The use of prognostic nutritional index (PNI) and selected inflammatory indicators for predicting malnutrition in COVID-19 patients: A retrospective study

Development of a modified nutritional index model based on nutritional status and sarcopenia to predict long-term survival and chemotherapy benefits in elderly patients with advanced gastric cancer

BACKGROUND

Elderly patients with advanced gastric cancer have poor prognoses. This study aims to develop a prediction model for long-term survival after radical surgery and to identify patients who may benefit from chemotherapy.

METHODS

Data from 555 elderly patients with advanced gastric cancer admitted to two medical centers from 2009 to 2018 were retrospectively analyzed. Sarcopenia was combined with the Controlling Nutritional Status (CONUT) score to create a modified nutritional index (mCONUT). Cox regression analyses were used to develop a novel nomogram prediction model (mCNS) that combined mCONUT, pN, and tumor size, and its performance was further verified both internally and externally.

RESULTS

Multivariate Cox analysis revealed that tumor size, pN, and mCONUT were independent prognostic risk factors for overall survival (OS). The mCNS model showed good fit and high predictive value (AUC: training set 0.711; validation set 0.707), outperforming the pTNM model (p < 0.05). To further investigate the association between the model and adjuvant chemotherapy, we categorized the model into two risk groups: a high-risk group and a low-risk group. Further analysis revealed that, in the low-risk group, the OS and recurrence-free survival(RFS) for patients receiving adjuvant chemotherapy was significantly better than that of those who did not receive chemotherapy (p = 0.047,p = 0.019). In the high-risk group, this result was not observed (p = 0.120, p = 0.053).

CONCLUSION

The mCNS model has high predictive value in predicting long-term survival of elderly patients with advanced gastric cancer. Patients with mCNS-L were able to benefit from chemotherapy after laparoscopic radical gastrectomy.

Association between prognostic nutritional index and mortality risk in patients with community-acquired pneumonia: a retrospective study

BACKGROUND

The prognostic nutritional index (PNI), reflecting the body's immune-nutritional status, has been established as a correlate of prognosis across various diseases. However, its significance in community-acquired pneumonia (CAP) remains unclear. This study investigated the relationship between PNI and clinical outcomes in CAP patients.

METHODS

In this retrospective cohort study, we aimed to evaluate the prognostic value of the PNI in adults with CAP admitted to the ICU. Participants were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and categorized into quartiles (Q1-Q4) according to their PNI values. We employed Kaplan-Meier survival analysis, multivariate Cox regression, and restricted cubic spline (RCS) models to explore the association between PNI and the clinical outcomes of these CAP patients.

RESULTS

In this study, we included 1,608 patients with CAP. The observed 30-day and 90-day mortality rates stood at 30.85% and 39.99%, respectively. Patients with higher PNI levels exhibited a reduced risk of both 30-day and 90-day mortality. Following adjustment for confounders, PNI showed a significant negative association with 30-day mortality [HR, 0.93 (0.91-0.94), P < 0.001] and 90-day mortality [HR, 0.94 (0.92-0.95), P < 0.001]. RCS analysis revealed a consistent trend of declining all-cause mortality risk corresponding to increasing PNI values. PNI demonstrated predictive value for 30-day and 90-day mortality in CAP patients, with AUCs of 0.71 and 0.68, respectively. Combining PNI with CURB-65 enhanced the predictive value of CURB-65.

CONCLUSION

Our investigation identified a significant negative association between the PNI and the risk of mortality in patients with CAP. Additionally, the PNI demonstrated superior predictive value for mortality risk in CAP patients when compared to the CURB-65 scoring system.

A retrospective cohort study on the association between nutritional status and prognosis in COVID-19 patients with severe and critical infection

OBJECTIVE

To evaluate the relationship between nutritional scoring systems, nutritional support methods, and the prognosis of severe and critically ill patients infected with the Omicron variant of coronavirus disease 2019 (COVID-19).

METHODS

Patients with confirmed Omicron variant severe and critical COVID-19, who were admitted to Chongqing Medical University First Hospital between December 2022 and January 2023, were enrolled into this retrospective study. Clinical data of patients who survived for 28 days were compared with those who died during the same period. Nutritional status was assessed using the 2002 Nutrition Risk Screening (NRS) tool and Prognostic Nutritional Index (PNI). Factors influencing patient mortality were identified by multivariate logistic regression, and the relationship between patient nutrition and mortality as the disease progressed was illustrated using Kaplan-Meier curves. The study was registered on the ChiCTR platform (No. ChiCTR2300067595).

RESULTS

A total of 508 patients were included (349 survivors and 159 non-survivors). Significant differences were found in sex, age, NRS score, PNI score, albumin level, lymphocyte count, chronic comorbidities, mechanical ventilation, neutrophil count, procalcitonin, and platelet count between survivors and non-survivors. Multivariate analysis revealed that high NRS score (OR 3.87, 95% CI, 1.97, 7.63), fourth-level nutritional support (combined enteral and parenteral nutrition; OR 7.89, 95% CI, 1.32, 47.28), chronic comorbidities (OR 4.03, 95% CI, 1.91, 8.51), and mechanical ventilation (OR 6.03, 95% CI, 3, 12.13) were risk factors for mortality (OR > 1). The malnutrition rate among patients with NRS ≥ 3 was 41.93%. The median (interquartile range) PNI score was 38.20 (35.65, 41.25) for survivors versus 32.65 (29.65, 36.58) for non-survivors. The mortality rate was higher in patients with high nutritional risk within 28 days of hospitalization. The descending order for mortality rate in patients receiving different nutritional support was: dual parenteral and enteral nutrition, no nutritional intervention, single enteral nutrition, and single parenteral nutrition.

CONCLUSION

A high proportion of severe and critically ill patients with COVID-19 experience malnutrition, and various factors are associated with their prognosis. High nutritional risk is significantly related to patient mortality. Early assessment using NRS or PNI is crucial for these patients, and personalized interventions should be implemented to improve overall nutritional status, maintain organ function, and enhance the body's antiviral defence.

Subcutaneous adipose tissue measured by computed tomography could be an independent predictor for early outcomes of patients with severe COVID-19

Background

Patients with severe Coronavirus Disease 2019 (COVID-19) can experience protein loss due to the inflammatory response and energy consumption, impairing immune function. The presence of excessive visceral and heart fat leads to chronic long-term inflammation that can adversely affect immune function and, thus, outcomes for these patients. We aimed to explore the roles of prognostic nutrition index (PNI) and quantitative fat assessment based on computed tomography (CT) scans in predicting the outcomes of patients with severe COVID-19.

Methods

A total of 130 patients with severe COVID-19 who were treated between December 1, 2022, and February 28, 2023, were retrospectively enrolled. The patients were divided into survival and death groups. Data on chest CT examinations following admission were collected to measure cardiac adipose tissue (CAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) and to analyze the CT score of pulmonary lesions. Clinical information and laboratory examination data were collected. Univariate and multivariate logistic regression analyses were used to explore the risk factors associated with death, and several multivariate logistic regression models were established.

Results

Of the 130 patients included in the study (median age, 80.5 years; males, 32%), 68 patients died and 62 patients survived. PNI showed a strong association with the outcome of severe COVID-19 (p < 0.001). Among each part of the fat volume obtained based on a CT scan, SAT showed a significant association with the mortality of severe COVID-19 patients (p = 0.007). However, VAT and CAT were not significantly correlated with the death of patients. In the multivariate models, SAT had a higher predictive value than PNI; the area under the curve (AUC) of SAT was 0.844, which was higher than that of PNI (AUC = 0.833), but in the model of the combination of the two indexes, the prediction did not improve (AUC = 0.830), and SAT lost its significance (p = 0.069).

Conclusion

Subcutaneous adipose tissue measured by computed tomography and PNI were found to be independent predictors of death in patients with severe COVID-19.

Postoperative prognostic nutrition index predicts survival in patients with small bowel adenocarcinoma after surgical resection

BACKGROUND

Surgical resection (SR) is the main treatment for small bowel adenocarcinoma (SBA), but it increases metabolic demand, systemic inflammation, and digestive dysfunction, resulting in major impacts on the postoperative outcomes of patients. In this study, we aimed to investigate the role of the postoperative prognostic nutritional index (PNI), a surrogate marker of inflammation and nutrition, in patients with SBA after resection.

METHODS

From June 2014 to March 2022, 44 consecutive patients who underwent SR for SBA in Taipei Veterans General Hospital were retrospectively reviewed. Factors associated with survival including PNI were analyzed.

RESULTS

PNI decreased in patients after SR for SBA (median change: -1.82), particularly in those who underwent Whipple operation or developed postoperative pancreatic fistula. Postoperative PNI <45.2 best predicted overall survival (OS) (area under the receiver operating characteristic curve [AUROC]: 0.826, p = 0.001). Patients with lower postoperative PNI had significantly worse OS compared to those with higher postoperative values (median OS: 19.3 months vs not reached, p < 0.001). Low postoperative PNI (hazard ratio [HR]: 11.404, p = 0.002), tumoral lymphovascular invasion (HR: 8.023, p = 0.012), and adjuvant chemotherapy (HR: 0.055, p = 0.002) were independent risk factors for OS. Postoperative PNI also significantly predicted recurrence-free survival independent of lymphovascular invasion and adjuvant chemotherapy (HR: 6.705, p = 0.001).

CONCLUSION

PNI commonly decreases in patients with SBA who undergo Whipple surgery or develop postoperative pancreatic fistula. Postoperative PNI independently predicts survival and may serve as a clinical marker to optimize patient outcomes.

Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as potential diagnostic markers for rebleeding in patients with esophagogastric variceal bleeding

The aim of the present study is to explore the potential prediction value of neutrophil-to-lymphocyte ratio (NLR) or peripheral blood platelet-to-lymphocyte ratio (PLR) for rebleeding in patients with esophagogastric variceal bleeding (EVB). We have enrolled 80 rebleeding patients with EVB and 113 EVB patients without rebleeding in the present study. The lymphocyte, platelet counts, the PLR, and the NLR of the candidates were calculated, and receiver-operating characteristic curve was drawn to examine whether NLR or PLR is a sensitive biomarker for distinguishing rebleeding patients from the EVB patients. We observed that NLR and PLR were all significantly increased in rebleeding patients with EVB compared with the non-rebleeding patients (p < 0.01); moreover, the area under the curve of NLR and PLR was 0.7037 (95% confidence interval [CI], 0.6281-0.7792) and 0.7468 (95% CI, 0.6793-0.8144), respectively, suggesting that NLR or PLR is a sensitive biomarker for distinguishing non-rebleeding patients from the rebleeding patients. We reported that NLR and PLR were significantly increased in the peripheral blood of patient with esophagogastric variceal rebleeding, suggesting that NLR and PLR may be potential early diagnostic and prognostic markers for the rebleeding among patients with EVB.

Prognostic Nutritional Index (PNI) and Systemic Immune-Inflammatory Index (SII) as markers of severity among patients having COVID-19 infection

Background

Prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) are two novel markers that have emerged as potential candidates as an early indication of the severity of the disease in coronavirus disease 2019 (COVID-19) patients.

Objective

The objective of the study is to assess the utility of the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) as markers of severity among patients with COVID-19 infection.

Methods

This is a retrospective study conducted in a tertiary care centre in South India. A total of 80 patients diagnosed with COVID-19 were included in the study. The patients were divided into mild, moderate, and severe groups based on the clinical parameters as per Indian Council of Medical Research guidelines. Lab values taken at admission were obtained from patient records, using which the PNI and SII were calculated using standard formulae. These markers were correlated with the severity of the COVID-19 illness.

Results

PNI and SII were significantly elevated in the patients with severe COVID-19 illness as compared with mild COVID-19 illness. The mean PNI among subjects with mild COVID-19 and severe COVID-19 being 46.62 ± 6.51 and 34.09 ± 5.81, respectively. The mean SII among subjects with mild COVID-19 was 9,52,287.2 ± 1,42,113, and among subjects with severe COVID-19 was 15,39,461 ± 8,04,285. The cut-off value for PNI and SII for predicting severity of COVID-19 illness was 35.93 and 5,82,400, respectively. The sensitivity for PNI was 87.5, and the SII was 95.

Conclusion

The present study showed a significant correlation between the SII and PNI as markers used to determine the severity of COVID-19. Based on these findings, it can be effectively used independently of other markers to predict critical illness among COVID-19 patients.

Predictivity of the Prognostic Nutritional Index and Systemic Inflammation Index for All-Cause In-Hospital Mortality in Geriatric and Adult COVID-19 Inpatients

Background: The prognostic nutritional index (PNI) and the systemic immune inflammation index (SII) have been used as simple risk-stratification predictors for COVID-19 severity and mortality in the general population. However, the associations between these indices and mortality might differ due to age-related changes such as inflammaging and several comorbid conditions in older patients. Therefore, we aimed to compare the predictivity of the PNI and SII for mortality among hospitalized older patients and patients under 65 years old. Methods: Patients hospitalized with COVID-19 from March 2020 to December 2020 were retrospectively included. The PNI and SII were calculated from hospital records within the first 48 h after admission. Data were evaluated in the whole group and according to age groups (≥65 < years). Receiver operating characteristic curves were drawn to evaluate the predictivity of the PNI and SII. Results: Out of 407 patients included in this study, 48.4% (n = 197) were older patients, and 51.6% (n = 210) were under 65 years old. For mortality, the area under the curve (AUC) of the PNI and SII in the adult group (<65 years) was 0.706 (95% CI 0.583-0.828) (p = 0.003) and 0.697 (95% CI 0.567-0.827) (p < 0.005), respectively. The AUC of the PNI and SII in the older group was 0.515 (95% CI 0.427-0.604) (p = 0.739) and 0.500 (95% CI 0.411-0.590) (p = 0.993). Conclusions: The accuracy of the PNI and SII in predicting mortality in adult COVID-19 patients seemed to be fair, but no association was found in geriatric patients in this study. The predictivity of the PNI and SII for mortality varies according to age groups.

A Novel Facet of In-Hospital Food Consumption Associated with Hospital Mortality in Patients with Scheduled Admission-Addition of a Study Protocol to Test the Existence of Effects of COVID-19 in the Same Study in the Post-COVID-19 Period

BACKGROUND

Humankind has faced unexperienced pandemic events since 2020. Since the COVID-19 pandemic has calmed down, we felt the need to verify whether in-hospital mortality had worsened compared to pre-pandemic conditions due to the COVID-19 pandemic.

OBJECTIVE

To test the hypothesis that daily food consumption is associated with in-hospital mortality during hospitalization and to provide baseline data to examine whether the effects of COVID-19 exist or not in post-pandemic period.

METHODS

All hospitalized patients staying in a single institution on the third Thursday of May, August, November, and the following February were included. Compared data: (1) among four seasons, (2) between age < 75 vs. ≥75 years, (3) between <75% vs. ≥75% of in-hospital food, and (4) logistic regression analysis to identify factors associated with in-hospital mortality.

RESULTS

In 365 inpatients, the following results were obtained: (1) no seasonality or age effect in in-hospital mortality, (2) the novel cutoff value of 75% of the hospital food requirement was used to identify poor in-hospital survivors, (3) logistic regression analysis showed low food consumption, with <75% of the hospital food requirement as the predictor of high in-hospital mortality.

CONCLUSIONS

A small eater of in-hospital food < 75% during hospitalization was associated with significantly higher in-hospital mortality in patients with scheduled hospitalization in the pre-pandemic period. Then, a study protocol is proposed to test the existence of the effects of COVID-19 in the same study in the post-COVID-19 period. This study protocol is, to our knowledge, the first proposal to test the effects of food consumption in the post-COVID-19 period on in-hospital mortality in the clinical nutritional areas.

The prognostic value of prognostic nutritional index and renal function indicators for mortality prediction in severe COVID-19 elderly patients: A retrospective study

Identifying prognostic factors in elderly patients with severe coronavirus disease 2019 (COVID-19) is crucial for clinical management. Recent evidence suggests malnutrition and renal dysfunction are associated with poor outcome. This study aimed to develop a prognostic model incorporating prognostic nutritional index (PNI), estimated glomerular filtration rate (eGFR), and other parameters to predict mortality risk. This retrospective analysis included 155 elderly patients with severe COVID-19. Clinical data and outcomes were collected. Logistic regression analyzed independent mortality predictors. A joint predictor "L" incorporating PNI, eGFR, D-dimer, and lactate dehydrogenase (LDH) was developed and internally validated using bootstrapping. Decreased PNI (OR = 1.103, 95% CI: 0.78-1.169), decreased eGFR (OR = 0.964, 95% CI: 0.937-0.992), elevated D-dimer (OR = 1.001, 95% CI: 1.000-1.004), and LDH (OR = 1.005, 95% CI: 1.001-1.008) were independent mortality risk factors (all P < .05). The joint predictor "L" showed good discrimination (area under the curve [AUC] = 0.863) and calibration. The bootstrapped area under the curve was 0.858, confirming model stability. A combination of PNI, eGFR, D-dimer, and LDH provides useful prognostic information to identify elderly patients with severe COVID-19 at highest mortality risk for early intervention. Further external validation is warranted.

Predicting COVID-19 Re-Positive Cases in Malnourished Older Adults: A Clinical Model Development and Validation

Purpose

Building and validating a clinical prediction model for novel coronavirus (COVID-19) re-positive cases in malnourished older adults.

Patients and Methods

Malnourished older adults from January to May 2023 were retrospectively collected from the Department of Geriatrics of the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine. They were divided into a "non-re-positive" group and a "re-positive" group based on the number of COVID-19 infections, and into a training set and a validation set at a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify predictive factors for COVID-19 re-positivity in malnourished older adults, and a nomogram was constructed. Independent influencing factors were screened by multivariate logistic regression. The model's goodness-of-fit, discrimination, calibration, and clinical impact were assessed by Hosmer-Lemeshow test, area under the curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve analysis (CIC), respectively.

Results

We included 347 cases, 243 in the training set, and 104 in the validation set. We screened 10 variables as factors influencing the outcome. By multivariate logistic regression analysis, preliminary identified protective factors, risk factors, and independent influencing factors that affect the re-positive outcome. We constructed a clinical prediction model for COVID-19 re-positivity in malnourished older adults. The Hosmer-Lemeshow test yielded χ2 =5.916, P =0.657; the AUC was 0.881; when the threshold probability was >8%, using this model to predict whether malnourished older adults were re-positive for COVID-19 was more beneficial than implementing intervention programs for all patients; when the threshold was >80%, the positive estimated value was closer to the actual number of cases.

Conclusion

This model can help identify the risk of COVID-19 re-positivity in malnourished older adults early, facilitate early clinical decision-making and intervention, and have important implications for improving patient outcomes. We also expect more large-scale, multicenter studies to further validate, refine, and update this model.

Nutritional status of elderly patients previously ill with COVID-19: Assessment with nutritional risk screening 2002 (NRS-2002) and mini nutritional assessment (MNA-sf)

BACKGROUND

Long-term effects of COVID-19 showed a wide range of symptoms. Also, it was found that older patients were five times more likely than younger patients to develop long-COVID symptoms (1). This study aimed to investigate the use of Nutrition Risk Screening 2002 (NRS-2002) and the Mini Nutrition Assessment-Short Form (MNA-sf) among COVID-19 in elderly patients in Saudi Arabia.

METHODS

A total of (n = 159) COVID-19 elderly patients were recruited in the study; the relationship between patients' characteristics, including age, gender, Body Mass Index (BMI), infection history, vaccination and chronic disease were evaluated using NRS-2002 and MNA-sf. Multivariate logistic regression to estimate the Odd Ratio (OR) by comparing the OR of different variables between normal nutritional Status and at-risk and Cohen's kappa (κ) coefficient was assessed to analyse the agreement between both tools.

RESULTS

MNA-sf showed a positive association between age and malnutrition risk ≥ 66 years old P = 0.035. Both tools showed a negative association between BMI (P < 0.001 and P = 0.046), respectively and vaccination (P = 0.002 and P = 0.01), respectively, with risk for malnutrition. There was no significant association between Diabetes (DM) and malnutrition risk, but elderly Cardiovascular Disease (CVD) were at malnutrition risk using the NRS- 2002 tool P = 0.003. Inversely, people infected six months or more before malnutrition assessment have a lower risk of malnutrition P = 0.05.

CONCLUSIONS

Both tools were valuable and practical tools for screening elderly people with COVID-19 who are at nutritional risk and those in need of additional nutritional intervention. Further research needed to be applied in the relationship between nutritional status during and post-infectious disease for elderly people using cross-sectional and intervention studies in order to prevent malnutrition complications in Saudi Arabia.