Identification of risk factors for malnutrition in patients with severe pneumonia and development of a predictive model to guide personalized enteral nutrition care

Introduction

Severe pneumonia, as a critical and life-threatening condition of the respiratory system, is characterized by rapid onset, fast progression, and severe clinical manifestations. Patients often face multiple health challenges, among which malnutrition has become increasingly prominent (1). During the course of severe pneumonia, the body enters a hypermetabolic state with significantly elevated energy demands. Severe pneumonia is characterized by high-acuity features; for community-acquired cases, major criteria include invasive mechanical ventilation or septic shock requiring vasopressors, and minor criteria include ≥3. Patients frequently encounter nutrition-relevant challenges such as hypermetabolic stress, dyspnea, anorexia, gastrointestinal dysmotility, delirium, immobility, and polypharmacy. Meanwhile, inflammation, respiratory distress, and gastrointestinal dysfunction caused by the disease further impair nutrient intake, digestion, and absorption, leading to a high incidence of malnutrition (2). Malnutrition not only compromises immune function and increases susceptibility to infections but also impairs tissue repair, delays recovery, and raises the risk of complications and mortality, severely affecting patient prognosis (1,3,4). Therefore, identifying the factors contributing to malnutrition in patients with severe pneumonia and developing a reliable predictive model is of great clinical significance (5).

Previous studies and guidelines have highlighted the importance of malnutrition screening in pneumonia patients. For example, Shimizu et al. (1) demonstrated a multi-level texture-modified diet (TMD) was associated with maintenance or improvement of swallowing function and Mini Nutritional Assessment-Short Form (MNA-SF) scores in older patients with pneumonia. Furthermore, European Society for Parenteral and Enteral Nutrition (ESPEN) and American Society for Parenteral and Enteral Nutrition (ASPEN) guidelines emphasize early enteral nutrition (EN) initiation in critically ill patients, including those with pneumonia. By comprehensively analyzing various potential influences, such as baseline health status, disease severity, treatment strategies, and nutritional support methods, clinicians can more accurately identify high-risk individuals (6). Constructing a predictive model enables healthcare professionals to anticipate the risk of malnutrition in advance, allowing for the implementation of personalized EN plans. Such targeted nutritional interventions can improve patients’ nutritional status. Personalized care also can enhance immune resistance, promote faster recovery, and improve quality of life, while also providing a strong theoretical and practical foundation for clinical nutritional care. Severe pneumonia is characterized by high-acuity features; for community-acquired cases, major criteria include invasive mechanical ventilation or septic shock requiring vasopressors, and minor criteria include ≥3 of: respiratory rate ≥30/min, partial pressure of arterial oxygen (PaO₂)/fraction of inspired oxygen (FiO₂) ≤250, multilobar infiltrates, uremia, leukopenia, thrombocytopenia, hypothermia, or hypotension requiring fluids. Patients frequently encounter nutrition-relevant challenges such as hypermetabolic stress, dyspnea and increased work of breathing, anorexia and dysphagia, gastrointestinal dysmotility, delirium, immobility, and polypharmacy, all of which impair intake, digestion/absorption, and anabolic recovery. We present this article in accordance with the TRIPOD reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1225/rc).

Methods

Sample size estimation and patient selection

Sample size was calculated using G*Power software with linear multiple regression analysis selected. The significance level was set at α=0.05 and statistical power at 1−β=0.8. Assuming 8 independent variables and an expected effect size (f²) of 0.15, the estimated required sample size ranged from approximately 130 to 160 cases. To account for potential interaction terms, missing data, and model complexity, the final sample size was set at 150 patients.

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of Taizhou Affiliated Hospital of Nanjing University of Chinese Medicine (ethics approval No. 20250425). Informed consent was obtained from all individual participants included in the study.

Based on this estimation, clinical data from 150 critically ill patients with severe pneumonia (88 males; 62 females) were retrospectively collected between May 2023 and February 2025. The etiology included 68 cases of hospital-acquired pneumonia and 82 cases of community-acquired pneumonia (CAP). Regarding socioeconomic status, 58 patients had a per capita monthly household income of <3,000 yuan, while 92 had ≥3,000 yuan. The average age was 65.72±3.46 years, and the average body mass index (BMI) was 21.98±2.46 kg/m². Critical illness and broad-spectrum antibiotics are associated with gut microbial dysbiosis, barrier dysfunction, and immune perturbations, which have been documented within 48–72 h of intensive care unit (ICU) admission. These alterations plausibly contribute to malnutrition risk and adverse pulmonary outcomes along the gut-lung axis (7).

Patients meeting the following criteria were included: (I) diagnosed with severe pneumonia according to established criteria (8); (II) individuals with risk factors such as advanced age, smoking, or low BMI but without a clinical diagnosis of malnutrition were included, as these risk factors alone do not establish chronic malnutrition; and (III) with complete clinical data available. Exclusion criteria included: (I) presence of severe immunosuppressive conditions such as human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) or hematologic disorders; (II) history of organ transplantation; (III) death within 48 hours of hospital admission; (IV) diagnosed psychiatric disorders or mental illness; (V) coexisting severe neurological conditions such as dementia, hypoxic-ischemic brain injury, hepatic encephalopathy, or central nervous system infections; (VI) diagnosis of acute respiratory distress syndrome (ARDS); (VII) with persistent coma; (VIII) patients who underwent tracheotomy; (IX) patients with documented malnutrition prior to admission.

Severe pneumonia was defined a priori as severe community-acquired pneumonia (CAP) per Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS) criteria (9) (≥1 major or ≥3 minor criteria) or severe hospital-acquired pneumonia (HAP)/ventilator-associated pneumonia (VAP) per the IDSA/ATS 2016 guideline; patients meeting either framework were classified as severe pneumonia.

Nutritional status assessment and grouping

Nutritional status was assessed using the Mini Nutritional Assessment (MNA) tool (10), validated for use in adults aged ≥65 years. The MNA was performed within 24 hours of admission for all patients. For those with hospital-acquired pneumonia, the MNA was not repeated after diagnosis, which is acknowledged as a limitation of this study. When oral intake is possible, oral nutritional supplements (ONS) and dietitian-guided food-first strategies are appropriate; when intake is inadequate, nasogastric or nasojejunal enteral nutrition (EN) is preferred over parenteral routes in line with ESPEN hospital-nutrition recommendations (11). For ICU patients with EN-related diarrhea and no contraindications (no hemodynamic instability, severe dysmotility, or risk of bowel ischemia), consideration may be given to soluble/fermentable fiber (e.g., guar gum) or mixed-fiber EN formulas to help reduce diarrhea; insoluble fiber should be avoided in high-risk settings. Routine fiber to “regulate bowels” is not recommended in the ICU, and any fiber trial should be individualized and monitored (12). This includes 18 items grouped into four domains: (I) subjective assessment (2 items: nutritional and health status); (II) dietary questionnaire (6 items: food and fluid intake, appetite, number of meals, ability to eat independently); (III) global assessment (6 items: comorbidities, medications, mobility, neuropsychological problems, and lifestyle); and (IV) anthropometric measurements (4 items: weight loss in the last 3 months, calf circumference, mid-arm circumference, and body weight/BMI). The total score is 30 points. A score ≥24 indicates normal nutritional status; a score <24 indicates malnutrition.

Data collection

Basic demographic and clinical data were collected via questionnaires, including: (I) general characteristics (age, sex, BMI, pneumonia etiology, mechanical ventilation, smoking status, per capita monthly household income, and presence of gut microbiota imbalance, which was defined as persistent diarrhea, abdominal distension, or feeding intolerance, combined with abnormal stool cultures or documented dysbiosis associated with broad-spectrum antibiotic use in the medical record); (II) comorbidities (hypertension, diabetes, heart failure, hyperlipidemia, and anemia); (III) laboratory parameters. Fasting blood samples were drawn from the antecubital vein upon admission. Laboratory tests included platelet count, red blood cell count, white blood cell count, interleukin-6 (IL-6), procalcitonin (PCT), serum albumin (ALB, analyzed as a clinical/laboratory covariate and not as a nutrition-status marke), and estimated glomerular filtration rate (eGFR), measured using the AU5821 fully automated biochemical analyzer (Beckman Coulter, Brea, CA, USA).

Treatment protocol

All patients received empiric antibiotic therapy upon admission, tailored to disease severity, pathogen identification, and local antimicrobial resistance data. In addition, nutritional support was provided as part of the treatment protocol. Patients screened as at risk of malnutrition or with confirmed malnutrition (MNA <24) received individualized nutritional care. This included ONS if oral intake was possible, or early EN via nasogastric/nasojejunal tube within 24–48 hours of admission if intake was insufficient, in accordance with ESPEN and ASPEN guidelines. Nutritional status was reassessed regularly during hospitalization, and interventions were adjusted accordingly. Antibiotic regimens included β-lactams, carbapenems, fluoroquinolones, or aminoglycosides. Clinical response and microbiological test results were closely monitored, and adjustments to antibiotic type and dosage were made as necessary. We report in-hospital nutrition interventions initiated after MNA screening; discharge recommendations are summarized separately in the Discussion.

Statistical analysis

Statistical analyses were performed using SPSS version 27.0. Normally distributed continuous variables are expressed as mean ± standard deviation and compared using t-tests. Categorical data are expressed as frequency (percentage) and compared using χ². A significance level of α=0.05 was applied. Univariate and binary logistic regression analyses were conducted to identify independent risk factors associated with malnutrition in severe pneumonia. Statistically significant variables were then entered into the rms package in R to construct a Nomogram prediction model. Internal validation of the model was performed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results

Univariate analysis

No statistically significant differences were observed between the normal nutrition group and the malnutrition group in terms of sex, pneumonia etiology, hypertension, diabetes, heart failure, hyperlipidemia, anemia, mechanical ventilation, platelet count, red blood cell count, white blood cell count, IL-6, PCT, or eGFR (P>0.05). However, significant differences were found in gut microbiota imbalance, smoking status, per capita monthly household income, age, BMI, and ALB levels (P<0.05). These results are shown in Table 1.

Binary logistic regression analysis

Variables with P<0.05 from the univariate analysis were included in the binary logistic regression model. Variable assignments are detailed in Table 2. Multivariate analysis identified the following as independent risk factors for malnutrition in patients with severe pneumonia: gut microbiota imbalance, smoking, per capita monthly household income <3,000 yuan, and older age. In contrast, higher BMI and ALB levels were found to be protective factors (P<0.05). These results are presented in Table 3.

Construction of a nomogram prediction model for malnutrition risk

The independent predictors, gut microbiota imbalance, age, BMI, and ALB, were entered into R software to construct a Nomogram prediction model. Among these, age contributed the highest weight to the model (Figure 1).

Figure 1 Nomogram for predicting malnutrition risk in patients with severe pneumonia. Imbalance of gut microbiota: 1 = present and 2 = absent. ALB, albumin; BMI, body mass index.

Model performance was internally validated using the Bootstrap method with 1,000 resamples. Validation data are shown in Table 4. The area under the curve (AUC) was 0.974 (95% CI: 0.954–0.994), indicating excellent discriminative ability (Figure 2). DCA showed that the model’s threshold probability range was 1–99%. The absolute error between predicted and actual outcomes was 0.027. There was no significant difference between observed and predicted values (Chi-squared =3.6454, P=0.89), demonstrating good calibration (Figures 3,4).

Figure 2 ROC curve of the predictive model. ROC, receiver operating characteristic.

Figure 3 Calibration curve of the predictive model.

Figure 4 DCA of the predictive model. DCA, decision curve analysis.

Discussion

Severe pneumonia is a serious pulmonary infectious disease characterized by symptoms such as infection, fever, and respiratory failure. Patients are typically in a hypercatabolic state, with increased energy and protein demands. Impaired ventilation and gas exchange, as well as hypoxemia, lead to compensatory increases in respiratory rate and respiratory muscle activity, resulting in greater oxygen consumption and significantly elevated resting and activity-related energy expenditure (13). In addition, most patients have multiple comorbidities, which further increase the risk of malnutrition. Once malnutrition occurs, it can severely impair respiratory muscle strength, lung function, and immune defense, worsen infections, and negatively impact prognosis. Therefore, close monitoring of nutritional status and timely identification of at-risk patients are essential to enable early intervention and improve outcomes (14,15).

Guideline-based inpatient nutrition for severe pneumonia

In hemodynamically stable adults with severe pneumonia requiring critical care, contemporary ASPEN (16)/SCCM and ESPEN (17,18) guidance recommend early initiation of EN within 24–48 hours of admission (or intubation), with progressive advancement as tolerated and a protein target ~1.2–2.0 g/kg/day. Parenteral nutrition is generally deferred initially and considered as supplemental PN if energy-protein goals cannot be met enterally (timing varies by nutrition risk and feasibility of EN).

Revise fiber/probiotic guardrails

For ICU EN-related diarrhea without contraindications, a soluble/fermentable fiber trial or mixed-fiber formula can be considered; avoid insoluble fiber in high-risk states. Routine probiotics are not recommended in critically ill adults; potential benefits are strain-specific and must be weighed against safety (16,19).

Binary logistic regression analysis in this study identified gut microbiota imbalance, smoking, per capita monthly household income <3,000 yuan, and age as independent risk factors for malnutrition in patients with severe pneumonia. In contrast, BMI and ALB were found to be protective factors. Among them: (I) univariate analysis showed that patients with gut dysbiosis were more likely to develop malnutrition. This may be because the intestinal microbiota plays a key role in maintaining nutritional balance and gastrointestinal function. Dysbiosis can impair digestion and absorption, increase intestinal permeability, and allow endotoxins and bacteria to enter the bloodstream, triggering immune activation, oxidative stress, and inflammatory responses. These lead to the loss of muscle proteins and promote malnutrition (20,21). Moreover, the gut microbiota and mucosal barrier form a defensive line against harmful substances. Dysbiosis reduces beneficial bacteria and increases harmful ones, compromising the mucosal barrier and allowing toxins to enter circulation. It also reduces digestive enzyme secretion, further hindering nutrient breakdown and absorption (22). Additionally, dysbiosis may be related to antibiotic use. Critically ill patients often require broad-spectrum antibiotics, which, while targeting pathogens, can disrupt the normal gut flora. Future studies should explore the impact of different drug regimens on the microbiota and develop strategies to minimize antibiotic-induced dysbiosis. (II) Tobacco contains harmful substances that irritate the airways, impair mineral absorption, and exacerbate pulmonary inflammation. This places the body in a heightened stress state with increased energy expenditure and nitrogen loss. Given that energy needs are already elevated in severe pneumonia, smoking is an independent risk factor for malnutrition, as it chronically impairs nutrient absorption and depletes energy reserves. In patients with severe pneumonia, acute inflammation further elevates energy expenditure and decreases appetite. Under this metabolic stress, the pre-existing risk from smoking is compounded, placing patients at particularly high risk for malnutrition (23). (III) Univariate analysis indicated that economic status affects nutritional condition. Low-income families may struggle to afford nutrient-dense foods or access high-quality EN products and professional nutritional guidance. This lack of resources hinders proper intake and absorption, increasing malnutrition risk. Additionally, financial stress may reduce appetite and hinder recovery, especially under chronic psychological burden (24). (IV) Older age was associated with a higher risk of malnutrition. This is likely due to age-related declines in chewing ability, appetite, and digestive function, as well as the presence of chronic diseases. These factors reduce food intake and impair nutrient utilization. Elderly patients with severe pneumonia often experience poor general condition, ineffective coughing, and impaired airway reflexes, leading to feeding intolerance and negative nitrogen balance, which exacerbates malnutrition (25). (V) Patients with lower BMI were more likely to be malnourished, consistent with findings by Workie (2025) (26). Lower BMI indicates weaker physical reserves and reduced energy/nutrient stores. Such patients are more vulnerable to malnutrition under increased metabolic stress. Additionally, lower BMI is associated with weaker respiratory muscle strength, making them more prone to fatigue and worsening respiratory function. (VI) Serum ALB is a negative acute-phase reactant that is markedly influenced by systemic inflammation, illness severity, and fluid status; it is not a reliable indicator of nutritional status per contemporary guidance. The inverse association we observed between ALB and malnutrition risk likely reflects underlying inflammatory burden and disease severity rather than nutritional reserves. Accordingly, ALB in our model should be interpreted as a clinical/laboratory correlate and not as evidence of preserved nutrition. This interpretation aligns with current ASPEN guidance that visceral proteins (e.g., ALB, prealbumin) should not be used as nutrition markers (27).

To address these risk factors in clinical practice, the following EN strategies are recommended. For patients with gut microbiota imbalance, dietary fiber through fresh fruits, vegetables, and whole grains should be increased, while avoiding spicy, greasy, or irritating foods. Probiotic intake can be supported by consuming yogurt, fermented foods, or probiotic supplements, under medical supervision. Nutritional status (weight, BMI, ALB) should be monitored regularly. Our findings (age, smoking, lower BMI, low income, dysbiosis) fit with guideline-directed care pathways prioritizing early EN, sufficient protein, avoidance of routine probiotics in ICU settings, and targeted use of soluble fiber only when appropriate (16). For smokers, the importance of smoking cessation should be emphasized, with counseling and individualized plans provided to quit smoking. Increased metabolic demands caused by smoking should be addressed through tailored EN strategies, ensuring that energy and nutrient requirements are adequately met. For low-income patients, the economic situation should be assessed. Cost-effective and nutritionally balanced enteral formulas should be selected according to affordability, and relevant financial aid resources should be provided to alleviate economic burden and support adequate nutritional care. For elderly patients, age-related nutritional requirements and swallowing function should be evaluated. Where appropriate, nasogastric or nasojejunal feeding routes should be employed. Tolerance to EN should be closely monitored, and feeding rates and volumes should be adjusted to minimize the risk of complications. For patients with low ALB levels, protein intake should be prioritized. High-quality protein sources, such as whey protein powder, eggs, and fish, should be incorporated into EN to support ALB synthesis, maintain plasma oncotic pressure, and sustain normal physiological function.

Post-discharge nutrition & transitions of care

Recommendations such as increasing fresh fruits, vegetables, and whole grains are most feasible at discharge and during recovery, when anorexia and feeding intolerance have resolved. We provide this advice as part of transitions-of-care planning and arrange follow-up with outpatient nutrition services to support affordability and adherence (e.g., economical ONS when indicated) (11). Food-first counseling (e.g., fruits/vegetables/whole grains) and low-cost ONS are most feasible after discharge once anorexia/feeding intolerance improves. We embed these into transition-of-care plans and link low-income patients to economical ONS options and outpatient nutrition follow-up, per ESPEN hospital-nutrition and ASPEN resources.

Our findings are consistent with prior studies that applied nutrition screening tools in pneumonia patients. For example, Shimizu et al. (1) reported that older inpatients with pneumonia frequently presented with malnutrition when assessed by MNA, and nutritional status was strongly associated with clinical outcomes. Similarly, Shimizu et al. (4) confirmed the predictive validity of MNA cutoffs in pneumonia patients across Asian populations. Beyond MNA, the Global Leadership Initiative on Malnutrition (GLIM) criteria have been increasingly applied in hospitalized and surgical patients. Studies by Jensen et al. (28) and Murnane et al. (14) showed that GLIM criteria identified a higher incidence of malnutrition than MNA and were associated with adverse outcomes, including pulmonary complications. However, to our knowledge, no studies have directly applied GLIM criteria in severe pneumonia populations. Thus, our work extends prior MNA-based studies while highlighting the need for future comparative research on GLIM and other diagnostic frameworks in this patient group.

Definitions

EN: nutrition delivered into the GI tract via tube/catheter/stoma (preferred term over “tube feeding”). ONS: energy/protein-dense food for special medical purposes (FSMP) products used as ‘sip feeds’ to augment oral intake; clinical benefit and cost-effectiveness are well established.

In conclusion, gut microbiota imbalance, smoking, low per capita monthly household income, older age, low BMI, and low ALB are independent risk factors for malnutrition in patients with severe pneumonia. The nomogram prediction model based on these factors demonstrates strong clinical value in predicting malnutrition risk. Targeted EN interventions addressing these specific factors can help improve prognosis. However, there are some limitations in this study. We did not measure inflammatory biomarkers [e.g., C-reactive protein (CRP)], which limits our ability to disentangle the effects of inflammation from ALB; future studies should correlate ALB with inflammatory indices when modeling malnutrition risk. The sample size was relatively small, and the impact of different treatment approaches on nutritional status, particularly the effect of specific drug regimens on gut microbiota, was not fully explored. Further research with larger and multicenter cohorts is needed to validate and expand these findings.

Conclusions

This study identified gut microbiota imbalance, smoking, low household income, older age, low BMI, and low serum ALB as independent risk factors for malnutrition in patients with severe pneumonia. Based on these variables, we developed a nomogram with excellent discrimination and calibration that may assist clinicians in early identification of high-risk patients and in tailoring individualized EN strategies. Targeted nutritional interventions addressing these risk factors could improve prognosis, enhance recovery, and reduce complications.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1225/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1225/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1225/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1225/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of Taizhou Affiliated Hospital of Nanjing University of Chinese Medicine (ethics approval No. 20250425). Informed consent was obtained from all individual participants included in the study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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