Malnutrition and the Post-Acute Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 Infection: A Multi-Institutional Population-Based Propensity Score-Matched Analysis

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global health crisis, exacerbating issues like malnutrition due to increased metabolic demands and reduced intake during illness. Malnutrition, a significant risk factor, is linked to worse outcomes in patients with COVID-19, such as increased mortality and extended hospital stays. This retrospective cohort study investigated the relationship between malnutrition and clinical outcomes within 90–180 days using data obtained from the TriNetX database. Patients aged >18 years diagnosed with COVID-19 between 1 January 2022, and 31 March 2024 were enrolled in the study. The propensity score-matching (PSM) method was used to match patients with malnutrition (malnutrition group) and those without malnutrition (control group). The primary composite outcome was the cumulative hazard ratio (HR) for post-COVID-19 condition, all-cause hospitalization, and all-cause mortality between 90 days and 180 days after COVID-19 diagnosis. The secondary outcomes were the individual components of the primary outcomes. Two cohorts, each consisting of 15,004 patients with balanced baseline characteristics, were identified using PSM. During the 90–180-day follow-up period, the malnutrition group exhibited a higher incidence of all-cause hospitalization, mortality, or post-COVID-19 condition (HR = 2.315, 95% confidence interval: 2.170–2.471, p < 0.0001). Compared with patients with COVID-19 without malnutrition, those with malnutrition may be associated with a higher risk of adverse clinical outcomes.


Introduction
Coronavirus disease (COVID- 19), an acute respiratory syndrome caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has triggered a global pandemic and public health outbreak [1].As of 5 May 2024, over 700 million cases and 7 million deaths have been reported worldwide [2].The spectrum of symptoms in infected individuals varies widely; some patients remain asymptomatic, while others develop mild symptoms such as cough, chills, fever, fatigue, and dyspnea [3,4].More severe manifestations include sepsis, acute respiratory distress syndrome, heart failure, septic shock, and multi-organ dysfunction due to the acute inflammatory response [5,6].Beyond these immediate effects, approximately 10% of individuals experience long-term consequences known as the postacute sequelae of SARS-CoV-2 infection (PASC) or "long COVID."PASC can involve a range of persistent symptoms, including chronic fatigue, respiratory difficulties, cognitive impairment, and cardiovascular issues, extending for months beyond the initial recovery period [7][8][9].
Building on an understanding of the impact of COVID-19, the factors that can exacerbate the severity of the disease must be investigated.Malnutrition, which can manifest in acute, subacute, or chronic form, is one such factor.It is characterized by progressive weight loss, insufficient energy intake, muscle and fat loss, fluid accumulation, and reduced grip strength [10,11].It is a significant independent risk factor for increased morbidity and mortality across various diseases, as it leads to heightened susceptibility to infections or superinfections [12].
Malnutrition may influence the severity of COVID-19 through several mechanisms, including impairment of the immune response, increased inflammation, and delayed recovery.Deficiencies in key nutrients, such as vitamins A, C, and D, zinc, and proteinenergy malnutrition can reduce lymphocyte proliferation, impair immune function and antibody production, and weaken the mucosal barriers that are crucial for preventing pathogen entry.These deficiencies can compromise pulmonary function, which can weaken the respiratory muscles and reduce the pulmonary immune defenses, thereby facilitating more severe respiratory symptoms and extensive viral damage [10][11][12].
However, much of the existing evidence is derived from retrospective studies conducted at a single center.Therefore, more comprehensive studies with larger sample sizes are needed.This study aimed to explore the association between malnutrition and clinical outcomes in patients with SARS-CoV-2 infection over a period of 90-180 days using an international database.

Data Source
The data used in this study were collected from the TriNetX Research Network.The TriNetX database shares electronic medical record data (diagnoses, procedures, medications, laboratory values, genomic information, and types of visits) of approximately 140 million individuals at 119 healthcare organizations (HCOs) [20].Numerous observational studies have utilized the TriNetX database, particularly when conducting COVID-19 research [21][22][23][24].The TriNetX platform provides integrated tools for analyzing patient-level data and presents outcomes to researchers as consolidated reports.Considering that the data utilized from TriNetX were anonymized, written informed consent was not required.This study was approved by the Institutional Review Board of the Chi Mei Medical Center (approval no.11302-E01).

Patient Selection and Exposure
Patients aged >18 years who had more than two visits to HCOs from 1 January 2022 to 31 March 2024 and were diagnosed with COVID-19 (confirmed by a positive polymerase chain reaction test [laboratory test code with TNX: LAB:9088] or an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code U07.1) [25][26][27] were included in the study.To ensure consistency in terms of disease severity, patients who died within 90 days or were hospitalized within 7 days after contracting COVID-19 were excluded.Patients were further divided into the malnutrition and control groups based on whether they exhibited signs of malnutrition (ICD-10 cm codes: E40-E46) within 90 days before the index date.Our initial cohort from 1 January 2022 to 31 March 2024, consisted of 3,038,057 patients with COVID-19, including 23,364 with malnutrition and 3,014,693 without malnutrition (Figure 1).
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Patient Selection and Exposure
Patients aged >18 years who had more than two visits to HCOs from 1 January 2022 to 31 March 2024 and were diagnosed with COVID-19 (confirmed by a positive polymerase chain reaction test [laboratory test code with TNX: LAB:9088] or an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code U07.1) [25][26][27] were included in the study.To ensure consistency in terms of disease severity, patients who died within 90 days or were hospitalized within 7 days after contracting COVID-19 were excluded.Patients were further divided into the malnutrition and control groups based on whether they exhibited signs of malnutrition (ICD-10 cm codes: E40-E46) within 90 days before the index date.Our initial cohort from 1 January 2022 to 31 March 2024, consisted of 3,038,057 patients with COVID-19, including 23,364 with malnutrition and 3,014,693 without malnutrition (Figure 1).

Covariates
To balance the distribution between groups at baseline, we selected covariates for matching based on CDC [28].The baseline variables used to match the two study groups included (a) demographics such as age, sex, and race; (b) potential health risks linked to socioeconomic factors, including housing and financial conditions, educational attainment and literacy levels, employment status, and occupational exposure to hazards; and (c) comorbid conditions such as alcohol-related disorders, nicotine dependence, hypertension, hyperlipidemia, diabetes mellitus, neoplasms, chronic diseases of the lower

Covariates
To balance the distribution between groups at baseline, we selected covariates for matching based on CDC [28].The baseline variables used to match the two study groups included (a) demographics such as age, sex, and race; (b) potential health risks linked to socioeconomic factors, including housing and financial conditions, educational attainment and literacy levels, employment status, and occupational exposure to hazards; and (c) comorbid conditions such as alcohol-related disorders, nicotine dependence, hypertension, Life 2024, 14, 746 4 of 10 hyperlipidemia, diabetes mellitus, neoplasms, chronic diseases of the lower respiratory tract, liver diseases, chronic kidney disease, end-stage renal disease, cerebrovascular disease, heart failure, and atrial fibrillation.

Outcomes
The primary outcome of this study was a composite of all-cause hospitalization, allcause mortality, or post-COVID-19 condition.The secondary outcomes were the individual components of the primary outcome, including all-cause hospitalization, all-cause mortality, and post-COVID-19 condition.The follow-up period was 90-180 days after the index date.

Statistical Analysis
Statistical analyses were performed using the integrated functions of the TriNetX platform.The baseline characteristics of the malnutrition and control groups were expressed as the means, standard deviations, counts, and percentages.To correct imbalances in baseline covariates, a 1:1 PSM was employed.The PSM technique utilized a nearest-neighbor matching algorithm with a caliper width set at 0.1 of pooled standard deviations.Variables with a standardized difference of less than 0.1 between groups were considered adequately matched.Following PSM, the cumulative incidence of each outcome was estimated using Cox regression models and the results were expressed as hazard ratios (HRs) with 95% confidence intervals (CIs).Additionally, Kaplan-Meier curves were generated to assess the survival distributions between the groups, with significance evaluated using the log-rank test.A p value of <0.05 was considered significant.

Subgroup Analysis
Subgroup analyses were performed using a stratified approach to explore variations in outcomes based on sex, age, race, vaccination status, and the antiviral agent used.

Subgroup Analysis
The risk of the primary outcome was examined based on age, sex, race, vaccination status, and the antiviral agent used (Table 3).Subgroup analyses showed consistent results for each subgroup.In terms of the other secondary outcomes, similar trends were observed in the subgroup analyses (Table 4).

Subgroup Analysis
The risk of the primary outcome was examined based on age, sex, race, vaccination status, and the antiviral agent used (Table 3).Subgroup analyses showed consistent results for each subgroup.In terms of the other secondary outcomes, similar trends were observed in the subgroup analyses (Table 4).

Discussion
This study used a large sample size to investigate the association between malnutrition and clinical outcomes in patients with COVID-19 over a 90-180-day follow-up period.Our findings highlight that patients with COVID-19 experiencing malnutrition have a significantly higher risk of severe outcomes, including all-cause hospitalization, all-cause mortality, and post-COVID-19 condition.Notably, the effect size of all-cause mortality in the malnutrition group was fourfold higher than that in the control group, indicating a substantial impact of nutritional status on COVID-19 severity.
The underlying mechanisms by which malnutrition exacerbates COVID-19 severity involve both direct and indirect effects on patient health.Malnutrition weakens immune defense mechanisms, as evidenced by a reduced lymphocyte count and impaired phagocytic function, which are critical for combating viral infections [29,30].Deficiencies in essential proteins, vitamins, and minerals further weaken physical barriers and cellular immunity.This predisposition not only increases susceptibility to severe infections but also increases the risk of prolonged illness and complications [31][32][33][34].
Consistent with previous studies, malnutrition amplifies the severity of infectious diseases, including COVID-19 [3,12,[40][41][42][43][44].A meta-analysis of 12 studies demonstrated a similar trend, showing that malnourished patients had significantly higher odds of inhospital mortality (odds ratio = 3.43, 95% CI: 2.55-4.60)during a 90-day follow-up [45].Our study builds on these findings by including non-hospitalized patients and extending the follow-up duration, thus providing a more comprehensive view of the impact of malnutrition on COVID-19 outcomes in various settings.Additionally, our study addressed some of the limitations observed in previous studies, such as small sample sizes and short follow-up periods, by utilizing a larger and more diverse cohort with a longer observation period.This approach enhances the generalizability and applicability of our findings, suggesting robust associations across various healthcare settings and populations.
The strong association between malnutrition and adverse COVID-19 outcomes underscores the necessity of early nutritional screening and intervention in patients with COVID-19.The implementation of nutritional support strategies can potentially reduce disease severity and improve clinical outcomes.Physicians and dietitians should consider integrated care pathways that incorporate nutritional assessments and tailored interventions as part of standard care for patients with COVID-19.
Although our findings are significant, they highlight the need for further research to explore the causal relationships and effectiveness of specific nutritional interventions in improving COVID-19 prognosis.Prospective and randomized controlled trials are essential to determine the specific nutrients and dietary interventions that are most effective in mitigating the impact of malnutrition on COVID-19 severity.
This study has several strengths.First, although the existing research often relies on data from a single hospital with limited sample sizes and generalizability, our study draws from a vast and diverse population.This diversity enhances the relevance and generalizability of our findings to broader real-world settings.Second, we employed PSM to ensure comparability between the groups, effectively controlling for potential confounding factors related to the variables of interest and observed outcomes.Finally, the consistency observed across various subgroup analyses adds further credibility to our findings.
This study has some limitations.First, potential information bias and coding errors in the electronic health records database may have occurred; however, these errors were likely consistent between the groups, which minimizes their impact on our findings [46].Second, relying on ICD-10 cm codes to determine the history of malnutrition may underestimate its true prevalence.Third, although our data suggest significant associations, they do not establish causality.Fourth, due to database limitations, we could not determine the countries from which these patients originated.Finally, to control for disease severity and reduce heterogeneity, we excluded patients who were initially hospitalized and deceased within 90 days from the index date, limiting the generalizability of our findings.

Conclusions
This study demonstrated that malnutrition is associated with a significantly higher risk of all-cause hospitalization, mortality, or post-COVID-19 condition compared with the control group.Therefore, malnutrition is a potential risk factor for poor clinical outcomes in patients with COVID-19.These findings highlight the critical role of malnutrition in exacerbating the severity of COVID-19.The robustness of the data, enhanced by the large sample size and diverse patient population, provides compelling evidence supporting the integration of nutritional evaluations and interventions in the management of COVID-19.

Figure 2 .
Figure 2. Kaplan-Meier event-free curves for the primary outcome: a composite of all-cause hospitalization, all-cause mortality, or post-COVID-19 condition.

Figure 2 .
Figure 2. Kaplan-Meier event-free curves for the primary outcome: a composite of all-cause hospitalization, all-cause mortality, or post-COVID-19 condition.

Table 1 .
Baseline characteristics of the study participants before and after the implementation of propensity-score matching.
Std Diff: standardized difference.A standardized difference (Std diff) of <0.1 indicated an adequate balance between the two groups.

Table 2 .
Hazard ratios of the primary and secondary outcomes between the malnutrition group and control group.

Table 3 .
Subgroup analyses of the primary outcomes between the malnutrition and control groups.

Table 3 .
Subgroup analyses of the primary outcomes between the malnutrition and control groups.

Analyses of Primary Outcome Patients with Outcome Hazard Ratio (95% CI) p Value Malnutrition Group Control Group
CI: confidence interval; y/o: years old.

Table 4 .
Subgroup analysis of the secondary outcomes between malnutrition and control groups.