Nutritional Status and Clinical Outcomes of Adult Intensive Care Unit(ICU) Patients -- a systematic review and Meta-analysis

Nutritional Status and Clinical Outcomes of Adult Intensive Care Unit(ICU) Patients -- a systematic review and Meta-analysis | 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 Systematic Review Nutritional Status and Clinical Outcomes of Adult Intensive Care Unit(ICU) Patients -- a systematic review and Meta-analysis Misrak Weldeyohannes Menchamo, Zelalem Debebe, Zewetir Abebe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7976948/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The severity of the illness and the inability to eat while in the intensive care unit put ICU patients at a high risk of malnutrition. Nutritional status assessment is vital for managing patients’ morbidity, length of stay, and mortality. This systematic review and meta-analysis aimed to assess the nutritional status of adult ICU patients and evaluate the influence of malnutrition on clinical outcomes. Methods The meta-analysis included studies focusing on nutritional status in adult ICU patients. The data extraction comprised the author's name, year of publication, sample size, and nutritional assessment tool used to classify patients as well-nourished and malnourished. Statistical analysis was performed using STATA 17 to determine the prevalence of overall malnutrition among the ICU patients, and a forest plot was generated to visually depict the pooled estimate and individual study results. Results: 31 articles were included in this meta-analysis with a sample size of 21,413 patients. The overall mortality was 1.446 (95% CI: 0.761 - 2.130), and those who were undernourished had a 44.6% increased risk of passing away. In addition, malnourished patients required 5.593 more days of ICU stay on average with a 95% confidence interval of [2.920, 8.265], a Z-value of 4.10, and a p-value of 0.0000; the pooled effect size of malnutrition was 32.74 (95% confidence interval: 19.9 to 45.5). Conclusion Malnutrition is prevalent among adult ICU patients, with wide variation across studies, and the situation gets worse after admission. Also, malnourished patients are having longer hospital stays and are more likely to die compared to well-nourished patients. Critical Care & Emergency Medicine Malnourished well nourished ICU length of stay in ICU Mortality Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction The nutritional status of patients in the intensive care unit (ICU) plays a crucial role in their ability to recover from critical illnesses, and achieve positive clinical outcomes [ 1 ]. This is because nutrition and disease are closely interconnected [ 2 ]. Adequate nutrition intervention has shown to attenuate metabolic response to stress and favorably modulate immune responses. Nutritional support in critically ill patients prevents further metabolic deterioration and loss of lean body mass[ 3 ]. The amount and type of nutrients consumed are tightly linked to the metabolic stage and the immune health and thus, inappropriate nutrient consumption is associated with development of major human diseases due to an immune system not properly functioning[ 4 ]. Protein-calorie malnutrition can lead to impaired cell-mediated immunity, reduced T-lymphocyte counts, and altered cytokine production[ 5 ].For instance, tailored nutritional strategies designed to meet the individual caloric and protein requirements of patients can enhance immune function and promote faster recovery from acute illnesses [ 15 ]. In critically ill patients, it is common for their nutritional status to rapidly decline after being admitted to the ICU[ 11 ]. This is often due to the body breaking down proteins as a result of pro-inflammatory and stress-related substances, even if the patient was previously well-nourished. Research has shown that during a 10-day stay in the ICU, patients can lose anywhere from 10% to 25% of their body protein, particularly those with multiple organ dysfunction syndrome [ 12 ]. Malnutrition is associated with higher mortality rates and increased complications and found to have a 28-day mortality rate that is significantly higher than their well-nourished counterparts during hospitalization[ 6 , 7 ].The study found that the mean length of stay for patients with malnutrition was extended by 1.1 to 12.8 days depending on the diagnosis-related group[ 8 ]. Another study reported an increased hospital stay of 1.43 days on average for malnourished patients [ 9 ].Research indicates a significant correlation between early and appropriate nutritional support and a reduction in infections, delayed wound healing, and muscle wasting—factors known to prolong ICU stays for critically ill patients. [ 14 ]. Malnutrition significantly raises healthcare costs. A study indicated that patients with malnutrition incurred excess costs of approximately $ 1,738 to $ 3,557 per patient, with even higher costs associated with complications—up to $ 6,157 when complications occurred[ 8 ].Patients receiving nutritional support also had 2.5 more life days without complications during the modelled time[ 10 ]. Nutritional management in the ICU setting is a complex challenge that requires a multi-disciplinary approach. Barazzoni et al. (2020) identified three major challenges: lack of knowledge and skills among healthcare professionals, lack of agreement on how to provide optimal nutrition, and cost of providing nutrition[ 11 ]. The problem of nutrition management in the Intensive Care Unit (ICU) is a growing concern due to the increased rate of malnourishment in ICU patients. As indicated by R Dhaliwal et al. in their 2017 study published in Nutrition in Clinical Practice, malnourishment can increase the risk of morbidity and mortality in ICU patients, resulting in an increase in the length of their stay and a rise in healthcare costs. The purpose of this meta-analysis and comprehensive review is to identify the overall nutritional status of intensive care unit patients and evaluate how it affects their outcomes. 2. Materials and methods A systematic review and meta-analysis was done on observational and RCTstudies aimed to assess nutritional status and clinical outcomes of adult ICU patients. Search strategy Articles published from January 2012 to June 1, 2024were searched electronically from four databases, pub med, science direct,Scopus, and Google scholar. The search was to assess the nutritional status of adult ICU patients at admission, and determine its association with clinical outcomes on the different group of patients. Inclusion and exclusion criterion Thesystematic review included papers focusing on adult ICU patients’ nutritional status,and clinical outcomes. The review included studies with a prospective cohort, cross-sectional, case control, and RCT design and adult ICU patients only. Literatures older than January 2012, as well as those which did not measure treatmentoutcome after assessing nutritional status at admission were excluded. Data extraction The author's name, year of publication, study design, sample size, and nutritional assessment tool used to classify patients as well-nourished and malnourished were extracted from the studies that met the inclusion criteria. Moreover, the proportion of malnourished patients, length of stay (mean ± SD),disease severity measurement tools, and proportion of mortality among malnourished patients were also extracted for the systematic review and meta-analysis. Statistical analysis The prevalence of overall malnutrition among ICU patients was analyzed using STATA 17 to determine the effect size and heterogeneity across studies. A forest plot was generated to visually depict the pooled estimate and individual study results. Also, significant heterogeneity was assessed using the I^2 statistic. Next, the two malnutrition categories - moderate and severe - were analyzed in stratification. The distribution and weight proportions of moderately and severely malnourished patients were visualized using Python. To assess the impact of malnutrition on clinical outcomes, length of stay in the ICU was declared with pre-computed effect size of moderately and severely malnourished patients. A forest plot was generated in STATA 17 to determine the effect size and 95% confidence intervals.Finally, the distribution of mortality rates was compared between well-nourished and malnourished patients. Python was used to create visualizations illustrating the differences in mortality between the two groups.By employing these statistical techniques and data visualization methods, themetaanalysis wasable to comprehensively analyze the prevalence, severity, and association of malnutrition on ICU patients. The forest plots generated using STATA 17 provided a concise summary of the effect sizes, while the Python visualizations offered an intuitive way to explore the distributions and proportions of malnutrition status and mortality rates. 3. Results 3.1 Study selection The literature search generated20389articlesfrom which 4456 duplicates were removed as provided under Fig. 1 . The duplicates included articles with similar methodology and subject characteristics. The screening based on article title and abstract generated 8325 papers for full text review, but 8294 papers removed for not meeting the inclusion criteria as indicated in Fig. 1 .Finally, 31 papers were includedfor qualitative and quantitative synthesis(figure-1). 3.2 Characteristics of the studies The total sample size across all the studies mentioned in the search results was 21,413 ICU patients. The studies cover a wide range of sample sizes, from as low as 57 patients to as high as 6,518 patients. Most studies had sample sizes between 100 to 1,000 patients. The majority of the studies were prospective cohort studies (16 studies).There were also 4 retrospective studies, 3 cross-sectional studies, and 3 randomized controlled trials. The mean age of patients across the studies ranged from 36.0 to 74.2 years old. Most studies included both medical and surgical ICU patients (19 studies).A few studies focused on specific patient populations like COVID-19 patients (2 studies), trauma patients (1 study), and kidney injury patients (1 study). Details of the variables are shown in Table 1 . Measurement of Disease Severity: The two most frequently employed measures of illness severity were APACHE II, which was utilized in 19 studies, and SOFA, which was used in 9 studies. Additionally, a small number of studies incorporated alternative scores, such as the Charlson Comorbidity Index and predicted mortality risk. Assessment Tools to Measure Nutritional Status in ICU: The Subjective Global Assessment (SGA) was the most frequently used tool (16 studies).Other tools included NRS-2002 (5 studies), mNUTRIC score (7 studies), and various anthropometric and laboratory methods. Outcome Measures: The primary outcome measures evaluated in this meta-analysis were the length of stay in the intensive care unit (ICU) and mortality rates within the ICU. Additionally, some investigations also examined the length of time patients’ required mechanical ventilation, the length of stay in the hospital, rates of readmission, and long-term outcomes such as disability and quality of life. 3.3 Quality of articles The assessment of the study quality using the NOS indicates that most of the studies inthis meta-analysis, which asses nutritional risk in critically ill patients exhibited good to excellent quality in their design and reporting. The majority of studies effectively addressed selection bias, comparability of cohorts, and the assessment of outcomes, making their findings more reliable and applicable to clinical practice. However, some studies showed room for improvement, particularly in the clarity and reliability of outcome measures. Overall, the findings suggest a strong foundation for further understanding of the impact of nutritional risk on clinical outcomes in critically ill patients, with implications for future research and clinical interventions. The total scores for the studies ranged from 6 to 8. Table 2shows the detail information of the studies. Table 2 The Newcastle-Ottawa Scale (NOS)Quality Assessment of Included Studies. Study Selection (0–4) Comparability (0–2) Outcome (0–3) Total Score (0–9) Charles Chin Han Lew et al., 2017 4 2 2 8 Sungurtekin et al., 2014 3 2 2 7 Johane P. Allard et al., 2014 4 2 2 8 Daniel Fontes et al., 2013 3 2 2 7 ChandrashishChakravarty et al., 2013 3 2 1 6 Andrés Luciano NicolásMartinuzzi et al., 2021 4 2 2 8 Patricia M. Sheean et al., 2013 3 2 2 7 Bernadette Chimera-Khombe et al., 2022 3 2 1 6 F S Caporossi et al., 2012 3 2 2 7 SavitaBector et al., 2015 3 2 2 7 Anne Coltman et al., 2015 3 2 2 7 NajmehHejazi et al., 2016 3 2 1 6 ShaahinShahbazi et al., 2021 3 2 2 7 Suzie Ferrie et al., 2022 3 2 2 7 AdityaRameshbabuDevalla et al., 2020 3 2 1 6 SornwichateRattanachaiwong et al., 2020 3 2 1 6 ParsaMohammadi et al., 2022 3 2 1 6 H. G. Valente da Silva et al., 2012 3 2 1 6 RanimKaddoura et al., 2020 3 2 1 6 Smith et al., 2015 3 2 2 7 Arabi YM et al., 2015 3 2 2 7 Michael P. Casaer et al., 2011 4 2 2 8 Thain'aGattermann Pereira et al., 2018 3 2 1 6 LS Chapple et al., 2017 3 2 2 7 Kris M. Mogensen et al., 2015 4 2 2 8 GuilhermeDupratCeniccola et al., 2020 3 2 1 6 Rosa Mendes, 2019 3 2 1 6 Na Wang et al., 2023 3 2 2 7 Manon CH de Vries, 2018 3 2 1 6 OmidMoradiMoghaddam et al., 2024 3 2 1 6 DenizAvci, 2019 3 2 1 6 3.4 publication bias The funnel plot and Egger's test results together suggest the presence of publication bias in the analyzed studies.The red dashed lines represent the 95% confidence intervals. Observations outside these lines suggest significant results.The results of Egger's test provide a statistical assessment of publication bias. The confidence interval calculated approximately (0.583,1.099).The funnel plot visually represents the relationship between the log odds ratios and their standard errors mortality among well-nourished and malnourished presented in Fig. 2 . The funnel plot of malnutrition status in ICU patients suggests potential publication bias or other types of bias.presented in Fig. 3 3.5 Nutritional status of ICU patients The nutritional status of ICU patients can be described as well-nourished and malnourished. Prevalence of malnutrition among ICU patients is significant, with a pooled effect size of 32.74 (95% confidence interval: 19.9 to 45.5). This meta-analysis provides convincing evidence that malnutrition significantly impacts adolescents, as demonstrated by the overall effect size and the statistical significance of the findings. Furthermore, the low heterogeneity indicates that the results are robust and consistent across the studies included in the analysis. 3.6 Stratified Malnutrition Status Forest plot (Fig. 5 ) shows bar comparison of moderate and severe malnutrition among the examined studies. The x-axis is the percentage of the study population that experiences malnutrition, and the y-axis is the name of the initial author and the study year. The plot proves abundance of proportions for both categories with the increased rates of malnutrition towards to the right side. From the current study, the weighted mean proportions for moderate and severe malnutrition are 36.34% and 14.91% respectively showing a lot of variability in malnutrition prevalence’s among population and methodology. 3.7 Length of stay among malnourished patients Length of stay is analyzed in 24 studies, a meta-analysis revealed the indisputable impact of malnutrition on ICU stays. Employing the REML method and a random-effects model, minimal variations between studies and no observed heterogeneity were found. Malnourished patients hospitalized in the intensive care unit for an average of 5.593 days longer, indicating significant effects. A p-value of 0.0000, a Z-value of 4.10, and a 95% confidence interval of [2.920, 8.265] all supported this. The confidence intervals and individual effect sizes showed that smaller standard errors and bigger sample sizes were more significant. Interestingly, the homogeneity test revealed no heterogeneity (p-value of 0.9993), indicating that patients who are malnourished are more likely to require lengthier stays in the intensive care unit. Figure 6: Forest plot showing length of stay in malnourished patients 3.8 Mortality of ICU PATIENTS Malnourished patients appeared to have a higher risk of death than well-nourished patients, shown by the overall mortality odds ratio of 1.446 (95% CI: 0.761–2.130). In particular, those who are malnourished had 44.6% higher risks of death. This increased mortality risk is unlikely to have occurred by accident, according to the statistically significant p-value (Prob>|z| = 0.0000). The meta-analysis provides strong evidence that higher mortality rates in the populations under study are associated with malnutrition. It is possible that the impact size is constant amongst the included studies due to the lack of significant heterogeneity (Prob > Q = 0.9995). The confidence in the estimated overall mortality odds ratio is increased by the data' homogeneity. 3.9 Mortality rate among well-nourished and malnourished ICU patients As shown in a box plot (Fig. 8 ) comparing the mortality rate between the malnourished and well-nourished patients, the fact is highlighted on how nutritional status plays out in patient survival. In the median figures it is revealed that patients who meet the definition of malnutrition have a significantly higher mortality as compared with the well-nourished ones. The mean mortality proportion of the malnourished subgroup is 30.49, which is significantly higher than the mortality proportion for well-nourished patients of 14.89. As an interesting fact, the values of the IQRs are also given, showing that they are rather close to each other, while speaking about a difference in the higher 50% of the data. As for SD, there are several varieties in both groups; however, the ‘’malnourished’’ group has one rather high outlier above 60 percent. This graphic representation clearly defines the position that diet has in determining a patients’ status as well as the fact that more research and consideration is still needed. 4. Discussion Hospital malnutrition is a major worldwide problem as it is for all hospitalized patient especially for those critically ill being admitted in ICU.[38] From the above studies, it is clear that malnutrition is a more common problem in the ICU than in other hospital wards[39]. It can be attributed to the strenuous physiological and psychological demands of the disease which thereby activate cytokines hormones and other chemical mediators. These compounds raise metabolic rate andoxidise substances such as fats and proteins,[13, 38]. The nutritional status influences the capacity to tackle over crucial circumstances and clinical consequences amid patients admitted in intensive care unit [ICU] [ 16 ]. This study also indicated that Subjective Global Assessment (SGA) was the most frequently used method for the nutritional status assessment of ICU patients for this systematic review and also for that conducted by Charles Chin Han Lew et al.,2017[40]. Additionally, the most frequently employed disease severity assessment tools in most of the studies were the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores. This finding aligns with the results reported by Charles Chin Han Lew et al., where APACHE II was the predominant scoring system used to evaluate disease severity in the included studies[41–43]. The statistics indicate a significant variability in the occurrence of malnutrition, with rates ranging from approximately 14% to over 60% for mild/moderate malnutrition, and 1.8% to 35.8% for severe malnutrition. A systematic review conducted by Alissa R Cass [ 34 ]yielded comparable findings, reporting a decline of 10% to 65% in nutritional status among ICU patients following admission. The mean duration of stay in the ICU of the mal nourished patients included in the present meta-analysis ranged from 3.0 ± 2.125 to 22.2 ± 19.5days. The results presented and discussed above are in similar with Charles Chin Han Lew et al. in 2017[45] who observed the malnutrition group had the mean length of ICU stay ranged from 0.7–28.5 days. This result of meta-analysis indicates that the ICU length of stay range is similar, therefore, the patients in both meta-analyses were similar in terms of their malnutrition status, disease severity and required a longer period of intensive care unit stay[46–48]. [ 35 – 37 ] In addition, the pooled odds ratio of the studies on the relationship between malnutrition and prolonged ICU stay was between 0.109 and 5.21. This broad range shows that, malnutrition can be related to a reduction of 10.9% up to 5.21 times the chance of the patient staying longer in the ICU[49], indicating the enormous effect it has on patients’ outcome and resource consumption in the Intensive Care Unit. Mortality rate among malnourished patients has been found to varying from as low as 7.4% to as high as 66% according to different authors, [48, 50, 51]In a study conducted by charles chin hanlew et al. (2016) the mortality rates among ICU patients was slightly lower than what was obtained in this study and range from 11.9% to 23.4%. This inconsistency may be attributed to the fact that the different characteristics of the studies that were entered into the meta-analysis analysis. Moreover, differences allow reproducing results may vary by region and countries, where the level of mortality depends on the quality of medical care. This has shed much light on the relationship between nutrition and patient outcomes, and established that different treatment measures may yield disparate consequences on patients in this setting. 5. Conclusion Malnutrition is common among hospitalized patients and even more so among ICU patients. Because critical illness consumes a large amount of energy through the physical process and also the emotions that go along with it, it can cause the body to use up what little fat and protein stores it has. Therefore, to assess the nutritional status of ICU patient this review found commonly used tool is the Subjective Global Assessment ( SGA); while APACHE II and SOFA scores are used for disease severity. Research also has shown that the general incidence of malnutrition among patients admitted to ICU is quite high ranging from as low as 13.9% to as high as 85%. In ICU patients, the average length of stay among the malnourished patients had increased odds of longer ICU stay by 5.21 times.Mortality rates have also been seen to differ with patients suffering from malnutrition in the ICU with rates recorded at between 7.4% and 66%, this numbers also demonstrate the variability of care among different setups. 6. Recommendations Based on the findings of this meta-analysis, we recommend the following strategies to enhance nutritional care for critically ill patients: Conduct periodic mandatory nutritional screening at the time of the ICU admission using scoring tools that include the Subjective Global Assessment (SGA), so that patients at high risk of being malnourished can be easily identified. Educate healthcare personnel: Train all ICU staff on the significance of nutrients in patients’ healing processes, including the identification of malnutrition. This training should encourage a culture of antecedent nutrient competencies that should help dietitians, nurses, and physicians to develop and implement nutrient care plans that would be expected according the evidential needs of the patient. Promote research: researches should be done on different aspects, energy and protein adequacy with patient outcome and creation of guidelines for the nutritional support of the patients in intensive care. This will assist in improving even the standards of the care given to this helpless group of individuals. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Contributions M W and Z D developed the protocol, reviewed the reference list, extracted data, and conducted the analyses. MW and ZA assessed the quality of the data, ensured the absence of errors and arbitrated in case of disagreement. MW and ZD developed the draft manuscript and ZD and ZA critically reviewed it. All authors have read and agreed to the published version of the manuscript. Funding The authors received no specific funding for this work. Acknowledgement We extend our gratitude to Addis Ababa University for facilitating this meta-analysis, as well as to the authors of the primary studies who generously shared the full texts of several otherwise inaccessible articles. 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Malnutrition of patients at hospital admission: prevalence and importance of early detection. Integr Food Nutr Metab. ;7 Abate HK, Kidane SZ, Feyessa YM, Gebrehawariat EG (2019) Mortality in children with severe acute malnutrition. Clin Nutr ESPEN 33:98–104 Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations The authors declare no competing interests. Supplementary Files Table1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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statuses: \"Moderate or suspected malnutrition\" and \"Severely malnourished\" for each study\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7976948/v1/e0086939a58e206504f0036e.png"},{"id":94824771,"identity":"04f8af26-e855-425a-91bb-2e59dc4e8c9c","added_by":"auto","created_at":"2025-10-31 06:49:18","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":247049,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing length of stay in malnourished patients\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7976948/v1/64a4aeaa7ef96bc4e4c969df.png"},{"id":94762654,"identity":"e39e9b2e-1163-495e-917e-e410d585ed23","added_by":"auto","created_at":"2025-10-30 12:13:19","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":335819,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the overall mortality odds ratio of malnourished patients\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7976948/v1/541719d57c7f13808a06dd05.png"},{"id":94762653,"identity":"2e4f2bcd-7898-4bdf-bb7c-18b1e5e096b1","added_by":"auto","created_at":"2025-10-30 12:13:19","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":11675,"visible":true,"origin":"","legend":"\u003cp\u003eBox plots for mortality rates for well-nourished and malnourished adult ICU patients.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7976948/v1/4d6786cc2c1e7db2b63f0ac2.png"},{"id":94985062,"identity":"0a2c2239-28c1-45cd-962e-ed3ee95674be","added_by":"auto","created_at":"2025-11-03 06:57:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3130249,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7976948/v1/b0864aad-f9e1-4868-9db6-557016c74e33.pdf"},{"id":94823841,"identity":"491a5cd6-32a6-494c-9d0f-9f6f4ac6524c","added_by":"auto","created_at":"2025-10-31 06:48:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":37804,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7976948/v1/06f40935d3a25b1c0e0172e2.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eNutritional Status and Clinical Outcomes of Adult Intensive Care Unit(ICU) Patients -- a systematic review and Meta-analysis\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe nutritional status of patients in the intensive care unit (ICU) plays a crucial role in their ability to recover from critical illnesses, and achieve positive clinical outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This is because nutrition and disease are closely interconnected [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Adequate nutrition intervention has shown to attenuate metabolic response to stress and favorably modulate immune responses. Nutritional support in critically ill patients prevents further metabolic deterioration and loss of lean body mass[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe amount and type of nutrients consumed are tightly linked to the metabolic stage and the immune health and thus, inappropriate nutrient consumption is associated with development of major human diseases due to an immune system not properly functioning[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Protein-calorie malnutrition can lead to impaired cell-mediated immunity, reduced T-lymphocyte counts, and altered cytokine production[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].For instance, tailored nutritional strategies designed to meet the individual caloric and protein requirements of patients can enhance immune function and promote faster recovery from acute illnesses [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn critically ill patients, it is common for their nutritional status to rapidly decline after being admitted to the ICU[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This is often due to the body breaking down proteins as a result of pro-inflammatory and stress-related substances, even if the patient was previously well-nourished. Research has shown that during a 10-day stay in the ICU, patients can lose anywhere from 10% to 25% of their body protein, particularly those with multiple organ dysfunction syndrome [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMalnutrition is associated with higher mortality rates and increased complications and found to have a 28-day mortality rate that is significantly higher than their well-nourished counterparts during hospitalization[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].The study found that the mean length of stay for patients with malnutrition was extended by 1.1 to 12.8 days depending on the diagnosis-related group[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Another study reported an increased hospital stay of 1.43 days on average for malnourished patients [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].Research indicates a significant correlation between early and appropriate nutritional support and a reduction in infections, delayed wound healing, and muscle wasting\u0026mdash;factors known to prolong ICU stays for critically ill patients. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMalnutrition significantly raises healthcare costs. A study indicated that patients with malnutrition incurred excess costs of approximately \u003cspan\u003e$\u003c/span\u003e1,738 to \u003cspan\u003e$\u003c/span\u003e3,557 per patient, with even higher costs associated with complications\u0026mdash;up to \u003cspan\u003e$\u003c/span\u003e6,157 when complications occurred[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].Patients receiving nutritional support also had 2.5 more life days without complications during the modelled time[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNutritional management in the ICU setting is a complex challenge that requires a multi-disciplinary approach. Barazzoni et al. (2020) identified three major challenges: lack of knowledge and skills among healthcare professionals, lack of agreement on how to provide optimal nutrition, and cost of providing nutrition[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe problem of nutrition management in the Intensive Care Unit (ICU) is a growing concern due to the increased rate of malnourishment in ICU patients. As indicated by R Dhaliwal et al. in their 2017 study published in Nutrition in Clinical Practice, malnourishment can increase the risk of morbidity and mortality in ICU patients, resulting in an increase in the length of their stay and a rise in healthcare costs. The purpose of this meta-analysis and comprehensive review is to identify the overall nutritional status of intensive care unit patients and evaluate how it affects their outcomes.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003eA systematic review and meta-analysis was done on observational and RCTstudies aimed to assess nutritional status and clinical outcomes of adult ICU patients.\u003c/p\u003e\u003cp\u003eSearch strategy\u003c/p\u003e\u003cp\u003eArticles published from January 2012 to June 1, 2024were searched electronically from four databases, pub med, science direct,Scopus, and Google scholar. The search was to assess the nutritional status of adult ICU patients at admission, and determine its association with clinical outcomes on the different group of patients.\u003c/p\u003e\u003cp\u003eInclusion and exclusion criterion\u003c/p\u003e\u003cp\u003e Thesystematic review included papers focusing on adult ICU patients\u0026rsquo; nutritional status,and clinical outcomes. The review included studies with a prospective cohort, cross-sectional, case control, and RCT design and adult ICU patients only. Literatures older than January 2012, as well as those which did not measure treatmentoutcome after assessing nutritional status at admission were excluded.\u003c/p\u003e\u003cp\u003eData extraction\u003c/p\u003e\u003cp\u003eThe author's name, year of publication, study design, sample size, and nutritional assessment tool used to classify patients as well-nourished and malnourished were extracted from the studies that met the inclusion criteria. Moreover, the proportion of malnourished patients, length of stay (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD),disease severity measurement tools, and proportion of mortality among malnourished patients were also extracted for the systematic review and meta-analysis.\u003c/p\u003e\u003cp\u003eStatistical analysis\u003c/p\u003e\u003cp\u003eThe prevalence of overall malnutrition among ICU patients was analyzed using STATA 17 to determine the effect size and heterogeneity across studies. A forest plot was generated to visually depict the pooled estimate and individual study results. Also, significant heterogeneity was assessed using the I^2 statistic.\u003c/p\u003e\u003cp\u003eNext, the two malnutrition categories - moderate and severe - were analyzed in stratification. The distribution and weight proportions of moderately and severely malnourished patients were visualized using Python.\u003c/p\u003e\u003cp\u003eTo assess the impact of malnutrition on clinical outcomes, length of stay in the ICU was declared with pre-computed effect size of moderately and severely malnourished patients. A forest plot was generated in STATA 17 to determine the effect size and 95% confidence intervals.Finally, the distribution of mortality rates was compared between well-nourished and malnourished patients. Python was used to create visualizations illustrating the differences in mortality between the two groups.By employing these statistical techniques and data visualization methods, themetaanalysis wasable to comprehensively analyze the prevalence, severity, and association of malnutrition on ICU patients. The forest plots generated using STATA 17 provided a concise summary of the effect sizes, while the Python visualizations offered an intuitive way to explore the distributions and proportions of malnutrition status and mortality rates.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Study selection\u003c/h2\u003e\n\u003cp\u003eThe literature search generated20389articlesfrom which 4456 duplicates were removed as provided under Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The duplicates included articles with similar methodology and subject characteristics. The screening based on article title and abstract generated 8325 papers for full text review, but 8294 papers removed for not meeting the inclusion criteria as indicated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.Finally, 31 papers were includedfor qualitative and quantitative synthesis(figure-1).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Characteristics of the studies\u003c/h2\u003e\n\u003cp\u003eThe total sample size across all the studies mentioned in the search results was 21,413 ICU patients. The studies cover a wide range of sample sizes, from as low as 57 patients to as high as 6,518 patients. Most studies had sample sizes between 100 to 1,000 patients. The majority of the studies were prospective cohort studies (16 studies).There were also 4 retrospective studies, 3 cross-sectional studies, and 3 randomized controlled trials. The mean age of patients across the studies ranged from 36.0 to 74.2 years old. Most studies included both medical and surgical ICU patients (19 studies).A few studies focused on specific patient populations like COVID-19 patients (2 studies), trauma patients (1 study), and kidney injury patients (1 study). Details of the variables are shown in Table\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eMeasurement of Disease Severity:\u003c/p\u003e\n\u003cp\u003eThe two most frequently employed measures of illness severity were APACHE II, which was utilized in 19 studies, and SOFA, which was used in 9 studies. Additionally, a small number of studies incorporated alternative scores, such as the Charlson Comorbidity Index and predicted mortality risk.\u003c/p\u003e\n\u003cp\u003eAssessment Tools to Measure Nutritional Status in ICU:\u003c/p\u003e\n\u003cp\u003eThe Subjective Global Assessment (SGA) was the most frequently used tool (16 studies).Other tools included NRS-2002 (5 studies), mNUTRIC score (7 studies), and various anthropometric and laboratory methods.\u003c/p\u003e\n\u003cp\u003eOutcome Measures:\u003c/p\u003e\n\u003cp\u003eThe primary outcome measures evaluated in this meta-analysis were the length of stay in the intensive care unit (ICU) and mortality rates within the ICU. Additionally, some investigations also examined the length of time patients\u0026rsquo; required mechanical ventilation, the length of stay in the hospital, rates of readmission, and long-term outcomes such as disability and quality of life.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3 Quality of articles\u003c/h2\u003e\n\u003cp\u003eThe assessment of the study quality using the NOS indicates that most of the studies inthis meta-analysis, which asses nutritional risk in critically ill patients exhibited good to excellent quality in their design and reporting. The majority of studies effectively addressed selection bias, comparability of cohorts, and the assessment of outcomes, making their findings more reliable and applicable to clinical practice. However, some studies showed room for improvement, particularly in the clarity and reliability of outcome measures. Overall, the findings suggest a strong foundation for further understanding of the impact of nutritional risk on clinical outcomes in critically ill patients, with implications for future research and clinical interventions.\u003c/p\u003e\n\u003cp\u003eThe total scores for the studies ranged from 6 to 8. Table\u0026nbsp;2shows the detail information of the studies.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe Newcastle-Ottawa Scale (NOS)Quality Assessment of Included Studies.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStudy\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSelection (0\u0026ndash;4)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eComparability (0\u0026ndash;2)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOutcome (0\u0026ndash;3)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal Score (0\u0026ndash;9)\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\"\u003e\n\u003cp\u003eCharles Chin Han Lew et al., 2017\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSungurtekin et al., 2014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eJohane P. Allard et al., 2014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDaniel Fontes et al., 2013\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChandrashishChakravarty et al., 2013\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAndr\u0026eacute;s Luciano Nicol\u0026aacute;sMartinuzzi et al., 2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePatricia M. Sheean et al., 2013\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBernadette Chimera-Khombe et al., 2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eF S Caporossi et al., 2012\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSavitaBector et al., 2015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAnne Coltman et al., 2015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNajmehHejazi et al., 2016\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eShaahinShahbazi et al., 2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSuzie Ferrie et al., 2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdityaRameshbabuDevalla et al., 2020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSornwichateRattanachaiwong et al., 2020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eParsaMohammadi et al., 2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eH. G. Valente da Silva et al., 2012\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRanimKaddoura et al., 2020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmith et al., 2015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eArabi YM et al., 2015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMichael P. Casaer et al., 2011\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThain'aGattermann Pereira et al., 2018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLS Chapple et al., 2017\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKris M. Mogensen et al., 2015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGuilhermeDupratCeniccola et al., 2020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRosa Mendes, 2019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNa Wang et al., 2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eManon CH de Vries, 2018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOmidMoradiMoghaddam et al., 2024\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDenizAvci, 2019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4 publication bias\u003c/h2\u003e\n\u003cp\u003eThe funnel plot and Egger's test results together suggest the presence of publication bias in the analyzed studies.The red dashed lines represent the 95% confidence intervals. Observations outside these lines suggest significant results.The results of Egger's test provide a statistical assessment of publication bias. The confidence interval calculated approximately (0.583,1.099).The funnel plot visually represents the relationship between the log odds ratios and their standard errors mortality among well-nourished and malnourished presented in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eThe funnel plot of malnutrition status in ICU patients suggests potential publication bias or other types of bias.presented in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e3.5 Nutritional status of ICU patients\u003c/h2\u003e\n\u003cp\u003eThe nutritional status of ICU patients can be described as well-nourished and malnourished. Prevalence of malnutrition among ICU patients is significant, with a pooled effect size of 32.74 (95% confidence interval: 19.9 to 45.5). This meta-analysis provides convincing evidence that malnutrition significantly impacts adolescents, as demonstrated by the overall effect size and the statistical significance of the findings. Furthermore, the low heterogeneity indicates that the results are robust and consistent across the studies included in the analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.6 Stratified Malnutrition Status\u003c/h2\u003e\n\u003cp\u003eForest plot (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) shows bar comparison of moderate and severe malnutrition among the examined studies. The x-axis is the percentage of the study population that experiences malnutrition, and the y-axis is the name of the initial author and the study year. The plot proves abundance of proportions for both categories with the increased rates of malnutrition towards to the right side. From the current study, the weighted mean proportions for moderate and severe malnutrition are 36.34% and 14.91% respectively showing a lot of variability in malnutrition prevalence\u0026rsquo;s among population and methodology.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.7 Length of stay among malnourished patients\u003c/h2\u003e\n\u003cp\u003eLength of stay is analyzed in 24 studies, a meta-analysis revealed the indisputable impact of malnutrition on ICU stays. Employing the REML method and a random-effects model, minimal variations between studies and no observed heterogeneity were found. Malnourished patients hospitalized in the intensive care unit for an average of 5.593 days longer, indicating significant effects. A p-value of 0.0000, a Z-value of 4.10, and a 95% confidence interval of [2.920, 8.265] all supported this. The confidence intervals and individual effect sizes showed that smaller standard errors and bigger sample sizes were more significant. Interestingly, the homogeneity test revealed no heterogeneity (p-value of 0.9993), indicating that patients who are malnourished are more likely to require lengthier stays in the intensive care unit.\u003c/p\u003e\n\u003cp\u003eFigure 6: Forest plot showing length of stay in malnourished patients\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e3.8 Mortality of ICU PATIENTS\u003c/h2\u003e\n\u003cp\u003eMalnourished patients appeared to have a higher risk of death than well-nourished patients, shown by the overall mortality odds ratio of 1.446 (95% CI: 0.761\u0026ndash;2.130). In particular, those who are malnourished had 44.6% higher risks of death. This increased mortality risk is unlikely to have occurred by accident, according to the statistically significant p-value (Prob\u0026gt;|z| = 0.0000). The meta-analysis provides strong evidence that higher mortality rates in the populations under study are associated with malnutrition.\u003c/p\u003e\n\u003cp\u003eIt is possible that the impact size is constant amongst the included studies due to the lack of significant heterogeneity (Prob\u0026thinsp;\u0026gt;\u0026thinsp;Q\u0026thinsp;=\u0026thinsp;0.9995). The confidence in the estimated overall mortality odds ratio is increased by the data' homogeneity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003e3.9 Mortality rate among well-nourished and malnourished ICU patients\u003c/h2\u003e\n\u003cp\u003eAs shown in a box plot (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e) comparing the mortality rate between the malnourished and well-nourished patients, the fact is highlighted on how nutritional status plays out in patient survival. In the median figures it is revealed that patients who meet the definition of malnutrition have a significantly higher mortality as compared with the well-nourished ones. The mean mortality proportion of the malnourished subgroup is 30.49, which is significantly higher than the mortality proportion for well-nourished patients of 14.89. As an interesting fact, the values of the IQRs are also given, showing that they are rather close to each other, while speaking about a difference in the higher 50% of the data. As for SD, there are several varieties in both groups; however, the \u0026lsquo;\u0026rsquo;malnourished\u0026rsquo;\u0026rsquo; group has one rather high outlier above 60 percent. This graphic representation clearly defines the position that diet has in determining a patients\u0026rsquo; status as well as the fact that more research and consideration is still needed.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eHospital malnutrition is a major worldwide problem as it is for all hospitalized patient especially for those critically ill being admitted in ICU.[38] From the above studies, it is clear that malnutrition is a more common problem in the ICU than in other hospital wards[39]. It can be attributed to the strenuous physiological and psychological demands of the disease which thereby activate cytokines hormones and other chemical mediators. These compounds raise metabolic rate andoxidise substances such as fats and proteins,[13, 38]. The nutritional status influences the capacity to tackle over crucial circumstances and clinical consequences amid patients admitted in intensive care unit [ICU] [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study also indicated that Subjective Global Assessment (SGA) was the most frequently used method for the nutritional status assessment of ICU patients for this systematic review and also for that conducted by Charles Chin Han Lew et al.,2017[40]. Additionally, the most frequently employed disease severity assessment tools in most of the studies were the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores. This finding aligns with the results reported by Charles Chin Han Lew et al., where APACHE II was the predominant scoring system used to evaluate disease severity in the included studies[41\u0026ndash;43].\u003c/p\u003e\u003cp\u003eThe statistics indicate a significant variability in the occurrence of malnutrition, with rates ranging from approximately 14% to over 60% for mild/moderate malnutrition, and 1.8% to 35.8% for severe malnutrition. A systematic review conducted by Alissa R Cass [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]yielded comparable findings, reporting a decline of 10% to 65% in nutritional status among ICU patients following admission.\u003c/p\u003e\u003cp\u003eThe mean duration of stay in the ICU of the mal nourished patients included in the present meta-analysis ranged from 3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.125 to 22.2\u0026thinsp;\u0026plusmn;\u0026thinsp;19.5days. The results presented and discussed above are in similar with Charles Chin Han Lew et al. in 2017[45] who observed the malnutrition group had the mean length of ICU stay ranged from 0.7\u0026ndash;28.5 days. This result of meta-analysis indicates that the ICU length of stay range is similar, therefore, the patients in both meta-analyses were similar in terms of their malnutrition status, disease severity and required a longer period of intensive care unit stay[46\u0026ndash;48].\u003c/p\u003e\u003cp\u003e[\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003cspan type=\"UnderlineSmallCaps\" class=\"UnderlineSmallCaps\" name=\"Emphasis\"\u003eIn addition, the pooled odds ratio of the studies on the relationship between malnutrition and prolonged ICU stay was between 0.109 and 5.21. This broad range shows that, malnutrition can be related to a reduction of 10.9% up to 5.21 times the chance of the patient staying longer in the ICU[49], indicating the enormous effect it has on patients\u0026rsquo; outcome and resource consumption in the Intensive Care Unit.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"UnderlineSmallCaps\" class=\"UnderlineSmallCaps\" name=\"Emphasis\"\u003eMortality rate among malnourished patients has been found to varying from as low as 7.4% to as high as 66% according to different authors, [48, 50, 51]In a study conducted by charles chin hanlew et al. (2016) the mortality rates among ICU patients was slightly lower than what was obtained in this study and range from 11.9% to 23.4%. This inconsistency may be attributed to the fact that the different characteristics of the studies that were entered into the meta-analysis analysis. Moreover, differences allow reproducing results may vary by region and countries, where the level of mortality depends on the quality of medical care. This has shed much light on the relationship between nutrition and patient outcomes, and established that different treatment measures may yield disparate consequences on patients in this setting.\u003c/span\u003e\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eMalnutrition is common among hospitalized patients and even more so among ICU patients. Because critical illness consumes a large amount of energy through the physical process and also the emotions that go along with it, it can cause the body to use up what little fat and protein stores it has. Therefore, to assess the nutritional status of ICU patient this review found commonly used tool is the Subjective Global Assessment ( SGA); while APACHE II and SOFA scores are used for disease severity. Research also has shown that the general incidence of malnutrition among patients admitted to ICU is quite high ranging from as low as 13.9% to as high as 85%. In ICU patients, the average length of stay among the malnourished patients had increased odds of longer ICU stay by 5.21 times.Mortality rates have also been seen to differ with patients suffering from malnutrition in the ICU with rates recorded at between 7.4% and 66%, this numbers also demonstrate the variability of care among different setups.\u003c/p\u003e"},{"header":"6. Recommendations","content":"\u003cp\u003eBased on the findings of this meta-analysis, we recommend the following strategies to enhance nutritional care for critically ill patients:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eConduct periodic mandatory nutritional screening at the time of the ICU admission using scoring tools that include the Subjective Global Assessment (SGA), so that patients at high risk of being malnourished can be easily identified.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEducate healthcare personnel: Train all ICU staff on the significance of nutrients in patients\u0026rsquo; healing processes, including the identification of malnutrition. This training should encourage a culture of antecedent nutrient competencies that should help dietitians, nurses, and physicians to develop and implement nutrient care plans that would be expected according the evidential needs of the patient.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e Promote research: researches should be done on different aspects, energy and protein adequacy with patient outcome and creation of guidelines for the nutritional support of the patients in intensive care. This will assist in improving even the standards of the care given to this helpless group of individuals.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\u003cp\u003eNot applicable.\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\u003cp\u003e\u003ch2\u003eContributions\u003c/h2\u003e\u003cp\u003eM W and Z D developed the protocol, reviewed the reference list, extracted data, and conducted the analyses. MW and ZA assessed the quality of the data, ensured the absence of errors and arbitrated in case of disagreement. MW and ZD developed the draft manuscript and ZD and ZA critically reviewed it. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe extend our gratitude to Addis Ababa University for facilitating this meta-analysis, as well as to the authors of the primary studies who generously shared the full texts of several otherwise inaccessible articles.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\u003cp\u003eAll data generated or analyzed during this study is included in this published article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWeijs PJM, Mogensen KM, Rawn JD, Christopher KB (2019) Protein Intake, Nutritional Status and Outcomes in ICU Survivors: A Single Center Cohort Study. JCM 8:43\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWebb A (2016) Oxford textbook of critical care. Oxford University Press\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYatin Mehta (2018) Practice Guidelines for Nutrition in Critically Ill Patients: A Relook for Indian Scenario\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMunteanu C, Schwartz B (2022) The relationship between nutrition and the immune system. Front Nutr 9:1082500\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRanjit Kumar Chandra Military Strategies for Sustainment of Nutrition and Immune Function in the Field.7Nutrition and Immune Responses: What Do We Know?\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLew C, Wong G, Cheung K, Chua A, Chong M, Miller M (2017) Association between Malnutrition and 28-Day Mortality and Intensive Care Length-of-Stay in the Critically ill: A Prospective Cohort Study. Nutrients 10:10\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDidace Ndahimana E-KK Energy Requirements in Critically Ill Patients\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReilly JJ, Hull SF, Albert N, Waller A, Bringardener S (1988) Economic Impact of Malnutrition: A Model System for Hospitalized Patients. J Parenter Enter Nutr 12:371\u0026ndash;376\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRuiz AJ, Buitrago G, Rodr\u0026iacute;guez N, G\u0026oacute;mez G, Sulo S, G\u0026oacute;mez C et al (2019) Clinical and economic outcomes associated with malnutrition in hospitalized patients. Clin Nutr 38:1310\u0026ndash;1316\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u0026Aacute;lvarez-Hern\u0026aacute;ndez J Pred researchers. Prevalence and costs of malnutrition in hospitalized patients; the PREDyCES Study\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarazzoni R, Bischoff SC, Breda J, Wickramasinghe K, Krznaric Z, Nitzan D et al (2020) ESPEN expert statements and practical guidance for nutritional management of individuals with SARS-CoV-2 infection. Clin Nutr 39:1631\u0026ndash;1638\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSungurtekin H, Sungurtekin U, Oner O, Okke D (2008) Nutrition Assessment in Critically Ill Patients. Nut Clin Prac 23:635\u0026ndash;641\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAllard JP, Keller H, Jeejeebhoy KN, Laporte M, Duerksen DR, Gramlich L et al (2016) Malnutrition at Hospital Admission\u0026mdash;Contributors and Effect on Length of Stay: A Prospective Cohort Study From the Canadian Malnutrition Task Force. J Parenter Enter Nutr 40:487\u0026ndash;497\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoswami L, Chakravarty C, Hazarika B (2013) Prevalence of malnutrition in a tertiary care hospital in India. Indian J Crit Care Med 17:170\u0026ndash;173\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAndr\u0026eacute;s Luciano Nutritional risk and clinical outcomes in critically ill adult patients with COVID-19. 9;38(6):1119\u0026ndash;1125\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSheean PM, Peterson SJ, Chen Y, Liu D, Lateef O, Braunschweig CA (2013) Utilizing multiple methods to classify malnutrition among elderly patients admitted to the medical and surgical intensive care units (ICU). Clin Nutr 32:752\u0026ndash;757\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChimera-Khombe B, Barcus G, Schaffner A, Papathakis P (2022) High prevalence, low identification and screening tools of hospital malnutrition in critically- ill patients in Malawi. Eur J Clin Nutr 76:1158\u0026ndash;1164\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCaporossi FE, LA MEDICION DEL ESPESOR DEL M\u0026Uacute;SCULO ADUCTOR, DEL PULGAR COMO UN PREDICTOR DE RESULTADOS EN PACIENTES CR\u0026Iacute;TICAMENTE ENFERMOS (2012). Nutr Hosp. ;:490\u0026ndash;495\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBector S, Vagianos K, Suh M, Duerksen DR (2016) Does the Subjective Global Assessment Predict Outcome in Critically Ill Medical Patients? J Intensive Care Med 31:485\u0026ndash;489\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eColtman A, Peterson S, Roehl K, Roosevelt H, Sowa D (2015) Use of 3 Tools to Assess Nutrition Risk in the Intensive Care Unit. J Parenter Enter Nutr 39:28\u0026ndash;33\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNajmeh Hejazi1 AA 5 MD. Nutritional Assessment in Critically Ill Patients\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShahbazi S, Hajimohammadebrahim-Ketabforoush M, Vahdat Shariatpanahi M, Shahbazi E, Vahdat Shariatpanahi Z (2021) The validity of the global leadership initiative on malnutrition criteria for diagnosing malnutrition in critically ill patients with COVID-19: A prospective cohort study. Clin Nutr ESPEN 43:377\u0026ndash;382\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFerrie S, Weiss NB, Chau HY, Torkel S, Stepniewski ME (2022) Association of Subjective Global Assessment with outcomes in the intensive care unit: A retrospective cohort study. Nutr Dietetics 79:572\u0026ndash;581\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDevalla AR, Deshpande H, Ninave S, Bhaisare R (2020) Assessment of Malnutrition and Enteral Feeding Practices in Critically Ill in Neurosurgery ICU in Rural Teaching Hospital. jemds 9:2610\u0026ndash;2613\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRattanachaiwong S, Zribi B, Kagan I, Theilla M, Heching M, Singer P (2020) Comparison of nutritional screening and diagnostic tools in diagnosis of severe malnutrition in critically ill patients. Clin Nutr 39:3419\u0026ndash;3425\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohammadi P, Varpaei HA, Khafaee Pour Khamseh A, Mohammadi M, Rahimi M, Orandi A (2022) Evaluation of the Relationship between Nutritional Status of COVID-19 Patients Admitted to the ICU and Patients\u0026rsquo; Prognosis: A Cohort Study. J Nutr Metabolism 2022:1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eH G Valente da Silva Nutritional assessment associated with length of inpatients\u0026rsquo; hospital stay\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaddoura R, Shanks A, Chapman M, O\u0026rsquo;Connor S, Lange K, Yandell R (2021) Relationship between nutritional status on admission to the intensive care unit and clinical outcomes. Nutr Dietetics 78:128\u0026ndash;134\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMogensen KM, Robinson MK, Casey JD, Gunasekera NS, Moromizato T, Rawn JD et al (2015) Nutritional Status and Mortality in the Critically Ill*. Crit Care Med 43:2605\u0026ndash;2615\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCeniccola GD, Okamura AB, Sep\u0026uacute;lveda Neta JDS, Lima FC, De Santos AC, De Oliveira JA et al (2020) Association Between AND-ASPEN Malnutrition Criteria and Hospital Mortality in Critically Ill Trauma Patients: A Prospective Cohort Study. J Parenter Enter Nutr 44:1347\u0026ndash;1354\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Boulic M, Phipps R, Plagmann M, Cunningham C, Guyot G (2023) Field performance of a solar air heater used for space heating and ventilation \u0026ndash; A case study in New Zealand primary schools. J Building Eng 76:106802\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eManon CH, de Vries Nutritional assessment of critically ill patients: validation of the modified NUTRIC score\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoghaddam OM, Emam MH, Irandoost P, Hejazi M, Iraji Z, Yazdanpanah L et al (2024) Relation between nutritional status on clinical outcomes of critically ill patients: emphasizing nutritional screening tools in a prospective cohort investigation. BMC Nutr 10:69\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCass AR, Charlton KE (2022) Prevalence of hospital-acquired malnutrition and modifiable determinants of nutritional deterioration during inpatient admissions: A systematic review of the evidence. J Hum Nutr Diet 35:1043\u0026ndash;1058\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKahokehr AA, Sammour T, Wang K, Sahakian V, Plank LD, Hill AG (2010) Prevalence of malnutrition on admission to hospital \u0026ndash; Acute and elective general surgical patients. e-SPEN, the European e-Journal of Clinical. Nutr Metabolism 5:e21\u0026ndash;e25\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaraglia N, Gonzalez Campos P, Fellet A, Balaszczuk M, Arreche A, Cernadas N (2020) G. Malnutrition of patients at hospital admission: prevalence and importance of early detection. Integr Food Nutr Metab. ;7\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbate HK, Kidane SZ, Feyessa YM, Gebrehawariat EG (2019) Mortality in children with severe acute malnutrition. Clin Nutr ESPEN 33:98\u0026ndash;104\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Addis Ababa University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Malnourished, well nourished, ICU, length of stay in ICU, Mortality ","lastPublishedDoi":"10.21203/rs.3.rs-7976948/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7976948/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: The severity of the illness and the inability to eat while in the intensive care unit put ICU patients at a high risk of malnutrition. Nutritional status assessment is vital for managing patients’ morbidity, length of stay, and mortality. This systematic review and meta-analysis aimed to assess the nutritional status of adult ICU patients and evaluate the influence of malnutrition on clinical outcomes.\u003c/p\u003e\n\u003cp\u003eMethods The meta-analysis included studies focusing on nutritional status in adult ICU patients. The data extraction comprised the author's name, year of publication, sample size, and nutritional assessment tool used to classify patients as well-nourished and malnourished. Statistical analysis was performed using STATA 17 to determine the prevalence of overall malnutrition among the ICU patients, and a forest plot was generated to visually depict the pooled estimate and individual study results.\u003c/p\u003e\n\u003cp\u003eResults: 31 articles were included in this meta-analysis with a sample size of 21,413 patients. The overall mortality was 1.446 (95% CI: 0.761 - 2.130), and those who were undernourished had a 44.6% increased risk of passing away. In addition, malnourished patients required 5.593 more days of ICU stay on average with a 95% confidence interval of [2.920, 8.265], a Z-value of 4.10, and a p-value of 0.0000; the pooled effect size of malnutrition was 32.74 (95% confidence interval: 19.9 to 45.5).\u003c/p\u003e\n\u003cp\u003eConclusion\u003c/p\u003e\n\u003cp\u003eMalnutrition is prevalent among adult ICU patients, with wide variation across studies, and the situation gets worse after admission. Also, malnourished patients are having longer hospital stays and are more likely to die compared to well-nourished patients.\u003c/p\u003e","manuscriptTitle":"Nutritional Status and Clinical Outcomes of Adult Intensive Care Unit(ICU) Patients -- a systematic review and Meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 12:13:14","doi":"10.21203/rs.3.rs-7976948/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ff29cd5b-6758-4025-8205-64c77f291a7f","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57072898,"name":"Critical Care \u0026 Emergency Medicine"}],"tags":[],"updatedAt":"2025-10-30T12:13:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 12:13:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7976948","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7976948","identity":"rs-7976948","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}