 142, 34.2%) and those aged 85 years and older (n = 79, 19.0%). Regarding duration of nursing home stay, 166 participants (40.0%) had resided for less than one year, 211 (50.8%) for 1–5 years, and 38 (9.2%) for more than five years. Denture use was reported by 202 participants (48.7%), and 103 (24.8%) were current or former smokers. In terms of clinical comorbidities, hypertension was the most prevalent condition, present in 283 participants (68.2%), followed by diabetes mellitus in 139 (33.5%), heart disease in 178 (42.9%), and a history of stroke in 53 participants (12.8%). The majority of participants had a body mass index (BMI) in the normal-to-overweight range; 193 (46.5%) had a BMI of 18.5–24.9 kg/m², 182 (43.9%) had a BMI of 25.0–29.9 kg/m², and 31 (7.5%) had a BMI ≥ 30 kg/m². Only 9 participants (2.2%) were underweight (BMI < 18.5 kg/m²). The overall median BMI was 25.35 kg/m² (interquartile range [IQR]: 23.44–26.83). Prevalence and Characteristics of Aspiration Pneumonia Residents with a history of aspiration pneumonia were significantly older than those without (p < 0.001). Among the 42 residents with aspiration pneumonia, 5 (11.9%) were in the 65–74 age group, 20 (47.6%) were in the 75–84 age group, and 17 (40.5%) were aged 85 years or older. By contrast, among the 373 residents without aspiration pneumonia, the majority fell into the 65–74 (36.7%) and 75–84 (46.6%) age groups, with only 16.6% aged 85 years or older. When examined from the perspective of each age group's internal distribution, aspiration pneumonia was present in 3.5% of the 65–74 group (5/142), 10.3% of the 75–84 group (20/194), and 21.5% of those aged 85 years and older (17/79), indicating a progressive increase in aspiration pneumonia prevalence with advancing age. Duration of nursing home stay was also significantly associated with aspiration pneumonia (p < 0.001); among residents who had stayed for more than five years, 28.6% had a history of aspiration pneumonia, compared with 14.3% among those with a stay of less than one year. Denture use was significantly more common among residents with aspiration pneumonia (66.7% vs. 33.3% without dentures; p = 0.014). History of stroke was present in 26.2% of those with aspiration pneumonia compared with 11.3% of those without (p = 0.006). Heart disease was significantly more prevalent in the aspiration pneumonia group (69.0% vs. 39.9%; p 0.05 for all). Complete sociodemographic and clinical comparisons are presented in Table 1 . Table 1 Sociodemographic and Clinical Characteristics According to History of Aspiration Pneumonia Variable Total (n = 415) No aspiration pneumonia (n = 373) Aspiration pneumonia (n = 42) P Gender, n (%) Female 227 (54.7) 209 (56.0) 18 (42.9) 0.104 Male 188 (45.3) 164 (44.0) 24 (57.1) Age group, n (%) 65–74 142 (34.2) 137 (36.7) 5 (11.9) < 0.001 75–84 194 (46.7) 174 (46.6) 20 (47.6) ≥ 85 79 (19.0) 62 (16.6) 17 (40.5) Duration of nursing home stay, n (%) < 1 year 166 (40.0) 160 (42.9) 6 (14.3) 5 years 38 (9.2) 26 (7.0) 12 (28.6) Body mass index (kg/m 2 ) < 18.5 9 (2.2) 8 (2.1) 1 (2.4) N/C 18.5–24.9 193 (46.5) 170 (45.6) 23 (54.8) 25.0-29.9 182 (43.9) 164 (44.4) 18 (42.9) ≥ 30 31 (7.5) 31 (8.3) 0 (0.0) Denture use, n (%) No 213 (51.3) 199 (53.4) 14 (33.3) 0.014 Yes 202 (48.7) 174 (46.6) 28 (66.7) Smoking, n (%) No 312 (75.2) 277 (74.3) 35 (83.3) 0.197 Yes 103 (24.8) 96 (25.7) 7 (16.7) Hypertension, n (%) No 132 (31.8) 124 (33.2) 8 (19.0) 0.061 Yes 283 (68.2) 249 (66.8) 34 (81.0) COPD No 373 (89.9) 338 (90.6) 35 (83.3) 0.138 Yes 42 (10.1) 35 (9.4) 7 (16.7) Diabetes mellitus, n (%) No 276 (66.5) 254 (68.1) 22 (52.4) 0.041 Yes 139 (33.5) 119 (31.9) 20 (47.6) History of stroke, n (%) No 362 (87.2) 331 (88.7) 31 (73.8) 0.006 Yes 53 (12.8) 42 (11.3) 11 (26.2) Heart disease, n (%) No 237 (57.1) 224 (60.1) 13 (31.0) < 0.001 Yes 178 (42.9) 149 (39.9) 29 (69.0) Values are presented as number (percentage). Column percentages are shown.Comparisons were performed using the chi-square test or Fisher’s exact test, as appropriate.p < 0.05 was considered statistically significant. N/C: Not calculated due to one of the cells was zero. COPD: Chronic obstructive pulmonary disease Comparison of T-EAT-10, NUFFE-TR, and BMI Scores by Aspiration Pneumonia Status Both T-EAT-10 and NUFFE-TR scores differed significantly between residents with and without aspiration pneumonia (Table 2 ). The median T-EAT-10 score in participants with aspiration pneumonia was 24.0 (IQR: 13.8–30.3), compared with 4.0 (IQR: 0.0–10.0) in those without aspiration pneumonia (p < 0.001). Similarly, the median NUFFE-TR total score was significantly higher in participants with aspiration pneumonia (median: 11.0, IQR: 7.0–18.0) than in those without (median: 3.0, IQR: 2.0–6.0) (p < 0.001). BMI was also significantly lower in residents with aspiration pneumonia (median: 24.33 kg/m², IQR: 21.88–26.35) compared with those without (median: 25.35 kg/m², IQR: 23.44–26.83) (p = 0.044). Table 2 Comparison of NUFFE-TR, T-EAT-10, and BMI According to History of Aspiration Pneumonia Variable Total No aspiration pneumonia Aspiration pneumonia p† Median (25.-75. percentile) NUFFE-TR total score 3.0 (2.0–6.0) 3.0 (2.0–6.0) 11.0 (7.0–18.0) < 0.001 T-EAT-10 total score 4.0 (0.0–10.0) 4.0 (0.0–10.0) 24.0 (13.8–30.3) < 0.001 BMI (kg/m²) 25.35 (23.44–26.83) 25.35 (23.44–26.83) 24.33 (21.88–26.35) 0.044 Values are presented as median (25th–75th percentile). †Comparisons were performed using the Mann–Whitney U test. p < 0.05 was considered statistically significant. Logistic Regression Analysis: Independent Predictors of Aspiration Pneumonia Binary logistic regression analysis was conducted to identify independent predictors of aspiration pneumonia, with T-EAT-10 total score, NUFFE-TR total score, age group, duration of nursing home stay, denture use, history of stroke, heart disease, and diabetes mellitus entered as covariates (Table 3 ). The overall model was statistically significant (χ²(10) = 104.958, p < .001) and demonstrated good fit as confirmed by the Hosmer-Lemeshow test (χ²(8) = 5.151, p = .741). The model correctly classified 91.8% of cases overall (sensitivity for aspiration pneumonia: 42.9%; specificity for no aspiration pneumonia: 97.3%), with a Nagelkerke R² of 0.465. In the multivariate model, T-EAT-10 total score emerged as the only statistically significant independent predictor of aspiration pneumonia (B = 0.118, OR = 1.125, 95% CI [1.069–1.184], p < .001), indicating that each one-point increase in the T-EAT-10 score was associated with a 12.5% increase in the odds of aspiration pneumonia. NUFFE-TR total score did not reach statistical significance as an independent predictor in the multivariate model (B = 0.082, OR = 1.085, 95% CI [0.989–1.190], p = .079), although its univariate association with aspiration pneumonia was highly significant (p < .001). None of the other covariates — including age group, duration of nursing home stay, denture use, history of stroke, heart disease, or diabetes mellitus — were independently associated with aspiration pneumonia after adjustment. Table 3 Logistic Regression Analysis Predicting Aspiration Pneumonia Variable B SE Wald df p OR 95% CI NUFFE total score .082 .047 3.089 1 .079 1.085 0.989–1.190 EAT-10 total score .118 .026 19.867 1 < 0.001 1.125 1.069–1.184 Age group 75–84 (ref: 65–74) .572 .599 .912 1 .340 1.772 0.548–5.729 ≥ 85 (ref: 65–74) .882 .656 1.807 1 .179 2.415 0.666–8.753 Length of stay in nursing home 1–5 years (ref: 5 years (ref: < 1 year) 1.024 .718 2.034 1 .154 2.784 0.681–11.381 Denture use (yes) .671 .468 2.059 1 .151 1.956 0.781–4.897 Stroke history (yes) −.280 .518 .292 1 .589 0.756 0.274–2.08 Cardiac disease (yes) .048 .453 .011 1 .916 1.049 0.432–2.54 Diabetes (yes) .113 .427 .070 1 .791 1.120 0.485–2.585 Constant −5.871 .769 58.276 1 < .001 Note. n = 415. Dependent variable: Aspiration pneumonia (0 = No, 1 = Yes). OR = Odds Ratio; CI = Confidence Interval; NUFFE-TR = Nutritional Form for the Elderly-Turkish; EAT-10-TR = Eating Assessment Tool-10-TR. Reference categories are indicated in parentheses. a Omnibus model test: χ²(10) = 104.958, p < .001. b Model summary: −2LL = 167.052; Cox & Snell R² = .223; Nagelkerke R² = .465. c Hosmer and Lemeshow goodness-of-fit test: χ²(8) = 5.151, p = .741. d Classification accuracy: Overall 91.8% (No: 97.3%; Yes: 42.9%). Cut value = .500. Diagnostic Accuracy of T-EAT-10 for Aspiration Pneumonia: ROC Analysis ROC curve analysis was performed to evaluate the diagnostic accuracy of the T-EAT-10 for identifying aspiration pneumonia (Fig. 1 ). The area under the ROC curve (AUC) was 0.886 (SE = 0.028; 95% CI [0.851, 0.915]; z = 13.949; p < .0001), indicating excellent discriminative ability of the T-EAT-10 for aspiration pneumonia. The optimal cut-off value was determined using the Youden index (J = Sensitivity + Specificity − 1). The criterion T-EAT-10 score > 12 maximized the Youden index (J = 0.6406), yielding a sensitivity of 80.95% (95% CI [65.9–91.4]), specificity of 83.11% (95% CI [78.9–86.8]), positive likelihood ratio (+ LR) of 4.79, and negative likelihood ratio (− LR) of 0.23 (Table 4 ). At the conventional clinical cut-off of T-EAT-10 ≥ 3 (any abnormal swallowing), sensitivity was high at 95.24% but specificity was low at 46.92%, reflecting the screening-oriented nature of this threshold. As the cut-off was raised, specificity increased progressively while sensitivity declined, with a T-EAT-10 > 21 achieving a specificity of 93.30% at the cost of reduced sensitivity (64.29%). The ROC coordinates across all tested criterion values are presented in Table 4 . Table 4 ROC Curve Coordinates and Diagnostic Accuracy of EAT-10 for Aspiration Pneumonia Criterion Sensitivity (%) Specificity (%) +LR −LR Value 95% CI Value 95% CI Value 95% CI Value 95% CI > 0 97.62 87.4–99.9 33.78 29.0–38.8 1.47 1.35–1.61 0.070 0.010–0.49 > 3 95.24 83.8–99.4 46.92 41.8–52.1 1.79 1.60–2.02 0.100 0.026–0.39 > 6 90.48 77.4–97.3 64.08 59.0–68.9 2.52 2.13–2.98 0.150 0.058–0.38 > 9 90.48 77.4–97.3 72.92 68.1–77.4 3.34 2.75–4.05 0.130 0.051–0.33 > 12 † 80.95 65.9–91.4 83.11 78.9–86.8 4.79 3.66–6.27 0.230 0.12–0.43 > 15 73.81 58.0–86.1 85.79 81.8–89.2 5.19 3.82–7.07 0.310 0.18–0.51 > 18 69.05 52.9–82.4 88.20 84.5–91.3 5.85 4.15–8.25 0.350 0.22–0.55 > 21 64.29 48.0–78.4 93.30 90.3–95.6 9.59 6.17–14.90 0.380 0.25–0.57 > 24 47.62 32.0–63.6 96.51 94.1–98.1 13.66 7.34–25.43 0.540 0.41–0.72 > 27 35.71 21.6–52.0 97.32 95.1–98.7 13.32 6.40–27.75 0.660 0.53–0.83 > 33 14.29 5.4–28.5 100.00 99.0–100.0 — — 0.860 0.76–0.97 Note. Variable: EAT-10 total score. Outcome: Aspiration pneumonia (positive: n = 42; negative: n = 373; N = 415). +LR = positive likelihood ratio; −LR = negative likelihood ratio; CI = confidence interval. Only selected criterion values are shown for clarity. a Area under the ROC curve (AUC) = 0.886 (SE = 0.028; 95% CI [0.851, 0.915]; z = 13.949; p 12) maximises the sum of sensitivity and specificity (J = Sensitivity + Specificity − 1). † Optimal cut-off point selected by the Youden index (highlighted row): criterion > 12, Sensitivity = 80.95% (95% CI [65.9, 91.4]), Specificity = 83.11% (95% CI [78.9, 86.8]), +LR = 4.79, −LR = 0.23. The prevalence of dysphagia risk (T-EAT-10 ≥ 3) in the total study population is presented in Fig. 2 , illustrating the distribution of dysphagia risk screening results across participants. DISCUSSION This cross-sectional study examined the predictive value of the T-EAT-10 and NUFFE-TR for aspiration pneumonia among 415 nursing home residents aged 65 years and older in Ankara, Turkey. The principal findings were that T-EAT-10 emerged as the only independent predictor of aspiration pneumonia in multivariate analysis, demonstrating excellent discriminative ability (AUC = 0.886), while NUFFE-TR, although strongly associated with aspiration pneumonia in univariate analyses, did not retain independent significance after adjustment. An optimal cut-off of T-EAT-10 > 12 was identified as the most diagnostically accurate threshold for aspiration pneumonia detection in this population. Prevalence of Aspiration Pneumonia The prevalence of aspiration pneumonia in the present study was 10.1%, a figure that is broadly consistent with data from large nursing home cohorts. Langmore et al. reported a 3% prevalence in a cross-sectional analysis of over 100,000 U.S. nursing home residents using administrative data, though this figure likely reflects underreporting inherent to retrospective record review rather than active clinical screening [ 10 ]. The higher prevalence observed in our study may reflect the systematic physician-administered face-to-face data collection methodology and the older, comorbidity-rich profile of our sample. Indeed, Sarabia-Cobo et al. reported that among institutionalized elderly in Spanish nursing homes, those with oropharyngeal dysphagia had markedly higher rates of pneumonia and mortality [ 11 ], further supporting the premise that active screening yields higher detection than passive records-based ascertainment. T-EAT-10 as an Independent Predictor of Aspiration Pneumonia The finding that T-EAT-10 total score was the only statistically significant independent predictor of aspiration pneumonia (OR = 1.125 per one-point increase, 95% CI [1.069–1.184]) underscores the clinical utility of this brief self-report instrument in the nursing home setting. A systematic review and meta-analysis by Zhang et al. confirmed that the EAT-10 demonstrates good overall diagnostic performance for dysphagia screening (AUC 0.873–0.903 depending on cut-off), and concluded that a threshold of ≥ 3 offers the best balance for general dysphagia screening [ 12 ]. Crucially, the present study extends this evidence by demonstrating that the T-EAT-10 predicts not just dysphagia symptom risk but the clinically critical outcome of aspiration pneumonia, and that doing so requires a substantially higher cut-off than the conventional ≥ 3 threshold. Optimal Cut-Off Value: T-EAT-10 > 12 A key contribution of this study is the identification of T-EAT-10 > 12 as the optimal threshold for aspiration pneumonia prediction (sensitivity 80.95%, specificity 83.11%, +LR 4.79). This is considerably higher than the standard dysphagia screening cut-off of ≥ 3. This divergence is clinically meaningful: the ≥ 3 threshold was designed to capture any degree of perceived swallowing difficulty, whereas aspiration pneumonia represents a more severe clinical endpoint requiring a higher symptom burden to predict reliably. In a study of adults with stable COPD, Regan et al. similarly found that an EAT-10 cut-off of > 9 optimally predicted aspiration confirmed by fiberoptic endoscopic evaluation (AUC = 0.88; sensitivity 91.67%, specificity 77.78%) [ 13 ] suggesting that the optimal threshold for predicting aspiration — as opposed to dysphagia symptomatology — may vary by population and clinical context. Our finding of a higher optimal cut-off (> 12) may reflect the mixed etiology and older age profile of nursing home residents compared with the COPD clinic population studied by Regan et al. And also the higher cut-off value (> 12) of the T-EAT-10 for predicting aspiration pneumonia in our study may be attributed to the baseline physiological changes in the swallowing mechanism of older adults, known as presbyphagia. Since mild swallowing difficulties may be a natural part of aging rather than a strictly pathological state, a higher threshold may be clinically more relevant to identify true aspiration risk in institutionalized populations [ 14 , 15 ]. The Role of NUFFE-TR and the Dysphagia–Malnutrition Relationship Although NUFFE-TR did not independently predict aspiration pneumonia in the multivariate model (p = .079), its strong univariate association (p < .001) and near-significant trend in the adjusted model suggest that malnutrition risk contributes meaningfully to aspiration pneumonia burden, likely through pathways partially mediated by dysphagia severity. This interpretation is consistent with the conceptual framework proposed by Baijens et al. in the European Society for Swallowing Disorders white paper, which recognizes that impaired swallowing efficacy leads to malnutrition, while malnutrition in turn impairs respiratory muscle strength and mucosal immune defenses — creating a bidirectional relationship that amplifies pneumonia risk [ 16 ]. The finding that NUFFE-TR's independent effect was attenuated by T-EAT-10 in the multivariate model may indicate substantial collinearity between the two instruments, since residents with more severe dysphagia are inherently at greater nutritional risk. These results are consistent with the nationally representative Dutch study by Huppertz et al., which found that nursing home residents with oropharyngeal dysphagia symptoms were 1.5 times more likely to be malnourished than those without — confirming the tight epidemiological coupling between these two geriatric syndromes [ 2 ]. More recently, Engberg et al. similarly reported that approximately one-third of nursing home residents in Sweden exhibited dysphagia, and that the condition was frequently unrecognized by both patients and caregivers, underlining the value of systematic screening [ 17 ]. Clinical and Comorbidity-Related Risk Factors The progressive increase in aspiration pneumonia prevalence with advancing age — from 3.5% in the 65–74 age group to 21.5% in those aged 85 and older — aligns with well-established evidence that aging is associated with sarcopenic changes in the swallowing musculature, reduced laryngeal elevation, and impaired pharyngeal clearance. De Sire et al. comprehensively reviewed these overlapping pathophysiological mechanisms in their discussion of sarcopenic dysphagia, underscoring that the combined burden of sarcopenia, dysphagia, and poor oral health creates a self-reinforcing cycle of functional decline in elderly individuals [ 18 ]. In the present study, stroke history and heart disease were significantly associated with aspiration pneumonia in univariate analysis, consistent with findings by Taylor et al., who demonstrated that patients with aspiration risk factors — including neurological disorders and dysphagia — had substantially higher long-term mortality and rehospitalization rates in a large UK pneumonia cohort [ 19 ]. These comorbidities did not retain statistical significance in the multivariate model after adjustment for T-EAT-10, suggesting that their effect on aspiration pneumonia may be substantially mediated through dysphagia severity, as captured by the T-EAT-10 score. The significant association between denture use and aspiration pneumonia is a noteworthy finding that merits clinical attention. Takeuchi et al. demonstrated in a prospective cohort of Japanese nursing home residents that denture wearing moderated the relationship between aspiration risk and incident pneumonia — while dentures may facilitate oral bolus control, they also provide a substrate for oral bacterial colonization if oral hygiene is suboptimal [ 20 ]. Similarly, Chen et al., in their cross-sectional study of 775 nursing home residents in China using the EAT-10, identified history of aspiration, heart attack, and pneumonia as the strongest risk factors for dysphagia risk, with heart disease carrying an OR of 3.804 [ 21 ] — findings that parallel our own observations. Strengths and Limitations This study has several notable strengths. The large, population-based sample drawn from a diversity of nursing home types (private, public, and municipal) in Ankara province enhances the representativeness of findings. Data were collected through structured face-to-face interviews by physicians, minimizing misclassification bias. The use of ROC Analysis to derive an evidence-based cut-off value for aspiration pneumonia prediction adds direct clinical applicability. To our knowledge, this is the first study to evaluate T-EAT-10 and NUFFE-TR concurrently as predictors of aspiration pneumonia in Turkish nursing home residents. Several limitations must be acknowledged. The cross-sectional design precludes causal inference; aspiration pneumonia history was ascertained from medical records rather than confirmed by clinical or radiological evaluation at the time of assessment, which may introduce both ascertainment bias. The retrospective ascertainment of aspiration pneumonia from records may have led to underreporting, particularly for mild or atypically presenting episodes. Furthermore, objective dysphagia assessment using instrumental methods such as videofluoroscopic swallowing study or fiberoptic endoscopic evaluation was not performed, meaning that T-EAT-10 scores reflect self-perceived swallowing symptoms rather than physiologically confirmed aspiration. As a scoping review by Chen et al. noted, the nursing home setting remains resource-constrained with respect to speech-language pathology access, particularly in developing-country contexts [ 22 ], and our findings should be interpreted within this pragmatic screening context. Finally, cognitive status was an exclusion criterion, meaning that residents with cognitive impairment — who are at particularly high risk for dysphagia and aspiration — were not included, potentially limiting the generalizability of findings to this vulnerable subgroup. CONCLUSION The T-EAT-10 is a practical, brief, and highly discriminating screening tool for aspiration pneumonia risk in nursing home residents aged 65 years and older. A cut-off score of > 12 maximizes diagnostic accuracy in this population, providing a clinically actionable threshold that is distinct from — and substantially higher than — the conventional dysphagia screening cut-off of ≥ 3. Routine T-EAT-10 screening, combined with nutritional risk assessment using NUFFE-TR, should be integrated into standard care protocols for institutionalized elderly individuals. Future prospective studies incorporating instrumental swallowing assessment and longer follow-up periods are warranted to confirm the independent predictive value of these instruments and to evaluate the impact of screening-based interventions on aspiration pneumonia incidence and related outcomes. Declarations Ethics approval and consent to participate Ethics approval for this study was obtained from the Ankara Yıldırım Beyazıt University Health Sciences Ethics Committee (Date: 22.04.2024, Decision Number: 04.701). The research was conducted in accordance with the ethical principles of the Declaration of Helsinki (2013 revision). Informed consent was obtained from all participants or their legal representatives before their inclusion in the study. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding The authors received no financial support for the research, authorship, and/or publication of this article. Author Contribution All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by all authors. All authors participated in drafting the manuscript and critically revising it for important intellectual content. All authors read and approved the final manuscript. Acknowledgement The authors would like to thank all the nursing home residents and staff for their participation and cooperation in this study. Data Availability The datasets generated and analyzed during the current study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request. References Clave P, Rofes L, Carrion S, Ortega O, Cabre M, Serra-Prat M, Arreola V. Pathophysiology, relevance and natural history of oropharyngeal dysphagia among older people. Nestle Nutr Inst Workshop Ser. 2012;72:57–66. Huppertz VAL, Halfens RJG, van Helvoort A, de Groot L, Baijens LWJ, Schols J. Association between Oropharyngeal Dysphagia and Malnutrition in Dutch Nursing Home Residents: Results of the National Prevalence Measurement of Quality of Care. J Nutr Health Aging. 2018;22(10):1246–52. Belafsky PC, Mouadeb DA, Rees CJ, Pryor JC, Postma GN, Allen J, Leonard RJ. Validity and reliability of the Eating Assessment Tool (EAT-10). Ann Otol Rhinol Laryngol. 2008;117(12):919–24. Demir N, Serel Arslan S, Inal O, Karaduman AA. Reliability and Validity of the Turkish Eating Assessment Tool (T-EAT-10). Dysphagia. 2016;31(5):644–9. Söderhamn U, Söderhamn O. Reliability and validity of the nutritional form for the elderly (NUFFE). J Adv Nurs. 2002;37(1):28–34. Söderhamn U, Flateland S, Jessen L, Söderhamn O. Norwegian version of the Nutritional Form for the Elderly: sufficient psychometric properties for performing institutional screening of elderly patients. Nutr Res. 2009;29(11):761–7. Kamarli Altun H, Suna G, Çiftçi S. Turkish Adaptation of Nutritional Form for the Elderly: A Methodological Study. Turkiye Klinikleri J Health Sci. 2022;7(4):1135–42. IBM Corp. IBM SPSS Statistics for Windows. In., 27.0 edn. Armonk, NY; 2020. MedCalc Software Ltd. MedCalc Statistical Software. In., 23.4.4 edn. Ostend, Belgium: MedCalc Software Ltd,; 2024. Langmore SE, Skarupski KA, Park PS, Fries BE. Predictors of aspiration pneumonia in nursing home residents. Dysphagia. 2002;17(4):298–307. Sarabia-Cobo CM, Pérez V, de Lorena P, Domínguez E, Hermosilla C, Nuñez MJ, Vigueiro M, Rodríguez L. The incidence and prognostic implications of dysphagia in elderly patients institutionalized: A multicenter study in Spain. Appl Nurs Res. 2016;30:e6–9. Zhang PP, Yuan Y, Lu DZ, Li TT, Zhang H, Wang HY, Wang XW. Diagnostic Accuracy of the Eating Assessment Tool-10 (EAT-10) in Screening Dysphagia: A Systematic Review and Meta-Analysis. Dysphagia. 2023;38(1):145–58. Regan J, Lawson S, De Aguiar V. The Eating Assessment Tool-10 Predicts Aspiration in Adults with Stable Chronic Obstructive Pulmonary Disease. Dysphagia. 2017;32(5):714–20. Labeit B, Lapa S, Lueg G, Joebges R, Hofacker J, Muhle P, Suntrup-Krueger S, Werner CJ, Schreiber S, Wirth R, et al. Oropharyngeal dysphagia: a narrative review towards an integrated neurogeriatric perspective. Lancet Healthy Longev. 2025;6(12):100794. Namasivayam-MacDonald AM, Riquelme LF. Presbyphagia to Dysphagia: Multiple Perspectives and Strategies for Quality Care of Older Adults. Semin Speech Lang. 2019;40(3):227–42. Baijens LW, Clave P, Cras P, Ekberg O, Forster A, Kolb GF, Leners JC, Masiero S, Mateos-Nozal J, Ortega O, et al. European Society for Swallowing Disorders - European Union Geriatric Medicine Society white paper: oropharyngeal dysphagia as a geriatric syndrome. Clin Interv Aging. 2016;11:1403–28. Engberg AV, Rångevall G, Eriksson K, Tuomi L. Prevalence of Dysphagia and Risk of Malnutrition in Elderly Living in Nursing Homes. Dysphagia. 2024;39(6):1065–70. de Sire A, Ferrillo M, Lippi L, Agostini F, de Sire R, Ferrara PE, Raguso G, Riso S, Roccuzzo A, Ronconi G et al. Sarcopenic Dysphagia, Malnutrition, and Oral Frailty in Elderly: A Comprehensive Review. Nutrients 2022, 14(5). Taylor JK, Fleming GB, Singanayagam A, Hill AT, Chalmers JD. Risk factors for aspiration in community-acquired pneumonia: analysis of a hospitalized UK cohort. Am J Med. 2013;126(11):995–1001. Takeuchi K, Izumi M, Furuta M, Takeshita T, Shibata Y, Kageyama S, Okabe Y, Akifusa S, Ganaha S, Yamashita Y. Denture Wearing Moderates the Association between Aspiration Risk and Incident Pneumonia in Older Nursing Home Residents: A Prospective Cohort Study. Int J Environ Res Public Health 2019, 16(4). Chen S, Cui Y, Ding Y, Sun C, Xing Y, Zhou R, Liu G. Prevalence and risk factors of dysphagia among nursing home residents in eastern China: a cross-sectional study. BMC Geriatr. 2020;20(1):352. Chen S, Kent B, Cui Y. Interventions to prevent aspiration in older adults with dysphagia living in nursing homes: a scoping review. BMC Geriatr. 2021;21(1):429. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9009756","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622313176,"identity":"f43bd4ef-5997-41af-ad57-e1b824a8a082","order_by":0,"name":"Melih Gaffar GOZUKARA","email":"","orcid":"","institution":"Ankara Yıldırım Beyazıt University","correspondingAuthor":false,"prefix":"","firstName":"Melih","middleName":"Gaffar","lastName":"GOZUKARA","suffix":""},{"id":622313177,"identity":"c416e1dc-49e5-438f-9924-7f2d7f1979c5","order_by":1,"name":"Sema Nur ERYILMAZ ALKAN","email":"","orcid":"","institution":"Ankara Yıldırım Beyazıt 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Aspiration Pneumonia\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9009756/v1/dace6ec5a01ac0cf915e71e1.png"},{"id":107181260,"identity":"0d922596-b615-4a4d-9901-049cb07719c1","added_by":"auto","created_at":"2026-04-17 17:19:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":414873,"visible":true,"origin":"","legend":"\u003cp\u003eDysphagia Risk Prevalence According to T-EAT-10 Survey\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9009756/v1/6a3357ab900ef9d4d6cb1d7e.png"},{"id":107705403,"identity":"ac654d4f-4ac8-43f9-ae40-fe512bf92a4e","added_by":"auto","created_at":"2026-04-24 09:12:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":903308,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9009756/v1/4077c3f4-76bc-49e5-b848-ff46f52a396f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePredictive Value of T-Eat-10 and Nuffe-tr for Aspiration Pneumonia in Nursing Home Residents: A Cross-sectional Study\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAging is associated with progressive physiological changes that increase vulnerability to nutritional deficiencies and swallowing dysfunction. Among older adults residing in nursing homes, these two conditions \u0026mdash; malnutrition and oropharyngeal dysphagia \u0026mdash; are particularly prevalent and frequently coexist, placing residents at heightened risk for serious respiratory complications, most notably aspiration pneumonia. Aspiration pneumonia arises when oropharyngeal secretions or food material is aspirated into the lower respiratory tract, triggering an infectious and inflammatory response. It is one of the leading causes of morbidity and mortality in institutionalized elderly populations, and its clinical burden has increased substantially over recent decades as the global nursing home population has grown.\u003c/p\u003e \u003cp\u003eOropharyngeal dysphagia is now widely recognized as a major geriatric syndrome. Its prevalence among nursing home residents exceeds 50% in some reports, driven by age-related sarcopenia of the swallowing musculature, neurological comorbidities such as stroke and dementia, and polypharmacy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The pathophysiological consequences of dysphagia are twofold: impaired efficacy of swallowing leads to inadequate nutrient and fluid intake, predisposing residents to malnutrition and dehydration, while impaired safety of swallowing \u0026mdash; characterized by delayed laryngeal vestibule closure and reduced pharyngeal clearance \u0026mdash; results in aspiration of material into the airway, ultimately precipitating aspiration pneumonia [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In elderly nursing home residents with dysphagia, aspiration pneumonia has been reported to occur in 43\u0026ndash;50% of cases within the first year, carrying a mortality rate of up to 45%.\u003c/p\u003e \u003cp\u003eMalnutrition, a second major geriatric syndrome in this population, compounds these risks. Studies in Dutch nursing homes have demonstrated that residents with clinically relevant swallowing problems are 1.5 times more likely to be malnourished than those without dysphagia [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In that national prevalence study of 6,349 residents, approximately 12% had swallowing problems, 10% were malnourished, and nearly one in five problematic swallowers was concurrently malnourished. Beyond dysphagia, malnutrition itself impairs respiratory muscle strength, immune function, and mucociliary clearance \u0026mdash; all of which further elevate susceptibility to pulmonary infections including aspiration pneumonia. The bidirectional relationship between dysphagia and malnutrition thus creates a self-reinforcing cycle that accelerates functional decline in nursing home residents.\u003c/p\u003e \u003cp\u003eGiven this clinical burden, early and reliable screening for both dysphagia and malnutrition risk is essential in nursing home settings. The Eating Assessment Tool-10 (EAT-10) is a validated, patient-reported 10-item instrument developed to screen for dysphagia symptom severity. It is widely used in clinical practice due to its brevity and ease of administration, with a score of \u0026ge;\u0026thinsp;3 indicating abnormal swallowing function [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The Turkish adaptation of the EAT-10 (T-EAT-10) has been validated for use in Turkish-speaking populations [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Alongside dysphagia screening, nutritional risk assessment is equally critical. The Nutritional Form for the Elderly (NUFFE) is a malnutrition screening instrument specifically developed for older adults, encompassing functional, social, nutritional, and health-related determinants of dietary intake without requiring anthropometric measurements or laboratory parameters [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Its Norwegian version (NUFFE-NO) demonstrated a Cronbach's alpha of 0.77 and a strong concurrent validity correlation with the Mini Nutritional Assessment (rs\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.74), supporting its psychometric robustness for institutional screening [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The Turkish version of the NUFFE (NUFFE-TR) was subsequently adapted and validated in a 12-item structure following removal of items with low factor loadings [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the well-established clinical relationship between dysphagia, malnutrition, and aspiration pneumonia, few studies have prospectively examined the independent predictive value of standardized screening tools for aspiration pneumonia in nursing home populations. Most prior research has focused on the association between dysphagia and malnutrition as outcomes in themselves, rather than evaluating the utility of brief screening instruments in predicting aspiration pneumonia \u0026mdash; a clinically critical endpoint. Furthermore, studies conducted in nursing home settings using both dysphagia and nutritional screening tools concurrently remain sparse, and none have evaluated the T-EAT-10 and NUFFE-TR together in this context.\u003c/p\u003e \u003cp\u003eThe present cross-sectional study therefore aimed to examine the predictive value of the T-EAT-10 and NUFFE-TR for aspiration pneumonia in a large sample of nursing home residents aged 65 years and over in Ankara, Turkey. Secondary objectives included determining the optimal diagnostic cut-off value for the T-EAT-10 in identifying residents at risk for aspiration pneumonia, and exploring sociodemographic and clinical characteristics associated with aspiration pneumonia occurrence. To our knowledge, this is the first study to evaluate the combined screening utility of T-EAT-10 and NUFFE-TR as predictors of aspiration pneumonia in Turkish nursing home residents.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eThis study is a cross-sectional, descriptive-analytical research conducted to examine the levels of dysphagia and malnutrition risk in geriatric individuals residing in nursing homes. In Ankara province, a total of 2,963 people reside in 49 nursing homes (37 private, 10 public, and 2 municipal). In the study, with a malnutrition prevalence of 50%, The minimum required sample size was calculated as 408 participants, based on an estimated malnutrition prevalence of 50%, with a 3% margin of error and a 95% confidence level. Ethics approval for this study was obtained from Ankara Yıldırım Beyazıt University Health Sciences Ethics Committee dated 22.04.2024 with decision number 04.701. The research was conducted in accordance with the ethical principles of the Declaration of Helsinki (2013 revision). The data collection process was completed with a total of 415 participants between July 15 - September 15, 2024.\u003c/p\u003e \u003cp\u003eThe study population consisted of individuals aged 65 and over residing in the relevant nursing homes.\u003c/p\u003e \u003cp\u003eThe inclusion criteria for the study were defined as being 65 years of age or older, residing in a nursing home for at least one month, being able to communicate verbally, and being willing to participate in the study. The exclusion criteria were determined as having a consciousness disorder or severe cognitive impairment, acute infection or severe systemic disease, and anatomical abnormality preventing swallowing assessment. A total of 415 individuals meeting these specified criteria were included in the study.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Collection Tools\u003c/h2\u003e \u003cp\u003eData were collected through face-to-face interviews conducted by physicians participating in the research team. The interviews were conducted in quiet and appropriate environments within the nursing homes, with each interview lasting approximately 15\u0026ndash;20 minutes. This approach constitutes one of the study's strengths, enhancing data reliability.\u003c/p\u003e \u003cp\u003e \u003cb\u003e1) Sociodemographic and Clinical Information Form\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWith the form prepared by researchers based on literature, participants' age group, gender, duration of nursing home stay, denture use, smoking, and history of aspiration pneumonia were queried. Aspiration pneumonia history within the last 3 years was obtained retrospectively from the patients' medical and nursing home records.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2) Turkish Eating Assessment Tool (T-EAT-10)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Turkish Eating Assessment Tool [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] (T-EAT-10) is a 10-item instrument developed by Demir et al. to evaluate the severity of dysphagia symptoms and the individual's self-perceived dysphagia risk status over Eating Assessment Tool [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] in Turkish language. A score of 3 or above on the scale is considered abnormal. The scale comprises 10 questions through which patients self-report their swallowing problems. A 5-point Likert-type scoring system ranging from 0 (No problem) to 4 (Severe problem) is employed for each item. The minimum obtainable score from the scale is 0, while the maximum is 40. The validity and reliability of the Turkish version of the scale were established by Demir and colleagues [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. T-EAT-10 has been demonstrated to be a practical and reliable tool that can be completed in approximately 2 minutes. A score of 3 or higher (\u0026ge;\u0026thinsp;3) obtained from the scale is considered abnormal and indicates that the individual is at risk for dysphagia. An elevation in the score signifies an increase in the severity of swallowing difficulty symptoms [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003e3) Nutritional Form for the Elderly (NUFFE-TR)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe original version of this scale, developed to assess the nutritional status of elderly individuals, was introduced to the literature in Swedish (Nutritional Form for the Elderly - NUFFE). The scale is a malnutrition screening tool that does not require anthropometric measurements or biochemical parameters and can be readily implemented in clinical nursing care [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The original scale comprises 15 items encompassing nutritional history, dietary assessment, and general evaluation. The items employ an ordinal scale structure with three options specific to each question (0, 1, 2) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The Turkish validity and reliability study of the scale was conducted by Kamarlı Altun and colleagues. Following the analyses, three items (N6, N8, N14) were removed from the scale due to low factor loadings, resulting in a 12-item structure for NUFFE-TR [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The minimum score obtainable from the 12-item Turkish version is 0, and the maximum score is 24. In the scale, the most favorable option is scored as 0, the intermediate option as 1, and the unfavorable option as 2 points. As the total score obtained from the scale increases, the individual's malnutrition risk and nutritional inadequacy level escalate [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using IBM SPSS Statistics, Version 27.0 (IBM Corp., Armonk, NY, USA) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Categorical data were presented as frequency (n) and percentage (%), while continuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and median (min-max). The normality assumption was tested using the Kolmogorov-Smirnov test. Since continuous variables did not show normal distribution, non-parametric tests were used. Mann-Whitney U test was used for comparisons between two independent groups. A binary logistic regression model was established to determine independent predictors of dysphagia risk. Model fit was evaluated with the Hosmer-Lemeshow test. Statistical significance level was accepted as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Roc Analysis was calculated with MedCalc\u0026reg; Statistical Software version 23.4.4 (MedCalc Software Ltd, Ostend, Belgium) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eSociodemographic and Clinical Characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 415 nursing home residents aged 65 years and older were included in the study. Of the participants, 227 (54.7%) were female and 188 (45.3%) were male. The majority of residents fell into the 75\u0026ndash;84 age group (n\u0026thinsp;=\u0026thinsp;194, 46.7%), followed by the 65\u0026ndash;74 group (n\u0026thinsp;=\u0026thinsp;142, 34.2%) and those aged 85 years and older (n\u0026thinsp;=\u0026thinsp;79, 19.0%). Regarding duration of nursing home stay, 166 participants (40.0%) had resided for less than one year, 211 (50.8%) for 1\u0026ndash;5 years, and 38 (9.2%) for more than five years. Denture use was reported by 202 participants (48.7%), and 103 (24.8%) were current or former smokers.\u003c/p\u003e\n \u003cp\u003eIn terms of clinical comorbidities, hypertension was the most prevalent condition, present in 283 participants (68.2%), followed by diabetes mellitus in 139 (33.5%), heart disease in 178 (42.9%), and a history of stroke in 53 participants (12.8%). The majority of participants had a body mass index (BMI) in the normal-to-overweight range; 193 (46.5%) had a BMI of 18.5\u0026ndash;24.9 kg/m\u0026sup2;, 182 (43.9%) had a BMI of 25.0\u0026ndash;29.9 kg/m\u0026sup2;, and 31 (7.5%) had a BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;. Only 9 participants (2.2%) were underweight (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;). The overall median BMI was 25.35 kg/m\u0026sup2; (interquartile range [IQR]: 23.44\u0026ndash;26.83).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003ePrevalence and Characteristics of Aspiration Pneumonia\u003c/h3\u003e\n\u003cp\u003eResidents with a history of aspiration pneumonia were significantly older than those without (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Among the 42 residents with aspiration pneumonia, 5 (11.9%) were in the 65\u0026ndash;74 age group, 20 (47.6%) were in the 75\u0026ndash;84 age group, and 17 (40.5%) were aged 85 years or older. By contrast, among the 373 residents without aspiration pneumonia, the majority fell into the 65\u0026ndash;74 (36.7%) and 75\u0026ndash;84 (46.6%) age groups, with only 16.6% aged 85 years or older. When examined from the perspective of each age group\u0026apos;s internal distribution, aspiration pneumonia was present in 3.5% of the 65\u0026ndash;74 group (5/142), 10.3% of the 75\u0026ndash;84 group (20/194), and 21.5% of those aged 85 years and older (17/79), indicating a progressive increase in aspiration pneumonia prevalence with advancing age. Duration of nursing home stay was also significantly associated with aspiration pneumonia (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); among residents who had stayed for more than five years, 28.6% had a history of aspiration pneumonia, compared with 14.3% among those with a stay of less than one year.\u003c/p\u003e\n\u003cp\u003eDenture use was significantly more common among residents with aspiration pneumonia (66.7% vs. 33.3% without dentures; p\u0026thinsp;=\u0026thinsp;0.014). History of stroke was present in 26.2% of those with aspiration pneumonia compared with 11.3% of those without (p\u0026thinsp;=\u0026thinsp;0.006). Heart disease was significantly more prevalent in the aspiration pneumonia group (69.0% vs. 39.9%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as was diabetes mellitus (47.6% vs. 31.9%; p\u0026thinsp;=\u0026thinsp;0.041). Gender, smoking status, hypertension, and COPD were not significantly associated with aspiration pneumonia (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all). Complete sociodemographic and clinical comparisons are presented in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSociodemographic and Clinical Characteristics According to History of Aspiration Pneumonia\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;415)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eNo aspiration pneumonia (n\u0026thinsp;=\u0026thinsp;373)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eAspiration pneumonia (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eGender, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e227 (54.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e209 (56.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e18 (42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e188 (45.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e164 (44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e24 (57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAge group, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e65\u0026ndash;74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e142 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e137 (36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e75\u0026ndash;84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e194 (46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e174 (46.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e20 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e79 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e62 (16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e17 (40.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDuration of nursing home stay, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e166 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e160 (42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e6 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e1\u0026ndash;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e211 (50.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e187 (50.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e24 (57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e38 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e26 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e12 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e9 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e8 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\n \u003cp\u003eN/C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e18.5\u0026ndash;24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e193 (46.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e170 (45.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e23 (54.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e25.0-29.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e182 (43.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e164 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e18 (42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e31 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e31 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDenture use, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e213 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e199 (53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e14 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e202 (48.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e174 (46.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e28 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSmoking, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e312 (75.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e277 (74.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e35 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e103 (24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e96 (25.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e7 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHypertension, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e132 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e124 (33.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e8 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e283 (68.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e249 (66.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e34 (81.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e373 (89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e338 (90.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e35 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e42 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e35 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e7 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDiabetes mellitus, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e276 (66.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e254 (68.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e22 (52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e139 (33.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e119 (31.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e20 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHistory of stroke, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e362 (87.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e331 (88.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e31 (73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e53 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e42 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e11 (26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHeart disease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e237 (57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e224 (60.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e13 (31.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e178 (42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e149 (39.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e29 (69.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cem\u003eValues are presented as number (percentage). Column percentages are shown.Comparisons were performed using the chi-square test or Fisher\u0026rsquo;s exact test, as appropriate.p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. N/C: Not calculated due to one of the cells was zero. COPD: Chronic obstructive pulmonary disease\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eComparison of T-EAT-10, NUFFE-TR, and BMI Scores by Aspiration Pneumonia Status\u003c/h2\u003e\n \u003cp\u003eBoth T-EAT-10 and NUFFE-TR scores differed significantly between residents with and without aspiration pneumonia (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The median T-EAT-10 score in participants with aspiration pneumonia was 24.0 (IQR: 13.8\u0026ndash;30.3), compared with 4.0 (IQR: 0.0\u0026ndash;10.0) in those without aspiration pneumonia (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, the median NUFFE-TR total score was significantly higher in participants with aspiration pneumonia (median: 11.0, IQR: 7.0\u0026ndash;18.0) than in those without (median: 3.0, IQR: 2.0\u0026ndash;6.0) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). BMI was also significantly lower in residents with aspiration pneumonia (median: 24.33 kg/m\u0026sup2;, IQR: 21.88\u0026ndash;26.35) compared with those without (median: 25.35 kg/m\u0026sup2;, IQR: 23.44\u0026ndash;26.83) (p\u0026thinsp;=\u0026thinsp;0.044).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of NUFFE-TR, T-EAT-10, and BMI According to History of Aspiration Pneumonia\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eNo aspiration pneumonia\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eAspiration pneumonia\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003ep\u0026dagger;\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\n \u003cp\u003eMedian (25.-75. percentile)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNUFFE-TR total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3.0 (2.0\u0026ndash;6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3.0 (2.0\u0026ndash;6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e11.0 (7.0\u0026ndash;18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eT-EAT-10 total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e4.0 (0.0\u0026ndash;10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e4.0 (0.0\u0026ndash;10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e24.0 (13.8\u0026ndash;30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e25.35 (23.44\u0026ndash;26.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e25.35 (23.44\u0026ndash;26.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e24.33 (21.88\u0026ndash;26.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eValues are presented as median (25th\u0026ndash;75th percentile).\u003c/p\u003e\n \u003cp\u003e\u0026dagger;Comparisons were performed using the Mann\u0026ndash;Whitney U test.\u003c/p\u003e\n \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eLogistic Regression Analysis: Independent Predictors of Aspiration Pneumonia\u003c/h3\u003e\n\u003cp\u003eBinary logistic regression analysis was conducted to identify independent predictors of aspiration pneumonia, with T-EAT-10 total score, NUFFE-TR total score, age group, duration of nursing home stay, denture use, history of stroke, heart disease, and diabetes mellitus entered as covariates (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The overall model was statistically significant (\u0026chi;\u0026sup2;(10)\u0026thinsp;=\u0026thinsp;104.958, p \u0026lt; .001) and demonstrated good fit as confirmed by the Hosmer-Lemeshow test (\u0026chi;\u0026sup2;(8)\u0026thinsp;=\u0026thinsp;5.151, p = .741). The model correctly classified 91.8% of cases overall (sensitivity for aspiration pneumonia: 42.9%; specificity for no aspiration pneumonia: 97.3%), with a Nagelkerke R\u0026sup2; of 0.465.\u003c/p\u003e\n\u003cp\u003eIn the multivariate model, T-EAT-10 total score emerged as the only statistically significant independent predictor of aspiration pneumonia (B\u0026thinsp;=\u0026thinsp;0.118, OR\u0026thinsp;=\u0026thinsp;1.125, 95% CI [1.069\u0026ndash;1.184], p \u0026lt; .001), indicating that each one-point increase in the T-EAT-10 score was associated with a 12.5% increase in the odds of aspiration pneumonia. NUFFE-TR total score did not reach statistical significance as an independent predictor in the multivariate model (B\u0026thinsp;=\u0026thinsp;0.082, OR\u0026thinsp;=\u0026thinsp;1.085, 95% CI [0.989\u0026ndash;1.190], p = .079), although its univariate association with aspiration pneumonia was highly significant (p \u0026lt; .001). None of the other covariates \u0026mdash; including age group, duration of nursing home stay, denture use, history of stroke, heart disease, or diabetes mellitus \u0026mdash; were independently associated with aspiration pneumonia after adjustment.\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic Regression Analysis Predicting Aspiration Pneumonia\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eWald\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNUFFE total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.989\u0026ndash;1.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEAT-10 total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e19.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e1.069\u0026ndash;1.184\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\n \u003cp\u003eAge group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e75\u0026ndash;84 (ref: 65\u0026ndash;74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.548\u0026ndash;5.729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;85 (ref: 65\u0026ndash;74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e2.415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.666\u0026ndash;8.753\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\n \u003cp\u003eLength of stay in nursing home\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e1\u0026ndash;5 years (ref: \u0026lt; 1 year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.589\u0026ndash;5.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;5 years (ref: \u0026lt; 1 year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e2.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e2.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.681\u0026ndash;11.381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDenture use (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e2.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.781\u0026ndash;4.897\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eStroke history (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026minus;.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.274\u0026ndash;2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCardiac disease (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.432\u0026ndash;2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDiabetes (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.485\u0026ndash;2.585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026minus;5.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e58.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\u003cem\u003eNote.\u003c/em\u003e n\u0026thinsp;=\u0026thinsp;415. Dependent variable: Aspiration pneumonia (0\u0026thinsp;=\u0026thinsp;No, 1\u0026thinsp;=\u0026thinsp;Yes). OR\u0026thinsp;=\u0026thinsp;Odds Ratio; CI\u0026thinsp;=\u0026thinsp;Confidence Interval; NUFFE-TR\u0026thinsp;=\u0026thinsp;Nutritional Form for the Elderly-Turkish; EAT-10-TR\u0026thinsp;=\u0026thinsp;Eating Assessment Tool-10-TR. Reference categories are indicated in parentheses.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Omnibus model test: \u0026chi;\u0026sup2;(10)\u0026thinsp;=\u0026thinsp;104.958, p \u0026lt; .001.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Model summary: \u0026minus;2LL\u0026thinsp;=\u0026thinsp;167.052; Cox \u0026amp; Snell R\u0026sup2; = .223; Nagelkerke R\u0026sup2; = .465.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Hosmer and Lemeshow goodness-of-fit test: \u0026chi;\u0026sup2;(8)\u0026thinsp;=\u0026thinsp;5.151, p = .741.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ed\u003c/sup\u003e Classification accuracy: Overall 91.8% (No: 97.3%; Yes: 42.9%). Cut value = .500.\u003c/p\u003e\n\u003ch3\u003eDiagnostic Accuracy of T-EAT-10 for Aspiration Pneumonia: ROC Analysis\u003c/h3\u003e\n\u003cp\u003eROC curve analysis was performed to evaluate the diagnostic accuracy of the T-EAT-10 for identifying aspiration pneumonia (Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The area under the ROC curve (AUC) was 0.886 (SE\u0026thinsp;=\u0026thinsp;0.028; 95% CI [0.851, 0.915]; z\u0026thinsp;=\u0026thinsp;13.949; p \u0026lt; .0001), indicating excellent discriminative ability of the T-EAT-10 for aspiration pneumonia.\u003c/p\u003e\n\u003cp\u003eThe optimal cut-off value was determined using the Youden index (J\u0026thinsp;=\u0026thinsp;Sensitivity\u0026thinsp;+\u0026thinsp;Specificity\u0026thinsp;\u0026minus;\u0026thinsp;1). The criterion T-EAT-10 score\u0026thinsp;\u0026gt;\u0026thinsp;12 maximized the Youden index (J\u0026thinsp;=\u0026thinsp;0.6406), yielding a sensitivity of 80.95% (95% CI [65.9\u0026ndash;91.4]), specificity of 83.11% (95% CI [78.9\u0026ndash;86.8]), positive likelihood ratio (+\u0026thinsp;LR) of 4.79, and negative likelihood ratio (\u0026minus;\u0026thinsp;LR) of 0.23 (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). At the conventional clinical cut-off of T-EAT-10\u0026thinsp;\u0026ge;\u0026thinsp;3 (any abnormal swallowing), sensitivity was high at 95.24% but specificity was low at 46.92%, reflecting the screening-oriented nature of this threshold. As the cut-off was raised, specificity increased progressively while sensitivity declined, with a T-EAT-10\u0026thinsp;\u0026gt;\u0026thinsp;21 achieving a specificity of 93.30% at the cost of reduced sensitivity (64.29%). The ROC coordinates across all tested criterion values are presented in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eROC Curve Coordinates and Diagnostic Accuracy of EAT-10 for Aspiration Pneumonia\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eCriterion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\n \u003cp\u003eSensitivity (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003eSpecificity (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003e+LR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003e\u0026minus;LR\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e97.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e87.4\u0026ndash;99.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e33.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e29.0\u0026ndash;38.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.35\u0026ndash;1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.010\u0026ndash;0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e95.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e83.8\u0026ndash;99.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e46.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e41.8\u0026ndash;52.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1.60\u0026ndash;2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.026\u0026ndash;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e90.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e77.4\u0026ndash;97.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e64.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e59.0\u0026ndash;68.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e2.13\u0026ndash;2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.058\u0026ndash;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e90.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e77.4\u0026ndash;97.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e72.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e68.1\u0026ndash;77.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e2.75\u0026ndash;4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.051\u0026ndash;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;\u0026thinsp;12\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e\u003cstrong\u003e80.95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e65.9\u0026ndash;91.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cstrong\u003e83.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e78.9\u0026ndash;86.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.79\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.66\u0026ndash;6.27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.230\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.12\u0026ndash;0.43\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e73.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e58.0\u0026ndash;86.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e85.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e81.8\u0026ndash;89.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e5.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e3.82\u0026ndash;7.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.18\u0026ndash;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e69.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e52.9\u0026ndash;82.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e88.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e84.5\u0026ndash;91.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e5.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e4.15\u0026ndash;8.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.22\u0026ndash;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e64.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e48.0\u0026ndash;78.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e93.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e90.3\u0026ndash;95.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e9.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e6.17\u0026ndash;14.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.25\u0026ndash;0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e47.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e32.0\u0026ndash;63.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e96.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e94.1\u0026ndash;98.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e13.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e7.34\u0026ndash;25.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.41\u0026ndash;0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e35.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e21.6\u0026ndash;52.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e97.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e95.1\u0026ndash;98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e13.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e6.40\u0026ndash;27.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.53\u0026ndash;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e14.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5.4\u0026ndash;28.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e99.0\u0026ndash;100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.76\u0026ndash;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003cem\u003eNote.\u003c/em\u003e Variable: EAT-10 total score. Outcome: Aspiration pneumonia (positive: n\u0026thinsp;=\u0026thinsp;42; negative: n\u0026thinsp;=\u0026thinsp;373; N\u0026thinsp;=\u0026thinsp;415). +LR\u0026thinsp;=\u0026thinsp;positive likelihood ratio; \u0026minus;LR\u0026thinsp;=\u0026thinsp;negative likelihood ratio; CI\u0026thinsp;=\u0026thinsp;confidence interval. Only selected criterion values are shown for clarity.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Area under the ROC curve (AUC)\u0026thinsp;=\u0026thinsp;0.886 (SE\u0026thinsp;=\u0026thinsp;0.028; 95% CI [0.851, 0.915]; z\u0026thinsp;=\u0026thinsp;13.949; p \u0026lt; .0001). AUC standard error computed using the DeLong et al. (1988) method; 95% CI computed using the binomial exact method.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Youden index J\u0026thinsp;=\u0026thinsp;0.6406. The optimal cut-off criterion (\u0026gt;\u0026thinsp;12) maximises the sum of sensitivity and specificity (J\u0026thinsp;=\u0026thinsp;Sensitivity\u0026thinsp;+\u0026thinsp;Specificity\u0026thinsp;\u0026minus;\u0026thinsp;1).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e Optimal cut-off point selected by the Youden index (highlighted row): criterion\u0026thinsp;\u0026gt;\u0026thinsp;12, Sensitivity\u0026thinsp;=\u0026thinsp;80.95% (95% CI [65.9, 91.4]), Specificity\u0026thinsp;=\u0026thinsp;83.11% (95% CI [78.9, 86.8]), +LR\u0026thinsp;=\u0026thinsp;4.79, \u0026minus;LR\u0026thinsp;=\u0026thinsp;0.23.\u003c/p\u003e\n\u003cp\u003eThe prevalence of dysphagia risk (T-EAT-10\u0026thinsp;\u0026ge;\u0026thinsp;3) in the total study population is presented in Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, illustrating the distribution of dysphagia risk screening results across participants.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis cross-sectional study examined the predictive value of the T-EAT-10 and NUFFE-TR for aspiration pneumonia among 415 nursing home residents aged 65 years and older in Ankara, Turkey. The principal findings were that T-EAT-10 emerged as the only independent predictor of aspiration pneumonia in multivariate analysis, demonstrating excellent discriminative ability (AUC\u0026thinsp;=\u0026thinsp;0.886), while NUFFE-TR, although strongly associated with aspiration pneumonia in univariate analyses, did not retain independent significance after adjustment. An optimal cut-off of T-EAT-10\u0026thinsp;\u0026gt;\u0026thinsp;12 was identified as the most diagnostically accurate threshold for aspiration pneumonia detection in this population.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Aspiration Pneumonia\u003c/h2\u003e \u003cp\u003eThe prevalence of aspiration pneumonia in the present study was 10.1%, a figure that is broadly consistent with data from large nursing home cohorts. Langmore et al. reported a 3% prevalence in a cross-sectional analysis of over 100,000 U.S. nursing home residents using administrative data, though this figure likely reflects underreporting inherent to retrospective record review rather than active clinical screening [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The higher prevalence observed in our study may reflect the systematic physician-administered face-to-face data collection methodology and the older, comorbidity-rich profile of our sample. Indeed, Sarabia-Cobo et al. reported that among institutionalized elderly in Spanish nursing homes, those with oropharyngeal dysphagia had markedly higher rates of pneumonia and mortality [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], further supporting the premise that active screening yields higher detection than passive records-based ascertainment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eT-EAT-10 as an Independent Predictor of Aspiration Pneumonia\u003c/h2\u003e \u003cp\u003eThe finding that T-EAT-10 total score was the only statistically significant independent predictor of aspiration pneumonia (OR\u0026thinsp;=\u0026thinsp;1.125 per one-point increase, 95% CI [1.069\u0026ndash;1.184]) underscores the clinical utility of this brief self-report instrument in the nursing home setting. A systematic review and meta-analysis by Zhang et al. confirmed that the EAT-10 demonstrates good overall diagnostic performance for dysphagia screening (AUC 0.873\u0026ndash;0.903 depending on cut-off), and concluded that a threshold of \u0026ge;\u0026thinsp;3 offers the best balance for general dysphagia screening [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Crucially, the present study extends this evidence by demonstrating that the T-EAT-10 predicts not just dysphagia symptom risk but the clinically critical outcome of aspiration pneumonia, and that doing so requires a substantially higher cut-off than the conventional\u0026thinsp;\u0026ge;\u0026thinsp;3 threshold.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eOptimal Cut-Off Value: T-EAT-10\u0026thinsp;\u0026gt;\u0026thinsp;12\u003c/h2\u003e \u003cp\u003eA key contribution of this study is the identification of T-EAT-10\u0026thinsp;\u0026gt;\u0026thinsp;12 as the optimal threshold for aspiration pneumonia prediction (sensitivity 80.95%, specificity 83.11%, +LR 4.79). This is considerably higher than the standard dysphagia screening cut-off of \u0026ge;\u0026thinsp;3. This divergence is clinically meaningful: the \u0026ge;\u0026thinsp;3 threshold was designed to capture any degree of perceived swallowing difficulty, whereas aspiration pneumonia represents a more severe clinical endpoint requiring a higher symptom burden to predict reliably. In a study of adults with stable COPD, Regan et al. similarly found that an EAT-10 cut-off of \u0026gt;\u0026thinsp;9 optimally predicted aspiration confirmed by fiberoptic endoscopic evaluation (AUC\u0026thinsp;=\u0026thinsp;0.88; sensitivity 91.67%, specificity 77.78%) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] suggesting that the optimal threshold for predicting aspiration \u0026mdash; as opposed to dysphagia symptomatology \u0026mdash; may vary by population and clinical context. Our finding of a higher optimal cut-off (\u0026gt;\u0026thinsp;12) may reflect the mixed etiology and older age profile of nursing home residents compared with the COPD clinic population studied by Regan et al. And also the higher cut-off value (\u0026gt;\u0026thinsp;12) of the T-EAT-10 for predicting aspiration pneumonia in our study may be attributed to the baseline physiological changes in the swallowing mechanism of older adults, known as presbyphagia. Since mild swallowing difficulties may be a natural part of aging rather than a strictly pathological state, a higher threshold may be clinically more relevant to identify true aspiration risk in institutionalized populations [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe Role of NUFFE-TR and the Dysphagia\u0026ndash;Malnutrition Relationship\u003c/h2\u003e \u003cp\u003eAlthough NUFFE-TR did not independently predict aspiration pneumonia in the multivariate model (p = .079), its strong univariate association (p \u0026lt; .001) and near-significant trend in the adjusted model suggest that malnutrition risk contributes meaningfully to aspiration pneumonia burden, likely through pathways partially mediated by dysphagia severity. This interpretation is consistent with the conceptual framework proposed by Baijens et al. in the European Society for Swallowing Disorders white paper, which recognizes that impaired swallowing efficacy leads to malnutrition, while malnutrition in turn impairs respiratory muscle strength and mucosal immune defenses \u0026mdash; creating a bidirectional relationship that amplifies pneumonia risk [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The finding that NUFFE-TR's independent effect was attenuated by T-EAT-10 in the multivariate model may indicate substantial collinearity between the two instruments, since residents with more severe dysphagia are inherently at greater nutritional risk. These results are consistent with the nationally representative Dutch study by Huppertz et al., which found that nursing home residents with oropharyngeal dysphagia symptoms were 1.5 times more likely to be malnourished than those without \u0026mdash; confirming the tight epidemiological coupling between these two geriatric syndromes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. More recently, Engberg et al. similarly reported that approximately one-third of nursing home residents in Sweden exhibited dysphagia, and that the condition was frequently unrecognized by both patients and caregivers, underlining the value of systematic screening [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eClinical and Comorbidity-Related Risk Factors\u003c/h2\u003e \u003cp\u003eThe progressive increase in aspiration pneumonia prevalence with advancing age \u0026mdash; from 3.5% in the 65\u0026ndash;74 age group to 21.5% in those aged 85 and older \u0026mdash; aligns with well-established evidence that aging is associated with sarcopenic changes in the swallowing musculature, reduced laryngeal elevation, and impaired pharyngeal clearance. De Sire et al. comprehensively reviewed these overlapping pathophysiological mechanisms in their discussion of sarcopenic dysphagia, underscoring that the combined burden of sarcopenia, dysphagia, and poor oral health creates a self-reinforcing cycle of functional decline in elderly individuals [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In the present study, stroke history and heart disease were significantly associated with aspiration pneumonia in univariate analysis, consistent with findings by Taylor et al., who demonstrated that patients with aspiration risk factors \u0026mdash; including neurological disorders and dysphagia \u0026mdash; had substantially higher long-term mortality and rehospitalization rates in a large UK pneumonia cohort [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These comorbidities did not retain statistical significance in the multivariate model after adjustment for T-EAT-10, suggesting that their effect on aspiration pneumonia may be substantially mediated through dysphagia severity, as captured by the T-EAT-10 score.\u003c/p\u003e \u003cp\u003eThe significant association between denture use and aspiration pneumonia is a noteworthy finding that merits clinical attention. Takeuchi et al. demonstrated in a prospective cohort of Japanese nursing home residents that denture wearing moderated the relationship between aspiration risk and incident pneumonia \u0026mdash; while dentures may facilitate oral bolus control, they also provide a substrate for oral bacterial colonization if oral hygiene is suboptimal [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Similarly, Chen et al., in their cross-sectional study of 775 nursing home residents in China using the EAT-10, identified history of aspiration, heart attack, and pneumonia as the strongest risk factors for dysphagia risk, with heart disease carrying an OR of 3.804 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] \u0026mdash; findings that parallel our own observations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study has several notable strengths. The large, population-based sample drawn from a diversity of nursing home types (private, public, and municipal) in Ankara province enhances the representativeness of findings. Data were collected through structured face-to-face interviews by physicians, minimizing misclassification bias. The use of ROC Analysis to derive an evidence-based cut-off value for aspiration pneumonia prediction adds direct clinical applicability. To our knowledge, this is the first study to evaluate T-EAT-10 and NUFFE-TR concurrently as predictors of aspiration pneumonia in Turkish nursing home residents.\u003c/p\u003e \u003cp\u003eSeveral limitations must be acknowledged. The cross-sectional design precludes causal inference; aspiration pneumonia history was ascertained from medical records rather than confirmed by clinical or radiological evaluation at the time of assessment, which may introduce both ascertainment bias. The retrospective ascertainment of aspiration pneumonia from records may have led to underreporting, particularly for mild or atypically presenting episodes. Furthermore, objective dysphagia assessment using instrumental methods such as videofluoroscopic swallowing study or fiberoptic endoscopic evaluation was not performed, meaning that T-EAT-10 scores reflect self-perceived swallowing symptoms rather than physiologically confirmed aspiration. As a scoping review by Chen et al. noted, the nursing home setting remains resource-constrained with respect to speech-language pathology access, particularly in developing-country contexts [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and our findings should be interpreted within this pragmatic screening context. Finally, cognitive status was an exclusion criterion, meaning that residents with cognitive impairment \u0026mdash; who are at particularly high risk for dysphagia and aspiration \u0026mdash; were not included, potentially limiting the generalizability of findings to this vulnerable subgroup.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe T-EAT-10 is a practical, brief, and highly discriminating screening tool for aspiration pneumonia risk in nursing home residents aged 65 years and older. A cut-off score of \u0026gt;\u0026thinsp;12 maximizes diagnostic accuracy in this population, providing a clinically actionable threshold that is distinct from \u0026mdash; and substantially higher than \u0026mdash; the conventional dysphagia screening cut-off of \u0026ge;\u0026thinsp;3. Routine T-EAT-10 screening, combined with nutritional risk assessment using NUFFE-TR, should be integrated into standard care protocols for institutionalized elderly individuals. Future prospective studies incorporating instrumental swallowing assessment and longer follow-up periods are warranted to confirm the independent predictive value of these instruments and to evaluate the impact of screening-based interventions on aspiration pneumonia incidence and related outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e Ethics approval for this study was obtained from the Ankara Yıldırım Beyazıt University Health Sciences Ethics Committee (Date: 22.04.2024, Decision Number: 04.701). The research was conducted in accordance with the ethical principles of the Declaration of Helsinki (2013 revision). Informed consent was obtained from all participants or their legal representatives before their inclusion in the study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study\u0026rsquo;s conception and design. Material preparation, data collection, and analysis were performed by all authors. All authors participated in drafting the manuscript and critically revising it for important intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank all the nursing home residents and staff for their participation and cooperation in this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eClave P, Rofes L, Carrion S, Ortega O, Cabre M, Serra-Prat M, Arreola V. Pathophysiology, relevance and natural history of oropharyngeal dysphagia among older people. Nestle Nutr Inst Workshop Ser. 2012;72:57\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuppertz VAL, Halfens RJG, van Helvoort A, de Groot L, Baijens LWJ, Schols J. Association between Oropharyngeal Dysphagia and Malnutrition in Dutch Nursing Home Residents: Results of the National Prevalence Measurement of Quality of Care. J Nutr Health Aging. 2018;22(10):1246\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBelafsky PC, Mouadeb DA, Rees CJ, Pryor JC, Postma GN, Allen J, Leonard RJ. Validity and reliability of the Eating Assessment Tool (EAT-10). Ann Otol Rhinol Laryngol. 2008;117(12):919\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemir N, Serel Arslan S, Inal O, Karaduman AA. Reliability and Validity of the Turkish Eating Assessment Tool (T-EAT-10). Dysphagia. 2016;31(5):644\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026ouml;derhamn U, S\u0026ouml;derhamn O. Reliability and validity of the nutritional form for the elderly (NUFFE). J Adv Nurs. 2002;37(1):28\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026ouml;derhamn U, Flateland S, Jessen L, S\u0026ouml;derhamn O. Norwegian version of the Nutritional Form for the Elderly: sufficient psychometric properties for performing institutional screening of elderly patients. Nutr Res. 2009;29(11):761\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamarli Altun H, Suna G, \u0026Ccedil;ift\u0026ccedil;i S. Turkish Adaptation of Nutritional Form for the Elderly: A Methodological Study. Turkiye Klinikleri J Health Sci. 2022;7(4):1135\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIBM Corp. IBM SPSS Statistics for Windows. In., 27.0 edn. Armonk, NY; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMedCalc Software Ltd. MedCalc Statistical Software. In., 23.4.4 edn. Ostend, Belgium: MedCalc Software Ltd,; 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLangmore SE, Skarupski KA, Park PS, Fries BE. Predictors of aspiration pneumonia in nursing home residents. Dysphagia. 2002;17(4):298\u0026ndash;307.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarabia-Cobo CM, P\u0026eacute;rez V, de Lorena P, Dom\u0026iacute;nguez E, Hermosilla C, Nu\u0026ntilde;ez MJ, Vigueiro M, Rodr\u0026iacute;guez L. The incidence and prognostic implications of dysphagia in elderly patients institutionalized: A multicenter study in Spain. Appl Nurs Res. 2016;30:e6\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang PP, Yuan Y, Lu DZ, Li TT, Zhang H, Wang HY, Wang XW. Diagnostic Accuracy of the Eating Assessment Tool-10 (EAT-10) in Screening Dysphagia: A Systematic Review and Meta-Analysis. Dysphagia. 2023;38(1):145\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRegan J, Lawson S, De Aguiar V. The Eating Assessment Tool-10 Predicts Aspiration in Adults with Stable Chronic Obstructive Pulmonary Disease. Dysphagia. 2017;32(5):714\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLabeit B, Lapa S, Lueg G, Joebges R, Hofacker J, Muhle P, Suntrup-Krueger S, Werner CJ, Schreiber S, Wirth R, et al. Oropharyngeal dysphagia: a narrative review towards an integrated neurogeriatric perspective. Lancet Healthy Longev. 2025;6(12):100794.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNamasivayam-MacDonald AM, Riquelme LF. Presbyphagia to Dysphagia: Multiple Perspectives and Strategies for Quality Care of Older Adults. Semin Speech Lang. 2019;40(3):227\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaijens LW, Clave P, Cras P, Ekberg O, Forster A, Kolb GF, Leners JC, Masiero S, Mateos-Nozal J, Ortega O, et al. European Society for Swallowing Disorders - European Union Geriatric Medicine Society white paper: oropharyngeal dysphagia as a geriatric syndrome. Clin Interv Aging. 2016;11:1403\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEngberg AV, R\u0026aring;ngevall G, Eriksson K, Tuomi L. Prevalence of Dysphagia and Risk of Malnutrition in Elderly Living in Nursing Homes. Dysphagia. 2024;39(6):1065\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Sire A, Ferrillo M, Lippi L, Agostini F, de Sire R, Ferrara PE, Raguso G, Riso S, Roccuzzo A, Ronconi G et al. Sarcopenic Dysphagia, Malnutrition, and Oral Frailty in Elderly: A Comprehensive Review. Nutrients 2022, 14(5).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor JK, Fleming GB, Singanayagam A, Hill AT, Chalmers JD. Risk factors for aspiration in community-acquired pneumonia: analysis of a hospitalized UK cohort. Am J Med. 2013;126(11):995\u0026ndash;1001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakeuchi K, Izumi M, Furuta M, Takeshita T, Shibata Y, Kageyama S, Okabe Y, Akifusa S, Ganaha S, Yamashita Y. Denture Wearing Moderates the Association between Aspiration Risk and Incident Pneumonia in Older Nursing Home Residents: A Prospective Cohort Study. Int J Environ Res Public Health 2019, 16(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen S, Cui Y, Ding Y, Sun C, Xing Y, Zhou R, Liu G. Prevalence and risk factors of dysphagia among nursing home residents in eastern China: a cross-sectional study. BMC Geriatr. 2020;20(1):352.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen S, Kent B, Cui Y. Interventions to prevent aspiration in older adults with dysphagia living in nursing homes: a scoping review. BMC Geriatr. 2021;21(1):429.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Oropharyngeal dysphagia, Malnutrition, Aspiration pneumonia, Nursing home, T-EAT-10, NUFFE-TR","lastPublishedDoi":"10.21203/rs.3.rs-9009756/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9009756/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Aging is associated with physiological changes that increase vulnerability to malnutrition and oropharyngeal dysphagia, both of which are prevalent in nursing homes and major risk factors for aspiration pneumonia. This study aimed to evaluate the predictive value of the Turkish Eating Assessment Tool (T-EAT-10) and the Nutritional Form for the Elderly (NUFFE-TR) for aspiration pneumonia in nursing home residents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This cross-sectional study included 415 residents aged 65 and older in Ankara, Turkey. Data were collected via face-to-face interviews using a sociodemographic form, the 10-item T-EAT-10 for dysphagia screening, and the 12-item NUFFE-TR for malnutrition risk assessment. Aspiration pneumonia history was obtained from medical records. Logistic regression and Receiver Operating Characteristic (ROC) analyses were performed to identify independent predictors and determine optimal diagnostic thresholds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The prevalence of aspiration pneumonia was 10.1%. Residents with aspiration pneumonia had significantly higher median T-EAT-10 (24.0 vs. 4.0; p \u0026lt; 0.001) and NUFFE-TR (11.0 vs. 3.0; p \u0026lt; 0.001) scores. In multivariate logistic regression, the T-EAT-10 total score emerged as the only independent predictor of aspiration pneumonia (OR = 1.125, 95% CI [1.069–1.184], p \u0026lt; 0.001). ROC analysis showed excellent discriminative ability for the T-EAT-10 (AUC = 0.886, p \u0026lt; 0.0001). The optimal cut-off value for predicting aspiration pneumonia was T-EAT-10 \u0026gt; 12 (sensitivity: 80.95%, specificity: 83.11%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e The T-EAT-10 is a practical and highly effective screening tool for identifying aspiration pneumonia risk in institutionalized elderly populations. A clinical threshold of \u0026gt;12 is recommended for identifying high-risk residents, which is substantially higher than the standard dysphagia screening cut-off. Systematic screening using T-EAT-10 and NUFFE-TR should be integrated into routine geriatric care in nursing homes to improve preventive strategies.\u003c/p\u003e","manuscriptTitle":"Predictive Value of T-Eat-10 and Nuffe-tr for Aspiration Pneumonia in Nursing Home Residents: A Cross-sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-17 17:19:49","doi":"10.21203/rs.3.rs-9009756/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-18T12:24:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308369657621371933086006328024105021325","date":"2026-05-17T15:59:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T13:10:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178550129907820793910432461694438008385","date":"2026-04-10T04:27:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T23:21:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-08T09:49:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-05T00:55:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-05T00:54:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2026-03-02T11:40:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"94a7e911-a749-4e9d-9f03-c3a8792089e5","owner":[],"postedDate":"April 17th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-18T12:24:29+00:00","index":50,"fulltext":""},{"type":"reviewerAgreed","content":"308369657621371933086006328024105021325","date":"2026-05-17T15:59:08+00:00","index":49,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-17T17:19:49+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-17 17:19:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9009756","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9009756","identity":"rs-9009756","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}