Do prior neurological comorbidities predict COVID-19 severity and death? A 25-month cross-sectional multicenter study on 7370 patients

BACKGROUND

The prognosis of COVID-19 cases that suffer from particular comorbidities is worse. The impact of chronic neurological disorders (CNDs) on the outcome of COVID-19 patients is not clear yet. This study aimed to assess whether CNDs can predict in-hospital mortality or severity in COVID-19 patients.

METHODS

Following a cross-sectional design, all consecutive hospitalized patients with PCR-confirmed COVID-19 who were hospitalized at three centers from February 20th, 2020 to March 20th, 2022, were studied. CND was defined as neurological conditions resulting in permanent disability. Data on demographic and clinical characteristics, COVID-19 severity, treatment, and laboratory findings were evaluated. A multivariate Cox-regression log-rank test was used to assess the primary outcome, which was in-hospital all-cause mortality. The relationship among CND, COVID-19 severity and abnormal laboratory findings was analyzed as a secondary endpoint.

RESULTS

We studied 7370 cases, 43.6% female, with a mean age of 58.7 years. 1654 (22.4%) patients had one or more CNDs. Patients with CNDs had higher age, were more disabled at baseline, and had more vascular risk factors and comorbidities. The ICU admission rate in CND patients with 59.7% was more frequent than the figure among non-CND patients with 20.3% (p = 0.044). Mortality of those with CND was 43.4%, in comparison with 12.8% in other participants (p = 0.005). Based on the Cox regression analysis, CND could independently predict death (HR 1.198, 95% CI 1.023-3.298, p = 0.003).

CONCLUSION

CNDs could independently predict the death and severity of COVID-19. Therefore, early diagnosis of COVID-19 should be considered in CND patients.

Association of preoperative nutritional status evaluated by the controlling nutritional status score with walking independence at 180 days postoperatively: a prospective cohort study in Chinese older patients with hip fracture

BACKGROUND

Malnutrition is significantly associated with unfavorable outcomes, but there is little high-level evidence to elucidate the association of malnutrition with losing walking independence (LWI) after hip fracture surgery. This study aimed to assess the association between preoperative nutritional status evaluated by the Controlling Nutritional Status (CONUT) score and walking independence at 180 days postoperatively in Chinese older hip fracture patients.

METHODS

This prospective cohort study included 1958 eligible cases from the SSIOS database. The restricted cubic spline was used to assess the dose-effect relationship between the CONUT score and the recovery of walking independence. Propensity score matching was performed to balance potential preoperative confounders, and multivariate logistic regression analysis was applied to assess the association between malnutrition and LWI with perioperative factors for further adjustment. Furthermore, inverse probability treatment weighting and sensitivity analyses were performed to test the robustness of the results and the Fine and Gray hazard model was applied to adjust the competing risk of death. Subgroup analyses were used to determine potential population heterogeneity.

RESULTS

The authors found a negative relationship between the preoperative CONUT score and recovery of walking independence at 180 days postoperatively, and that moderate-to-severe malnutrition evaluated by the CONUT score was independently associated with a 1.42-fold (95% CI, 1.12-1.80; P =0.004) increased risk of LWI. The results were overall robust. And in the Fine and Gray hazard model, the result was still statistically significant despite the apparent decrease in the risk estimate from 1.42 to 1.21. Furthermore, significant heterogeneities were observed in the subgroups of age, BMI, American Society of Anesthesiologists score, Charlson's comorbidity index, and surgical delay ( P for interaction < 0.05).

CONCLUSION

Preoperative malnutrition is a significant risk factor for LWI after hip fracture surgery, and nutrition screening on admission would generate potential health benefits.

Association between malnutrition and stroke-associated pneumonia in patients with ischemic stroke

BACKGROUND

Malnutrition is associated with a high risk of mortality in adults with ischemic stroke (IS). This study aimed to investigate the relationship between malnutrition and the risk of stroke-associated pneumonia (SAP) as only a few studies examined the relationship between malnutrition and the risk of SAP in IS.

METHODS

Patients were included from emergency departments of five tertiary hospitals in the REtrospective Multicenter study for Ischemic Stroke Evaluation (REMISE) study from January 2020 to December 2020. Malnutrition was defined according to the Controlling Nutritional Status (CONUT), Geriatric Nutritional Risk Index (GNRI), and Prognostic Nutritional Index (PNI) systems. Multivariable logistic regression analysis was used to explore the association between malnutrition and risk of SAP.

RESULTS

We enrolled 915 patients with IS, 193 (14.75%), 495 (54.1%), and 148 (16.2%) of whom were malnourished according to the PNI, CONUT, and GNRI scores, respectively. SAP occurred in 294 (32.1%) patients. After adjusting for confounding influencing factors in the logistic regression analysis, malnutrition (moderate and severe risk vs. absent malnutrition) was independently associated with an increased risk of SAP based on the PNI (odds ratio [OR], 5.038; 95% confidence interval [CI] 2.435-10.421, P < 0.001), CONUT (OR, 6.941; 95% CI 3.034-15.878, P < 0.001), and GNRI (OR, 2.007; 95% CI 1.186-3.119, P = 0.005) scores. Furthermore, adding malnutrition assessment indices to the A2DS2 score significantly improved the ability to predict SAP by analysis of receiver operating characteristic curves and net reclassification improvement.

CONCLUSION

Malnutrition was notably prevalent in patients with IS and independently associated with an increased risk of SAP. Further studies are required to identify the effect of interventions on malnutrition to reduce the risk of SAP.

Controlling Nutritional Status (CONUT) score and the risk of mortality or impaired physical function in stroke patients: A systematic review and meta-analysis

AIMS

The Controlling Nutritional Status (CONUT) score is a tool for assessing the risk of malnutrition (undernutrition) that can be calculated from albumin concentration, total peripheral lymphocyte count, and total cholesterol concentration. CONUT score has been proposed as a promising prognostic marker in several clinical settings; however, a consensus on its prognostic value in patients with stroke is lacking. The aim of this systematic review and meta-analysis was to evaluate the relationship between CONUT score and clinical outcomes in patients with stroke based on all current available studies.

DATA SYNTHESIS

Systematic research on PubMed, Scopus and Web of Science from inception to February 2023 was performed on the association between CONUT score and clinical outcomes in patients with stroke. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses were followed. Methodological quality was evaluated using the Newcastle-Ottawa Scale quality assessment tool. Pooled effect estimation was calculated by a random-effect model. Through the initial literature search, 15 studies (all high-quality) including 16 929 patients were found to be eligible and analysed in the meta-analysis. A significant risk of malnutrition (in most studies defined by a CONUT score ≥5) was directly associated with mortality, higher risk of poor functional outcome according to the modified Rankin Scale and total infection development. Evidence was consistent for acute ischaemic stroke and preliminary for acute haemorrhagic stroke.

CONCLUSION

CONUT score is an independent prognostic indicator, and it is associated with major disability and infection development during hospitalisation.

PROSPERO ID

CRD42022306560.

The association between malnutrition status and hemorrhagic transformation in patients with acute ischemic stroke receiving intravenous thrombolysis

OBJECTIVES

We evaluated the impact of malnutrition as estimated by the controlling nutritional status (CONUT) score and prognostic nutritional index (PNI) on hemorrhagic transformation (HT) and stroke outcomes after intravenous thrombolysis (IVT).

MATERIALS AND METHODS

Using a multicenter registry database, we enrolled 808 patients with acute ischemic stroke who received IVT between August 2013 and May 2021. We defined malnutrition as a CONUT score ≥ 2 and low PNI. The primary outcome measure was the occurrence of symptomatic HT contributing to early neurologic deterioration (END-SHT) after IVT. Multivariable analysis was performed to analyze the association between CONUT score, PNI, and END-SHT after IVT.

RESULTS

The rate of END-SHT was higher with increasing CONUT scores and PNI values. In the multivariable analysis, CONUT score ≥ 5 and low PNI were significantly associated with END-SHT (odds ratio [95% confidence interval], CONUT score ≥ 5: 12.23 [2.41-62.07], p = 0.003; low PNI: 4.98 [1.76-14.09], p = 0.003). The receiver operating characteristic curve showed that both the CONUT score and PNI had good predictive ability. The cutoff values for CONUT and PNI were 5 and 42.3, respectively, for END-SHT.

CONCLUSION

Malnutrition, as denoted by a higher CONUT score and lower PNI, was associated with END-SHT. The joint application of both nutritional markers could be useful in predicting END-SHT after IVT.

The controlling nutritional status score and risk factors associated with malnutrition in patients with acute ischemic stroke

Objectives

Malnutrition is an independent risk factor for poor outcomes in patients who suffered an acute ischemic stroke (AIS). The controlling nutritional status (CONUT) score can provide information for nutritional management in AIS patients. However, the risk factors associated with the CONUT score have not been established to date. Therefore, in this study, we aimed to investigate the CONUT score of patients with AIS and explore the potential risk factors associated with it.

Methods

We conducted a retrospective review of the data from consecutive AIS patients who were recruited in the CIRCLE study. Within 2 days of admission, we gathered the CONUT score, the Nutritional Risk Screening 2002, the Modified Rankin Scale, the National Institutes of Health Neurological Deficit Score (NIHSS), and demographic data from medical records. We used chi-squared tests to examine admission, and a logistic regression analysis was performed to explore the risk factors associated with CONUT in patients with AIS.

Results

A total of 231 patients with AIS participated in the study, with a mean age of 62.32 ± 13.0 years and a mean NIHSS of 6.77 ± 3.8. Of these patients, 41(17.7%) had hyperlipidemia. In terms of nutritional assessment, 137(59.3%) patients with AIS had high CONUT scores, 86(37.2%) patients with AIS had low or high BMI, and 117(50.6%) patients with AIS had NRS-2002 scores below 3. The chi-squared tests showed that age, NIHSS, body mass index (BMI), and hyperlipidemia were associated with the CONUT score (P &lt; 0.05). The logistic regression analysis showed that low NIHSS scores (OR = 0.055 95% CI: 0.003–0.893), younger age (OR = 0.159 95% CI: 0.054–0.469), and hyperlipidemia (OR = 0.303 95% CI: 0.141–0.648) were independently associated with lower CONUT scores (P &lt; 0.05), whereas BMI was not found to be independently associated with the CONUT.

Conclusions

More than half of the patients with AIS were at risk of malnutrition, with age and neurological deficits being identified as risk factors for nutritional control. Hyperlipidemia was found to be a protective factor of the CONUT, while NRS-2002 and BMI did not affect the nutritional control in patients with AIS.

The Assessment of the Risk of Malnutrition (Undernutrition) in Stroke Patients

Malnutrition is common in stroke patients, as it is associated with neurological and cognitive impairment as well as clinical outcomes. Nutritional screening is a process with which to categorize the risk of malnutrition (i.e., nutritional risk) based on validated tools/procedures, which need to be rapid, simple, cost-effective, and reliable in the clinical setting. This review focuses on the tools/procedures used in stroke patients to assess nutritional risk, with a particular focus on their relationships with patients' clinical characteristics and outcomes. Different screening tools/procedures have been used in stroke patients, which have shown varying prevalence in terms of nutritional risk (higher in rehabilitation units) and significant relationships with clinical outcomes in the short- and long term, such as infection, disability, and mortality. Indeed, there have been few attempts to compare the usefulness and reliability of the different tools/procedures. More evidence is needed to identify appropriate approaches to assessing nutritional risk among stroke patients in the acute and sub-acute phase of disease or during rehabilitation; to evaluate the impact of nutritional treatment on the risk of malnutrition during hospital stay or rehabilitation unit; and to include nutritional screening in well-defined nutritional care protocols.

Relationship between initial nutritional status and functional independence measures at discharge in subacute stroke

OBJECTIVE

This retrospective study examined the association between nutritional status at admission and functional independence measure (FIM™) at discharge.

MATERIALS AND METHODS

This study included 205 patients, aged ≥ 65, discharged from a convalescent ward between April 2017 and March 2018. The primary outcome was discharge FIM^TM, and the secondary outcomes were the length of stay (LOS) and FIM efficiency. The explanatory variables included demographic data, stroke type, admission FIM^TM, body mass index (BMI), controlling nutritional status (CONUT), and Geriatric Nutritional Risk Index (GNRI). Patients were divided into three groups based on BMI and GNRI scores and four groups based on the CONUT score. Univariate and multiple regression analyses were performed to predict discharge FIM^TM. Kruskal-Wallis and Dunn's tests were also performed for intergroup comparisons.

RESULTS

In the univariate analyses, age, sex, onset-to-admission interval, admission FIM^TM, GNRI, and BMI (all factors were p<0.001) were significant explanatory variables for discharge FIM^TM. In the multiple linear regression analysis, admission FIM^TM, LOS, age, and onset-to-admission interval were significant explanatory variables (adjusted R² = 0.791; p<0.001). Although those with poor nutritional status required a longer hospital stay, they achieved the same FIM gain as those without poor nutritional status.

CONCLUSIONS

Nutritional status on admission did not affect the FIM^TM at discharge in the convalescent ward. Patients with subacute stroke require adequate rehabilitation regardless of their nutritional status.

Association between malnutrition risk and hemorrhagic transformation in patients with acute ischemic stroke

Background and aims

Malnutrition is a prevalent problem occurring in different diseases. Hemorrhagic transformation (HT) is a severe complication of acute ischemic stroke (AIS). Few studies have evaluated the association between malnutrition risk and hemorrhagic transformation in patients with acute stroke. We aim to investigate the influence of malnutrition risk on the risk of hemorrhagic transformation in patients with AIS.

Methods

A total of 182 consecutive adults with HT and 182 age- and sex-matched patients with stroke were enrolled in this study. The controlling nutritional status (CONUT) score was calculated to evaluate the malnutrition risk. HT was detected by follow-up imaging assessment and was radiologically classified as hemorrhagic infarction type 1 or 2 or parenchymal hematoma type 1 or 2. Logistic regression models were conducted when participants were divided into different malnutrition risk groups according to the objective nutritional score to assess the risk for HT.

Results

The prevalence of moderate to severe malnutrition risk in patients with AIS was 12.5%, according to the CONUT score. Univariate analysis showed that the CONUT score is significantly higher in patients with HT than those without HT. After adjusting for potential covariables, the patients with mild risk and moderate to severe malnutrition risk were associated with a higher risk of HT compared to the patients in the normal nutritional status group [odds ratio, 3.180 (95% CI, 1.139–8.874), P = 0.027; odds ratio, 3.960 (95% CI, 1.015–15.453), P = 0.048, respectively].

Conclusion

Malnutrition risk, measured by CONUT score, was significantly associated with an increased risk of hemorrhagic transformation in patients with AIS.

Prognostic Potential of the Controlling Nutritional Status (CONUT) Score in Predicting All-Cause Mortality and Major Adverse Cardiovascular Events in Patients With Coronary Artery Disease: A Meta-Analysis

Background

As defined by the Controlling Nutrition Status (CONUT) score, the prognostic significance of nutritional status has attracted attention in patients with cardiovascular disease. This meta-analysis aimed to determine the importance of CONUT score for prediction of all-cause mortality and major adverse cardiovascular events (MACE) in adult patients with coronary artery disease (CAD).

Methods

Observational studies conducted to evaluate the association of CONUT score with adverse clinical outcomes in patients with CAD were included. We searched MEDLINE, Embase, Scopus, Cochrane library, Google scholar, medRxiv pre-print as well as Science Direct search engine for studies published from the inception of each database until March 21, 2022. Studies reporting the utility of CONUT score in prediction of all-cause mortality and MACE among patients with CAD were eligible. Predictive potential of the CONUT score were summarized by pooling the multivariable adjusted hazard ratio (aHR) with 95% CI for the malnourished vs. normal nutritional status or per point CONUT score increase.

Results

Of 2,547 screened citation, nine observational studies involving 81,257 patients with CAD were analyzed. Malnutrition defined by the CONUT score was associated with significantly increased risk of all-cause mortality when compared with the normal nutritional state (aHR for mild, moderate, and severe malnutrition, respectively: (1.21 [95% CI: 1.15–1.27], I² = 0%), (1.53 [95% CI: 1.26–1.84], I² = 84%), and (2.24 [95% CI: 1.57–3.19], I² = 77%). Similarly, moderate (aHR 1.71 [95% CI: 1.44–2.03], I² = 0%) and severe (aHR 2.66 [95% CI: 1.82–3.89], I² = 0%) malnutrition was associated with a significantly higher risk of MACE compared with the normal nutritional state. Additionally, per point increase in the CONUT score was correlated with 20 and 23% additional risk of all-cause mortality and MACE, respectively.

Conclusion

As defined by the CONUT score, malnutrition is an independent predictor of all-cause mortality and MACE in CAD patients. Nutritional assessment with CONUT score could allow clinicians to identify patients with CAD at high risk for adverse clinical outcomes.

Baseline Objective Malnutritional Indices as Immune-Nutritional Predictors of Long-Term Recurrence in Patients with Acute Ischemic Stroke

Background: The controlling nutritional status (CONUT) score and the prognostic nutritional index (PNI) score were designed as indicators of patients’ immune-nutritional status. This study aimed to investigate the prognostic impact of the CONUT and PNI scores on long-term recurrent ischemic stroke (RIS) and adverse outcomes for adults with acute ischemic stroke (AIS). Methods: This retrospective study enrolled 991 AIS patients. Multivariable Cox regression models were used to assess the relationships of the malnutritional indices and RIS and major cardiovascular events (MACEs). Results: During a median follow-up at 44 months (IQR 39−49 months), 203 (19.2%) patients had RIS and 261 (26.3%) had MACEs. Compared with normal nutritional status, moderate to severe malnutrition was significantly related to an increased risk of RIS in the CONUT score (adjusted hazard ratio (HR) 3.472, 95% confidence interval (CI) 2.223−5.432, p < 0.001). A higher PNI value tertile (tertile two, adjusted HR 0.295, 95% CI 0.202−0.430; tertile three, adjusted HR 0.445, 95% CI 0.308−0.632, all p < 0.001) was related to a lower risk of RIS. Similar results were found for MACEs. The PNI exhibited nonlinear association with the RIS and both two malnutritional indices improved the model’s discrimination when added to the model with other clinical risk factors. Conclusions: This study demonstrated that the CONUT and PNI are promising, straightforward screening indicators to identify AIS patients with impaired immune-nutritional status at higher risk of long-term RIS and MACEs.

Impaired Nutritional Condition After Stroke From the Hyperacute to the Chronic Phase: A Systematic Review and Meta-Analysis

Background

Malnutrition is common after stroke and can affect rehabilitation and healthcare costs. A comprehensive overview of stroke patients' nutritional condition from the hyperacute to the chronic phase is lacking. This systematic review aimed to investigate the prevalence of impaired nutritional condition (INC) across the continuum of care in specific phases after stroke.

Methods

CAB ABSTRACTS, Embase, MEDLINE, were used to collect studies published between 01-01-1999 and 26-08-2020. Primary and secondary outcomes were prevalence of INC and prevalence of malnutrition, respectively. Exploratory outcomes were prevalence of INC at follow-up, nutritional examination methods, prevalence of dysphagia, stroke severity, adverse events, and continent-specific prevalence of INC. A random-effects meta-analysis model was used to estimate the phase-specific pooled prevalence of INC and malnutrition.

Results

The dataset consisted of 78 study groups selected over a total of 1,244 identified records. The pooled prevalence of INC and malnutrition were 19% (95%CI:7–31) (N = 4) and 19% (95%CI:9–29) (N = 3), 34% (95%CI:25–43) (N = 34) and 26% (95%CI:18–35) (N = 29), 52% (95%CI:43–61) (N = 34) and 37% (95%CI:28–45) (N = 31), 21% (95%CI:12–31) (N = 3) and 11% (95%CI:0–24) (N = 3) and 72% (95%CI:41–100) (N = 3) and 30% (95%CI:0–76) (N = 2) in the hyperacute, acute, early subacute, late subacute, and chronic phase, respectively.

Conclusion

INC and malnutrition are highly prevalent in all stages of stroke care. Since malnutrition has been shown to negatively affect clinical outcomes, mortality, and overall healthcare expenditure in stroke survivors, it is essential to examine and monitor the nutritional status of stroke patients throughout their care journey to guide and plan, timely nutritional support and dietary modification.

Malnutrition on admission increases the in-hospital mortality and length of stay in elder adults with acute ischemic stroke

Purpose

Malnutrition, as determined by the Controlling Nutritional Status (CONUT), has an effect on the 3‐month and long‐term prognosis of stroke patients. The association between malnutrition and in‐hospital mortality has not been well established. We aimed to investigate the relationship between the CONUT score on admission and in‐hospital mortality and length of stay (LOS) in elderly patients with acute ischemic stroke (AIS).

Methods

This study analyzed controls and patients with AIS. Malnutrition was determined using the CONUT score. A CONUT score of 5–12 was defined as undernutrition status. Based on the CONUT scores, the patients were divided into the low CONUT (0–4) and high CONUT (5–12) groups.

Results

In total, 1079 participants were recruited, comprising 288 controls and 791 AIS patients. Among the 791 patients, 64 (8.1%) had malnutrition and 63 (7.9%) had an in‐hospital death. Compared to the controls, the AIS patients presented higher CONUT scores, higher proportion of in‐hospital mortality (8.0%), and longer length of stay. Malnutrition was independently associated with in‐hospital mortality in the AIS patients (adjusted odds ratio: 3.77, 95% confidence interval [CI]: 1.55–9.15; p = 0.003). The general linear models showed an association between the CONUT score and LOS (β = 0.574, 95% CI: 0.208–0.934; p = 0.002). Furthermore, the effect of the interaction between infection and nutrition status on in‐hospital mortality showed borderline statistical significance (p = 0.06).

Conclusions

Malnutrition estimated by the CONUT score on admission can be a predictor of in‐hospital mortality and increased LOS in elderly AIS patients.

The prognostic significance of controlling nutritional status (CONUT) score for surgically treated renal cell cancer and upper urinary tract urothelial cancer: a systematic review and meta-analysis

In order to evaluate the predictive effect of the controlled nutritional status (CONUT) score on the prognosis of patients with renal cell carcinoma (RCC) and upper urinary tract urothelial carcinoma (UTUC), a meta-analysis was performed. This systematic review has been registered on PROSPERO, the registration ID is CRD42021251879. A systematic search of the published literature using PubMed, Web of Science, Cochrane Library, EMBASE, and MEDLINE was performed. The fields of "renal cell cancer," "upper tract urothelial cancer," and "controlling nutritional status" and other fields were used as search terms. STATA 16 software was used to carry out data merging and statistical analysis of binary variables, Q test and χ² tests were used to verify the heterogeneity between the included works of studies. Subgroup analysis and sensitivity analysis were used to explain the sources of heterogeneity between studies. Begg's test was used to assess publication bias between studies. From the first 542 studies retrieved, through strict inclusion and exclusion criteria, 7 studies finally met the requirements and were included in the meta-analysis. Pooled results indicated that high CONUT indicates worse over survival (OS) [HR = 1.70, 95% CI (1.43-2.03), P = 0.02], cancer-specific survival (CSS) [HR = 1.84, 95% CI (1.52-2.23), P = 0.01], recurrence-free survival (RFS) [HR = 1.60, 95% CI (1.26-2.03), P = 0.116], and disease-free survival (DFS) [HR = 1.47, 95% CI (1.20-1.81), P = 0.03]. Based on cancer type, cutoff value, region, and sample size, a subgroup analysis was performed. The results showed that OS and CSS were not affected by the above factors, and the high CONUT score before surgery predicted worse OS and CSS. In conclusion, this meta-analysis revealed that the preoperative CONUT score is a potential independent predictor of the postoperative prognosis of RCC/UTUC patients. A high CONUT predicts worse OS/CSS/DFS and RFS in patients.

Prevalence and Prognostic Significance of Malnutrition Risk in Patients With Acute Ischemic Stroke: Results From the Third China National Stroke Registry

BACKGROUND AND PURPOSE

To investigate the prevalence of malnutrition risk in patients with acute ischemic stroke (AIS) at admission, the association between malnutrition risk and long-term outcomes, and whether the predictive ability would be improved after adding to previous prognostic models for poor outcomes.

METHODS

Based on the Third China National Stroke Registry data from August 2015 to March 2018, we evaluated malnutrition risk using objective scores, including the controlling nutritional status score, geriatric nutritional risk index, and prognostic nutritional index. The primary outcome was death or major disability (modified Rankin Scale score ≥3) at 1 year after stroke onset. We calculated the crude prevalence of malnutrition risk and investigated the association between malnutrition risk and clinical outcomes. Prognostic performance of 3 objective malnutrition scores for poor outcomes was assessed.

RESULTS

Moderate to severe malnutrition risk was identified in 5.89%, 5.30%, and 1.95% of the Third China National Stroke Registry AIS patients according to the controlling nutritional status score, geriatric nutritional risk index, and prognostic nutritional index, respectively. At 1-year follow-up, 1143 participants (13.5%) experienced death or major disability. After adjustment for traditional risk factors, moderate to severe malnutrition risk was associated with high risk of composite events (odds ratio, 2.25 [95% CI, 1.75-2.90], for controlling nutritional status score; odds ratio, 2.10 [95% CI, 1.63-2.69], for geriatric nutritional risk index; odds ratio, 3.36 [95% CI, 2.33-4.84], for prognostic nutritional index; all P<0.01). Addition of the 3 malnutrition scores to different predicted scales (iScore and Acute Stroke Registry and Analysis of Lausanne) improved predictive ability for long-term poor outcomes validated by the integrated discrimination index (all P<0.05).

CONCLUSIONS

The prevalence of moderate or severe malnutrition risk in Chinese patients with AIS ranged from 1.95% to 5.89%. Malnutrition risk in patients with AIS was associated with increased risk of long-term death and major disability. Our study provides evidence supporting the prognostic significance of objective malnutrition scores after AIS.

Controlling Nutritional Status score: A novel prognostic marker for patients with community-acquired pneumonia

Objective:

We aimed to investigate the prevalence and prognostic value of malnutrition assessed by Controlling Nutritional Status score in community-acquired pneumonia patients.

Methods:

All adult patients admitted to our emergency department and hospitalized for community-acquired pneumonia were prospectively followed-up until hospital discharge or death. Nutritional status was assessed with the Controlling Nutritional Status score, which is based on serum albumin levels, total cholesterol levels, and lymphocyte counts. The primary study endpoint was complicated hospital course defined as need for mechanical ventilation, mortality, or intensive care unit admission.

Results:

Three hundred and five patients (mean age 68.6 ± 11.2 years and 51.8% female) were enrolled, and 40 patients (13.1%) had complicated hospitalizations. Older patients, patients with more comorbidities, and patients with higher Controlling Nutritional Status scores on admission were tended to have a higher rate of complications during their hospitalization. Multivariate analysis showed that older age (odds ratio 2.55, 95% confidence interval 1.41–4.64, p < 0.001), presence of diabetes (odds ratio 1.54; 95% confidence interval 1.09–3.65; p = 0.004), pneumonia severity index ⩾ 3 (odds ratio 1.27, 95% confidence interval 0.524–3.725, p = 0.035), and Controlling Nutritional Status score > 4 (odds ratio 2.23, 95% confidence interval 1.129–3.657, p = 0.001) were independent predictors of complicated hospitalizations.

Conclusion:

Malnutrition determined by Controlling Nutritional Status score predicts complications in hospitalized patients with community-acquired pneumonia.

Comparing the prognostic significance of nutritional screening tools and ESPEN-DCM on 3-month and 12-month outcomes in stroke patients

BACKGROUND AND AIMS

Malnutrition is prevalent among individuals with acute ischaemic stroke (AIS) and may worsen clinical outcomes. There is no consensus on the best tool for nutritional screening in this population. The present study compared four screening tools and one diagnostic tool in terms of their prognostic significance in predicting short-term and long-term outcomes in AIS patients.

METHODS

We included patients admitted to five major hospitals in Wenzhou and diagnosed with a primary diagnosis of AIS from October 1 to December 31, 2018. The Controlling Nutritional Status (CONUT) score, the Geriatric Nutritional Risk Index (GNRI), the Malnutrition Universal Screening Tool (MUST), the Nutritional Risk Screening Tool 2002 (NRS-2002) and the European Society for Clinical Nutrition and Metabolism diagnostic criteria for malnutrition (ESPEN-DCM) were assessed at admission. The clinical outcomes were evaluated by the modified Rankin Scale (mRS) and mortality at 3 months and 12 months after discharge.

RESULTS

Five hundred and ninety-three patients were included in our prospective study. The mean age was 67.3 ± 12.0 years. Based on the mRS score, 125 patients exhibited poor functional recovery (an mRS ≥3) at 3 months after discharge. Seventeen patients died during the 3-month follow-up period, and the other 25 did not survive 12 months. Multivariate binary logistic regression revealed that inadequate nutritional status at admission, as determined by the CONUT, GNRI, MUST, NRS-2002 and ESPEN-DCM, were independently associated with poor outcomes in AIS patients 3 months after discharge. Both MUST ≥2 and NRS-2002 ≥ 3 showed significant associations with poor outcomes at 12-month post-discharge. Further analysis with the receiver operator characteristic (ROC) curve showed similar results, where all the tools predicted the poor outcomes at 3 months while only the NRS-2002 and MUST scores were significantly associated with the mRS at 12 months post-discharge. Moreover, the area under the curve (AUC) of MUST and NRS-2002 were significantly larger than those for the other tools. The optimal cut-off values of the MUST and NRS-2002 to predict poor outcomes were scores of ≥2 and ≥ 3 points, respectively.

CONCLUSIONS

Our data supported a deleterious effect of inadequate nutrition, as evidenced by the nutrition screening tools or ESPEN-DCM, on clinical outcomes during and beyond the acute phase of AIS. We recommended the use of the MUST and NRS-2002 in guiding nutritional support in AIS patients, as they have higher predictive power and can predict both short-term and long-term outcomes.

Controlling nutritional status score and prognostic nutrition index predict the outcome after severe traumatic brain injury

OBJECTIVES

Immune-nutritional status is correlated with a clinical outcome in critical illness. Recently, controlling nutritional status (CONUT) score and prognostic nutrition index (PNI) has been reported to predict prognosis following cancer and other diseases. The aim of this study was to explore the relationship between the CONUT score and PNI and 6-month outcome in patients with severe traumatic brain injury (STBI).

METHODS

We retrospectively analyzed the clinical data of 78 patients with STBI, including the CONUT score and PNI. Patients were divided into high CONUT group and low CONUT group. Patients were also divided into high PNI and low PNI group respectively. The 6-month outcome was evaluated by the modified Rankin scale (mRS). The unfavorable outcome was defined as mRS score ≥3.

RESULTS

The unfavorable outcome group had lower Glasgow coma scale (GCS) scores, serum albumin, total cholesterol, PNI, and higher CONUT scores (P < 0.05). Both CONUT scores and PNI were strongly correlated with mRS (r = 0.429, P < 0.05; r = -0.590, P < 0.05, respectively). After adjustment for confounding factors, the odds ratios of CONUT scores and PNI for predicting unfavorable outcome were 10.478 (95% CI: 2.793-39.301) and -0.039 (95% CI: 0.008-0.204), respectively. The area under the curve (AUC) of CONUT scores for predicting unfavorable outcome was 0.777 (95% CI: 0.674-0.880, P < 0.01), which was similar to PNI (0.764, 95% CI: 0.657-0.87, P < 0.01).

CONCLUSION

Both CONUT scores and PNI might be novel independent predictors of the poor outcome in STBI.

Neurological Comorbidity Is a Predictor of Death in Covid-19 Disease: A Cohort Study on 576 Patients

Introduction: Prognosis of Coronavirus disease 2019 (Covid-19) patients with vascular risk factors, and certain comorbidities is worse. The impact of chronic neurological disorders (CND) on prognosis is unclear. We evaluated if the presence of CND in Covid-19 patients is a predictor of a higher in-hospital mortality. As secondary endpoints, we analyzed the association between CND, Covid-19 severity, and laboratory abnormalities during admission.

Methods: Retrospective cohort study that included all the consecutive hospitalized patients with confirmed Covid-19 disease from March 8th to April 11th, 2020. The study setting was Hospital Clínico, tertiary academic hospital from Valladolid. CND was defined as those neurological conditions causing permanent disability. We assessed demography, clinical variables, Covid-19 severity, laboratory parameters and outcome. The primary endpoint was in-hospital all-cause mortality, evaluated by multivariate cox-regression log rank test. We analyzed the association between CND, covid-19 severity and laboratory abnormalities.

Results: We included 576 patients, 43.3% female, aged 67.2 years in mean. CND were present in 105 (18.3%) patients. Patients with CND were older, more disabled, had more vascular risk factors and comorbidities and fewer clinical symptoms of Covid-19. They presented 1.43 days earlier to the emergency department. Need of ventilation support was similar. Presence of CND was an independent predictor of death (HR 2.129, 95% CI: 1.382–3.280) but not a severer Covid-19 disease (OR: 1.75, 95% CI: 0.970–3.158). Frequency of laboratory abnormalities was similar, except for procalcitonin and INR.

Conclusions: The presence of CND is an independent predictor of mortality in hospitalized Covid-19 patients. That was not explained neither by a worse immune response to Covid-19 nor by differences in the level of care received by patients with CND.

Prognostic Nutritional Index for Predicting 3-Month Outcomes in Ischemic Stroke Patients Undergoing Thrombolysis

Objective: Malnutrition has been reported to be related to adverse prognosis in acute ischemic stroke (AIS) patients. Unfortunately, traditional nutritional assessment tools usually increase the workload of neurologists, which makes them unfeasible in the daily clinic work. We aimed to elucidate the association between the prognostic nutritional index (PNI), an easily obtainable baseline nutritional marker, and 3-month outcomes in AIS patients receiving intravenous thrombolysis (IVT).

Research methods and procedures: The present study retrospectively included 405 patients. PNI was calculated as 5^*lymphocyte count (10⁹ /L) + serum albumin concentration (g/L), and the good prognosis was defined as modified Rankin Scale score of 0–3. The relationship between PNI and clinical parameters was evaluated. The multiple logistic regression model was performed to find out independent predictors of the 3-month outcomes.

Results: We found that the patients in the low PNI group had a higher frequency of anemia (12.9 vs. 2.3%, P < 0.001) and a higher level of the Controlling nutritional status (CONUT) score (P < 0.001). The relationship between PNI and nutrition-related factors, such as body mass index (r = 0.208, P = 0.001), age (r = −0.329, P < 0.001), total cholesterol (r = 0.268, P < 0.001) and hemoglobin concentration (r = 0.328, P < 0.001), was significant. Low PNI value (adjusted odds ratio: 2.250, confidence interval: 1.192–4.249, p = 0.012) stayed as an independent predictor for the poor outcome at three months, after adjustment for potential confounders.

Conclusions: The PNI was independently associated with 3-month outcomes in AIS patients undergoing IVT. As an easily obtainable nutritional marker, PNI may be a useful nutritional assessment tool in the clinic work.

Being at risk of malnutrition predicts poor outcomes at 3 months in acute ischemic stroke patients

BACKGROUND

Malnutrition is confirmed to be associated with poor outcomes in stroke patients. The present study aimed to confirm that being at risk of malnutrition assessed by Nutritional Risk Screening Tool 2002 (NRS-2002) and the Controlling Nutritional Status (CONUT) score predicts poor outcomes at 3 months in acute ischemic stroke (AIS) patients.

METHODS

In total, 682 patients with AIS were recruited within 7 days of stroke onset consecutively and 110 were dropped out. They were screened for risk of malnutrition using NRS-2002 and the CONUT score. The primary outcome is the follow-up modified Rankin Scale (mRS) score. Poor outcomes were defined as an (mRS) score ≥ 3 at 3 months post discharge.

RESULTS

There was a significant difference in the mRS score at 3 months between patients at risk of malnutrition compared to those not at risk assessed by NRS-2002(P < 0.001) and CONUT (P = 0.011). The logistic regression model showed that the risk of malnourishment (according to NRS-2002), low risk of malnourishment (according to CONUT), and the moderate-to-severe risk of malnourishment (according to CONUT) were associated with higher risk of poor outcomes at 3 months (P < 0.001, P = 0.033, and P = 0.007). The multivariate logistic regression model (adjusted for confounding factors) demonstrated that the risk of malnourishment, according to the NRS-2002, was associated with the increasing risk of poor outcomes at 3 months (odds ratio = 2.31; 95% CI: 1.24-4.30; P = 0.008).

CONCLUSIONS

The risk of malnutrition assessed by NRS-2002 and CONUT can predict poor outcomes at 3 months in AIS patients. NRS-2002 is superior to CONUT in predicting poor outcomes at 3 months.