Associations of Naples Prognostic Score with Stroke and all-cause mortality in adults : evidence from NHANES (2005-2018)

doi:10.21203/rs.3.rs-4917702/v1

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Associations of Naples Prognostic Score with Stroke and all-cause mortality in adults : evidence from NHANES (2005-2018)

https://doi.org/10.21203/rs.3.rs-4917702/v1

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Objective

This study seeks to assess the associations of Naples Prognostic Score with stroke and all-cause mortality in adults.

Methods

We analyzed data from 44,601 participants in the 2005–2018 National Health and Nutrition Examination Survey (NHANES). The Naples Prognostic Score (NPS) was derived from total cholesterol, serum albumin, neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR). Participants were classified into three groups based on their NPS. Stroke incidence was determined through self-reported questionnaires, and mortality data were diligently tracked using the National Death Index. We investigated the relationship between NPS and stroke prevalence using multiple logistic regression analysis. To explore the association between NPS and all-cause mortality in stroke survivors, we applied Kaplan-Meier survival analysis and Cox proportional hazards models. Furthermore, we conducted a detailed subgroup analysis to assess interaction effects on all-cause mortality risk within this population.

Results

The median age of the participants was 50.00 years [interquartile range: 35.00–64.00], with males comprising 49.36% of the study. The overall stroke prevalence was 3.93%. Participants were categorized into three groups based on their NPS: 6,328 (18.1%) in Group 0 (NPS 0), 24,015 (68.8%) in Group 1 (NPS 1 or 2), and 4,580 (13.1%) in Group 2 (NPS 3 or 4). After adjusting for covariates, individuals in Group 2 exhibited a significantly higher stroke prevalence compared to Group 0, with an odds ratio (OR) of 1.83 [95% confidence interval: 1.49–2.26]. Among the 1,372 patients with a history of stroke, with a median follow-up duration of 5.94 years, we utilized Cox proportional hazards models to assess the relationship between NPS and all-cause mortality risk. The analysis revealed that, after adjusting for covariates, stroke patients in Group 2 faced a significantly elevated risk of all-cause mortality (hazard ratio [HR] = 2.08 [95% confidence interval: 1.40–3.09]) compared to those in Group 0. Subsequent subgroup analyses to explore interaction effects on all-cause mortality risk among stroke patients shown no significant interactions (p for interaction > 0.05).

Conclusions

This study establishes the associations of Naples Prognostic Score with stroke and all-cause mortality in adults.

Health sciences/Neurology/Neurological disorders

Health sciences/Neurology/Neurological disorders/Cerebrovascular disorders

Health sciences/Neurology/Neurological disorders/Cerebrovascular disorders/Stroke

Stroke

Naples prognostic score

NHANES

Stroke is a significant global public health challenge and the second leading cause of death¹, with estimated direct costs (such as treatment and rehabilitation) and indirect costs (productivity loss) exceeding US$891 billion annually². This drives researchers to continuously strive to improve prognosis by targeting stroke risk factors³. In 2019, the US recorded 7.09 million prevalent strokes, despite the decline in age-standardized incidence rates, the absolute burden of stroke is increasing⁴. Clinically, stroke is characterized by sudden neurological impairments, leading to varying degrees of physical and cognitive disabilities, which impact daily activities and quality of life for survivors⁵. Given the substantial impact of stroke on individual health and socio-economic well-being, understanding and managing these risk factors is of paramount importance. Researchers are focusing on identifying new risk factors and delving into the mechanisms of known ones to develop more effective prevention and treatment strategies¹. These efforts aim not only to reduce the incidence of stroke but also to improve long-term outcomes for patients, enhancing their quality of life.

Clinical outcomes in stroke patients are influenced by a variety of factors⁶. Both the occurrence and prognosis of stroke are affected by nutritional status and inflammation. Several scoring systems have been developed, such as the controlling nutritional status (CONUT) score and the systemic inflammation score (SIS)^7,8. However, these systems typically emphasize either inflammation or nutritional status, rather than integrating both aspects. The Naples Prognostic Score (NPS) is a novel scoring system that integrates both inflammatory and nutritional status⁹. Initially used to assess the prognosis of colorectal cancer patients¹⁰, NPS has since been extended to various malignancies^11–13 and recently applied to nonalcoholic fatty liver disease¹⁴ and asthma¹⁵. However, the association between NPS and stroke patients remains unexplored.

Utilizing data from NHANES (2005–2018), this study systematically evaluates the relationship between NPS and stroke prevalence. Additionally, it undertakes a comprehensive examination of the correlation related to NPS and all-cause mortality in stroke patients. The aim is to establish the associations of Naples Prognostic Score with stroke and all-cause mortality in adults.

Study population

NHANES, provided by the National Center for Health Statistics (NCHS), includes extensive medical data on participants, such as nutritional assessments, physical examinations, and health interviews. All data collected from NHANES participants have received approval from the NCHS Ethics Review Board (details available at: https://www.cdc.gov/nchs/nhanes/). Mortality data was tracked using the National Death Index up to December 31, 2019.

Figure 1 illustrates a detailed flowchart of the research population. Information of 70,190 participants was sourced from the NHANES(2005–2018). 28,047 participants under the age of 18; 2,454 participants missing data on assessment data of stroke; 682 participants who were pregnant, 4,084 participants with missing data on NPS, 2 participants lacking data on follow-up time and survival status. Finally, a total of 1372 patients with past histories of stroke were investigated, and their median follow-up duration was 5.94 years. Stroke diagnosis was based on responses to a standardized questionnaire. Participants were classified as having experienced a stroke if they responded affirmatively to the question, "Have you ever told you have had a stroke?".

Assessment of NPS

According to previous research⁹, the Naples Prognostic Score is calculated using four specific criteria: serum albumin (normal level: ≥4 g/dL), total cholesterol (normal level: >180 mg/dL), lymphocyte-to-monocyte ratio (LMR) (normal level: ≤2.96), and neutrophil-to-lymphocyte ratio (NLR) (normal level: >4.44). Individuals with all four parameters within the normal range score 0 points and belong to group 0 or the low NPS group. Those with 1 or 2 parameters outside the normal range belong to group 1 or the medium NPS group. Those with 3 or 4 parameters outside the normal range belong to group 2 or the high NPS group (Table 1).

Table 1

Characteristics of adult participants in NHANES 2005–2018.
Characteristic	Total	NPS, points
Characteristic	Total	0	1–2	3–4	p-value²
Participants, N	34923¹	6328¹	24015¹	4580¹
Age, years	50.00 [35.00,64.00]	48.00 [36.00,59.00]	49.00 [34.00,64.00]	61.00 [41.00,74.00]	< 0.001
Male, n (%)	17,238 (49.36%)	2,630 (41.56%)	12,245 (50.99%)	2,363 (51.59%)	< 0.001
Race, n (%)					< 0.001
Mexican American	5,505 (15.76%)	1,235 (19.52%)	3,677 (15.31%)	593 (12.95%)
Non-Hispanic White	14,846 (42.51%)	2,053 (32.44%)	10,562 (43.98%)	2,231 (48.71%)
Non-Hispanic Black	7,249 (20.76%)	1,397 (22.08%)	4,873 (20.29%)	979 (21.38%)
Other Race	7,323 (20.97%)	1,643 (25.96%)	4,903 (20.42%)	777 (16.97%)
Education level, n (%)					0.007
Below high school	8,720 (24.97%)	1,587 (25.08%)	5,906 (24.59%)	1,227 (26.79%)
High School or above	26,203 (75.03%)	4,741 (74.92%)	18,109 (75.41%)	3,353 (73.21%)
Marital status, n (%)					< 0.001
Married/living with partner	20,845 (59.69%)	4,010 (63.37%)	14,374 (59.85%)	2,461 (53.73%)
Widowed/divorced/separated/never married	14,078 (40.31%)	2,318 (36.63%)	9,641 (40.15%)	2,119 (46.27%)
Family PIR, n (%)					0.250
< 1	6,674 (19.11%)	1,171 (18.51%)	4,598 (19.15%)	905 (19.76%)
≥ 1	28,249 (80.89%)	5,157 (81.49%)	19,417 (80.85%)	3,675 (80.24%)
Smoking, n (%)	15,643 (44.79%)	2,589 (40.91%)	10,700 (44.56%)	2,354 (51.40%)	< 0.001
Drinking, n (%)	23,742 (67.98%)	4,118 (65.08%)	16,526 (68.82%)	3,098 (67.64%)	< 0.001
BMI (kg/m²)	28.07 [24.38,32.60]	28.03 [24.52,32.20]	27.92 [24.30,32.40]	28.93 [24.70,34.60]	< 0.001
Diabetes, n (%)	6,291 (18.01%)	900 (14.22%)	3,991 (16.62%)	1,400 (30.57%)	< 0.001
hyptersion, n (%)	14,971 (42.87%)	2,410 (38.08%)	9,966 (41.50%)	2,595 (56.66%)	< 0.001
SBP(mmHg)	121.33 [111.33,134.00]	120.67 [111.33,133.33]	121.33 [111.33,134.00]	124.00 [112.67,138.00]	< 0.001
DBP(mmHg)	70.67 [63.33,78.00]	72.00 [65.33,79.33]	70.67 [63.33,78.00]	68.00 [59.33,76.00]	< 0.001
Total cholesterol	189.00 [164.00,218.00]	215.00 [197.00,238.00]	188.00 [163.00,215.00]	160.00 [142.00,174.00]	< 0.001
Serum albumin	42.00 [40.00,45.00]	43.00 [42.00,45.00]	42.00 [40.00,45.00]	39.00 [37.00,42.00]	< 0.001
Neutrophils	4.00 [3.10,5.10]	3.60 [2.80,4.60]	3.90 [3.10,5.00]	5.00 [3.90,6.40]	< 0.001
Lymphocyte	2.10 [1.70,2.50]	2.50 [2.00,3.00]	2.00 [1.70,2.50]	1.60 [1.30,2.00]	< 0.001
Monocyte	0.50 [0.40,0.70]	0.40 [0.40,0.50]	0.50 [0.40,0.70]	0.60 [0.50,0.70]	< 0.001
Platelet	240.00 [203.00,284.00]	247.00 [212.00,291.00]	239.00 [203.00,282.00]	234.00 [191.00,284.00]	< 0.001
LMR	4.00 [3.00,5.00]	5.50 [4.88,6.33]	3.75 [3.00,4.50]	2.75 [2.13,3.40]	< 0.001
NLR	1.93 [1.45,2.57]	1.48 [1.17,1.87]	1.94 [1.50,2.47]	3.27 [2.45,4.00]	< 0.001
NPS					< 0.001
0	6,328 (18.12%)	6,328 (100.00%)	0 (0.00%)	0 (0.00%)
1	13,443 (38.49%)	0 (0.00%)	13,443 (55.98%)	0 (0.00%)
2	10,572 (30.27%)	0 (0.00%)	10,572 (44.02%)	0 (0.00%)
3	3,830 (10.97%)	0 (0.00%)	0 (0.00%)	3,830 (83.62%)
4	750 (2.15%)	0 (0.00%)	0 (0.00%)	750 (16.38%)
stroke, n (%)	1,374 (3.93%)	148 (2.34%)	830 (3.46%)	396 (8.65%)	< 0.001
¹n (%); Median [25%,75%]
²Pearson's Chi-squared test; Kruskal-Wallis rank sum test
Abbreviations: body mass index, BMI; PIR, poverty income ratio; NLR, neutrophil-to-lymphocyte ratio; LMR, lymphocyte-to-monocyte ratio;SBP, systolic blood pressure; DBP, diastolic blood pressure.

Assessment of all-cause mortality

All-cause mortality was determined using data released by the National Center for Health Statistics, with the cutoff date being December 31, 2019.

Covariates

A variety of covariates were introduced into our study according to previous research¹⁶. These covariates are considered to have an association with stroke: sex (male or female), race (Mexican American, non-Hispanic White, non-Hispanic Black, or other race), age (≥ 18 years), body mass index (BMI), education level (Below high School, High School or above), poverty–income ratio (< 1 and ≥ 1), smoking (yes or not), marital status(Married/living with partner or Widowed/divorced/separated/never married ), drinking, chronic conditions including hypertension and diabetes (was diagnosed with diabetes or Subcutaneous injection of insulin or oral hypoglycemic drugs or the value of fasting glycated hemoglobin more than 6.4).

Statistical analysis

Continuous variables are represented by median and interquartile ranges (IQRs), while categorical variables are represented by numbers and percentages. Wilcoxon rank-sum test is used for continuous variables. The pearson's Chi-square test is used for comparison of categorical variables.

We performed multivariate logistic regression analysis to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to investigate the relationship between NPS and its components and the prevalence of stroke. We calculated cumulative survival rates using the Kaplan-Meier method and log-rank test, and compared the three groups based on NPS. The adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause mortality in stroke patients were calculated using Cox regression analysis. Subgroup analysis to evaluate the interaction effect on all-cause mortality risk among stroke patients. All statistical analyses were performed using R software (version 4.4.0).

Characteristics of study participants

A flow diagram of this research population is shown in Fig. 1. Information of 70,190 participants were sourced from the NHANES (2005–2018). According to the inclusion criteria, a total of 28,047 participants under the age of 18 were excluded. Additionally, 2,454 participants were excluded due to missing data on stroke assessment, 682 participants due to pregnancy, 4,084 participants due to missing information on NPS, and 2 participants were excluded due to lacking data on follow-up for all-cause mortality. 1372 patients with past histories of stroke were investigated, and their median follow-up duration was 5.94 years.

Baseline characteristics of the three NPS groups in NHANES from 2005 to 2018 was shown in Table 1. The median age of the study population was 50.00 [IQR 35.00, 64.00] years, with 49.36% being male. The prevalence of stroke was 3.93%. The median for serum albumin was 42.00 [IQR 40.00, 45.00] g/L, the medians for TC was 189.00 [IQR 164.00, 218.00] mg/dL, the medians for NLR was 1.93 [IQR 1.45, 2.57], and the medians for LMR was 4.00 [IQR 3.00, 5.00]. The number of participants with NPS = 0 was 6328 (18.12%), NPS = 1 was 13443 (38.49%), NPS = 2 was 10572 (30.27%), NPS = 3 was 3730 (10.97%), and NPS = 4 was 3830 (2.15%). Compared to Group 0 (NPS0), participants in Group 2 (NPS = 3, 4) were older, lower rates of marriage and non-drinkers, a higher prevalence of hypertension, diabetes and stroke.

In the all-cause mortality outcomes with a median follow-up time of 5.94 years, among 1372 adult stroke patients, 504 cases (36.73%) experienced all-cause mortality (Table 2). Compared to adult stroke survivors, stroke patients who experienced all-cause mortality were characterized by older age, being non-Hispanic white males, lower education and income levels, and a higher prevalence of hypertension and diabetes. Additionally, they had significantly lower levels of serum albumin and LMR, and higher levels of TC and NLR (p < 0.05).

Table 2

**Survey baseline demographic and medical characteristics of patients with stroke in the NHANES 2005–2018.** body mass index, BMI; PIR, poverty income ratio; NLR, neutrophil-to-lymphocyte ratio; LMR, lymphocyte-to-monocyte ratio;SBP, systolic blood pressure; DBP, diastolic blood pressure.
Characteristic	Total	All-cause mortality		p-value²
Characteristic	Total	No	Events	p-value²
Participants, N	1372¹	868¹	504¹
Age, years	68.00 [59.00,78.00]	64.00 [54.00,73.00]	77.00 [68.00,80.00]	< 0.001
Male, n (%)	669 (48.76%)	384 (44.24%)	285 (56.55%)	< 0.001
Race, n (%)				< 0.001
Mexican American	124 (9.04%)	87 (10.02%)	37 (7.34%)
Non-Hispanic White	701 (51.09%)	378 (43.55%)	323 (64.09%)
Non-Hispanic Black	368 (26.82%)	262 (30.18%)	106 (21.03%)
Other Race	179 (13.05%)	141 (16.24%)	38 (7.54%)
Education level, n (%)				0.001
Below high school	469 (34.18%)	269 (30.99%)	200 (39.68%)
High School or above	903 (65.82%)	599 (69.01%)	304 (60.32%)
Marital status, n (%)				0.014
Married/living with partner	697 (50.80%)	463 (53.34%)	234 (46.43%)
Widowed/divorced/separated/never married	675 (49.20%)	405 (46.66%)	270 (53.57%)
Family PIR, n (%)				0.013
< 1	312 (22.74%)	216 (24.88%)	96 (19.05%)
≥ 1	1,060 (77.26%)	652 (75.12%)	408 (80.95%)
BMI (kg/m²)	29.00 [25.10,33.50]	29.60 [25.58,34.30]	27.94 [24.58,31.90]	< 0.001
Smoking, n (%)	831 (60.57%)	511 (58.87%)	320 (63.49%)	0.091
Drinking, n (%)	877 (63.92%)	587 (67.63%)	290 (57.54%)	< 0.001
Diabetes, n (%)	551 (40.16%)	332 (38.25%)	219 (43.45%)	0.058
Hypertension, n (%)	1,113 (81.12%)	684 (78.80%)	429 (85.12%)	0.004
Total cholesterol	178.00 [151.00,211.00]	182.00 [156.00,211.00]	172.00 [144.00,210.25]	0.003
Serum albumin	41.00 [38.00,43.00]	41.00 [39.00,43.00]	41.00 [38.00,43.00]	0.002
Neutrophils	4.30 [3.30,5.50]	4.20 [3.20,5.40]	4.50 [3.40,5.60]	0.006
Lymphocyte	1.90 [1.50,2.50]	2.00 [1.60,2.50]	1.80 [1.30,2.30]	< 0.001
Monocyte	0.60 [0.50,0.70]	0.60 [0.40,0.70]	0.60 [0.50,0.70]	< 0.001
Platelet	228.50 [191.00,275.00]	233.00 [196.00,276.00]	221.50 [177.75,272.00]	0.001
LMR	3.40 [2.50,4.58]	3.67 [2.71,4.75]	3.00 [2.17,4.17]	< 0.001
NLR	2.23 [1.64,3.07]	2.08 [1.55,2.85]	2.47 [1.82,3.51]	< 0.001
NPS				< 0.001
0	148 (10.79%)	115 (13.25%)	33 (6.55%)
1–2	829 (60.42%)	555 (63.94%)	274 (54.37%)
3–4	395 (28.79%)	198 (22.81%)	197 (39.09%)
¹n (%); Median [25%,75%]
²Pearson's Chi-squared test; Wilcoxon rank sum test

Correlation between NPS and stroke

This study, referencing other literature, categorized NPS into three groups, with group 0 as the reference¹⁵. We used Logistic regression analysis to assess its association with stroke prevalence (Table 3). Our data indicated a strong positive correlation between NPS and stroke prevalence in the crude model (OR = 3.95 [3.26, 4.79]). In Model 1, compared to the reference group, participants in Group 2 exhibited a markedly increased prevalence of stroke (OR = 2.13 [1.74, 2.61]). This link retained its statistical significance in Model 2 (OR = 1.83 [1.49, 2.26]). Further trend test results showed that as NPS levels increased, the risk of stroke significantly increased (trend p < 0.001).

Table 3

ORs (95% CIs) of NPS among adults with stroke in NHANES 2005–2018 (n = 1372).
Model	NPS, points	OR (95% CI)	p value	p for trend
Crude Model	0	1.0 [Reference]		< 0.001
	1–2	1.49 (1.25,1.78)	< 0.001
	3–4	3.95 (3.26,4.79)	< 0.001
Model Ⅰ	0	1.0 [Reference]		< 0.001
	1–2	1.22 (1.01,1.46)	0.035
	3–4	2.13 (1.74,2.61)	< 0.001
Model Ⅱ	0	1.0 [Reference]		< 0.001
	1–2	1.16 (0.96,1.39)	0.127
	3–4	1.83 (1.49,2.26)	< 0.001
Abbreviations: OR, Odds Ratio; CI, confidence interval.
Model Ⅰ adjusted for age, sex, Race.
Model Ⅱ adjusted for age, sex, Race, Education level, poverty income ratio (PIR), Marital status, body mass index (BMI), Smoking, Drinking, Diabetes, Hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP).

Correlation between NPS and mortality participants with stroke

The correlation between NPS and mortality in stroke participants was evaluated using Kaplan-Meier curves (Fig. 2). Results showed that individuals in Group 2 had the highest risk of all-cause mortality compared to other groups, and this was statistically significant (P < 0.001). After adjusting for multiple variables, Group 2 participants exhibited a significantly heightened risk of all-cause mortality (HR = 2.08 [1.40, 3.09]) relative to those in Group 0 (Table 4). Additionally, trend analysis revealed a significant pattern (p for trend < 0.001), indicating that each incremental increase in NPS corresponded to a statistically significant rise in mortality risk among stroke patients. To assess the robustness of the association between NPS and all-cause mortality risk in the stroke population, we conducted a subgroup analysis (Fig. 3). The analysis revealed no significant interaction effect (p for interaction > 0.05).

Table 4

HRs (95% CIs) of mortality according to three groups based on NPS among adults with stroke in NHANES 2005–2018 (n = 1372).
Outcome	Crude Model		Model Ⅰ		Model Ⅱ
Outcome	HR (95% CI)	P-value	HR (95% CI)	P-value	HR (95% CI)	P-value
NPS
0	Reference		Reference		Reference
1–2	1.74 (1.21,2.50)	0.003	1.22 (0.85, 1.76)	0.289	1.21(0.84, 1.77)	0.309
3–4	4.00 (2.76,5.79)	< 0.001	2.20 (1.50, 3.23)	< 0.001	2.08 (1.40,3.09)	< 0.001
P for trend	< 0.001		< 0.001		< 0.001
Abbreviations: CI, confidence interval.
Model Ⅰadjusted for age, sex, Race, Education level.
Model Ⅱadjusted for age, sex, Race, Education level, Marital status, body mass index (BMI), Diabetes, Hypertension, Smoking, Drinking.

Globally, stroke is a major public health issue with high disability rates. This cohort study utilized data from NHANES 2005–2018 and, to the best of our knowledge, is the first report examining the connection between NPS levels and stroke. The study elaborates on the relationships between nutrition, inflammation, and stroke, as well as the risk of all-cause mortality in stroke patients, further underscoring the importance of assessing nutritional and inflammatory markers in stroke patients. Our findings indicate that stroke patients have higher NPS levels compared to those without stroke. After adjusting for relevant factors, we found a significant positive association between NPS and all-cause mortality in stroke patients.

Malnutrition is associated with poor prognosis in stroke patients^17,18 and can trigger systemic inflammation¹⁹, which increases the risk of stroke²⁰ and worsens outcomes²¹. Conversely, inflammation exacerbates malnutrition, creating a vicious cycle²². Clinically, various biomarkers are used to assess the nutritional status of stroke patients⁷. Serum albumin levels, a common indicator of nutritional status, are closely associated with increased stroke risk^23,24. Total cholesterol levels are another nutritional status indicator; their relationship with stroke remains uncertain²⁵, with total cholesterol possibly positively associated with ischemic stroke and negatively associated with hemorrhagic stroke risk^26–28.

On the other hand, systemic inflammation exacerbates atherosclerosis, thereby increasing the risk of stroke. Post-stroke inflammation can lead to significant long-term sequelae²⁹. NLR and LMR are potential novel biomarkers of systemic inflammation and serve as good predictors in ischemic stroke patients^30,31. Inflammatory cytokines exacerbate malnutrition in stroke patients by increasing metabolic demands, reducing appetite, affecting digestion and absorption, and breaking down muscle and fat^32,33. Studies have shown that low albumin levels are correlated with elevated levels of inflammatory markers, further increasing stroke risk^34,35.

Elevated inflammatory markers are associated with poorer nutritional status and higher mortality rates in stroke patients³⁶. This bidirectional relationship between inflammation and malnutrition worsens the prognosis of stroke patients, making it crucial to find indicators that can assess both nutritional status and systemic inflammation. NPS uses albumin, total cholesterol, NLR, and LMR to calculate a score, reflecting systemic inflammation and nutritional status, and is associated with the prognosis of various diseases^37–39. Although research on NPS mainly focuses on tumor-related diseases, it has been applied in various non-tumor diseases^40,41. In our study, We found that stroke patients have higher NPS levels, and with 5.94 years of all-cause mortality follow-up data, Cox regression analysis found that the Naples Prognostic Score was significantly associated with all-cause mortality in adults stroke patients.

Our study has the following strengths, first, we used a nationally representative and relatively large sample to investigate the significantly increased NPS levels in adult stroke patients and further elucidate the relationship between NPS and stroke mortality, enhancing the generalizability and credibility of our findings. Secondly, we meticulously adjusted our analyses for key factors affecting stroke, thereby improving the reliability and scientific rigor of our results. We included an average of 5.94 years of follow-up data, elucidating the correlation between NPS and all-cause mortality in stroke patients. Third, NPS considers the dual impact of nutritional status and systemic inflammation, making it a more comprehensive indicator of a patient's health status and disease risk compared to individual nutritional or inflammatory markers.

Despite the significant advantages of our study, there are some limitations that must be acknowledged, aside from the lack of detailed neurological function scores in NHANES, which prevented us from assessing the impact of NPS on stroke-related disability and quality of life. NHANES relies on patient self-reporting, which may introduce recall bias and affect data accuracy. Secondly, although we controlled for various potential confounding factors, unmeasured confounders may still influence our analysis. For instance, unaccounted variables such as dietary habits and genetic factors could be potential confounders. Additionally, despite the nationwide scope of this study, the data primarily derive from the US population, limiting the representation of economically underdeveloped countries. This restricts the global applicability of our findings. Therefore, when interpreting and applying the results of this study, these limitations should be fully considered to more accurately understand the significance and impact of the research. Going forward, global clinical investigations are necessary to validate our conclusions and assess their applicability across different populations and regions.

This study analyzed data from NHANES (2005–2018) to evaluate the associations of Naples Prognostic Score with stroke and all-cause mortality in adults. The results indicate that NPS is significantly associated with stroke incidence and all-cause mortality risk in adults stroke patients. These findings have clinical significance, suggesting that monitoring Naples Prognostic Score levels may be a valuable tool for detecting stroke patients and their all-cause mortality.

Additional Information

The authors declare no competing interests.

Ethics approval

Data analyzed in this study were obtained from the NHANES. The protocols involved were approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board (ERB), and informed consent from all participants was documented. Details on Institutional Review Boards of the CDC and NCHS are available at (http://www.cdc.gov/nchs/nhanes/irba98.htm)

Consent for publication
The authors provide their consent for the publication of the study results.

Funding

This study was supported by Zhengzhou Science and Technology Preferential people project (2022KJHM0017), Zhengzhou Medical and Health Technology Innovation Guidance Plan Project(2024YLZDJH268), Henan Medical Science and Technology Research Project (LHGJ20191042), Chinese Stroke Association Qihang Fund(The 11th funding project).

Author Contribution

ZQ.X. performed data acquisition and drafted the main manuscript text. MY.P performed data analysis. XQ.Y. assisted in data acquisition. LX.X. and DY. Z. prepared Fig.1,2. XC. L. and CH.H. prepared Tables 1,2, JJ. Z. and RL. G. prepared Tables 3,4. WZ. X. and GQ. Y. contributed to the conception and design of the study, supervised the research process. All authors reviewed the manuscript.

Acknowledgement

The data from NHANES collection were sponsored by the CDC.

Data Availability

The datasets analyzed during the current study are publicly available in the National Health Nutrition Survey (NHANES), https://www.cdc.gov/nchs/nhanes/index.htm.

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No competing interests reported.

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Associations of Naples Prognostic Score with Stroke and all-cause mortality in adults : evidence from NHANES (2005-2018)

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Abstract

Objective

Methods

Results

Conclusions

Figures

Introduction

Methods

Study population

Assessment of NPS

Assessment of all-cause mortality

Covariates

Statistical analysis

Results

Characteristics of study participants

Correlation between NPS and stroke

Correlation between NPS and mortality participants with stroke

Discussion

Conclusions

Declarations

Additional Information

Ethics approval

Consent for publication
The authors provide their consent for the publication of the study results.

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1

Associations of Naples Prognostic Score with Stroke and all-cause mortality in adults : evidence from NHANES (2005-2018)

Status:

Version 1

Abstract

Objective

Methods

Results

Conclusions

Figures

Introduction

Methods

Study population

Assessment of NPS

Assessment of all-cause mortality

Covariates

Statistical analysis

Results

Characteristics of study participants

Correlation between NPS and stroke

Correlation between NPS and mortality participants with stroke

Discussion

Conclusions

Declarations

Additional Information

Ethics approval

Consent for publication The authors provide their consent for the publication of the study results.

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1

Consent for publication
The authors provide their consent for the publication of the study results.