Total blood lymphocyte count as a prognostic factor among unselected inpatients

Association of the Controlling Nutritional Status (CONUT) score with all-cause and cause-specific mortality in patients with diabetic kidney disease: evidence from the NHANES 2009-2018

OBJECTIVE

To investigate the association between the Controlling Nutritional Status (CONUT) score and all-cause and cause-specific mortality in patients with diabetic kidney disease (DKD).

DESIGN

A retrospective cohort study.

SETTING AND PARTICIPANTS

Data on patients with DKD from the National Health and Nutrition Examination Survey 2009-2018.

PRIMARY AND SECONDARY OUTCOME MEASURES

All-cause mortality, cardiovascular disease (CVD)-related mortality, diabetes-related mortality and nephropathy-related mortality.

RESULTS

A total of 1714 patients were included, with 1119 (65.29%) in normal nutrition group (a score of 0-1), 553 (32.26%) in mild malnutrition group (a score of 2-4) and 42 (2.45%) in moderate and severe malnutrition group (a score of 5-12), according to the CONUT score. After controlling for age, race, marital status, smoking, hypertension, CVD, diabetic retinopathy, poverty income ratio, antidiabetics, diuretics, urinary albumin to creatinine ratio, uric acid, energy, protein, total fat, sodium and estimated glomerular filtration rate, a higher CONUT score was associated with a significantly greater risk of all-cause death (HR 1.30, 95% CI 1.15 to 1.46, p<0.001). In contrast to patients with a CONUT score of 0-1, those who scored 5-12 had significantly increased risks of all-cause death (HR 2.80, 95% CI 1.42 to 5.51, p=0.003), diabetes-related death (HR 1.78, 95% CI 1.02 to 3.11, p=0.041) and nephropathy-related death (HR 1.84, 95% CI 1.04 to 3.24, p=0.036).

CONCLUSION

Moderate and severe malnutrition was associated with greater risks of all-cause death, diabetes-related death and nephropathy-related death than normal nutritional status in DKD. Close monitoring of immuno-nutritional status in patients with DKD may help prognosis management and improvement.

Effectiveness of a Digital Decision Aid for Nutrition Support in Women with Gynaecological Cancer: A Comparative Study

This study aimed to examine the effects of an animated Patient Decision Aid (PtDA) about dietary choices on decisional conflict and decision regret. A prospective, observational, two-group comparative effectiveness study was conducted with patients (n = 90) from a southern Taiwan oncology inpatient unit. Data included the Malnutrition Universal Screening Tool (MUST), laboratory results, 16-item Decisional Conflict Scale (sf-DCS), and 5-item Decision Regret Scale (DRSc). Data were collected at admission (T0), after the first-cycle of chemotherapy but before discharge (T1), and after the six-cycle chemotherapy protocol (T2) (around 3 months). Group A received standardized nutrition education and a printed brochure, while Group B watched a 10-minute information video during a one-on-one inpatient consultation and engaged in a values clarification exercise between T0 and T1. The percentage of women with a MUST score ≧1 in Group A sharply increased over time, but not in Group B. Decision aid usage significantly increased patients' hemoglobin and lymphocyte values over time (p < 0.05). The digital PtDA contributed to less decisional conflict and decision regret in at-risk patients and improved their nutritional well-being. Decision-aids help patients make healthcare decisions in line with their values, and are sustainable for use by busy clinicians.

Nutritional Risk Assessment and Adverse Events in Patients Undergoing Left Ventricular Assist Device Implantation-A Retrospective Cohort Study Using Hospital Information System

Clinical or subclinical malnutrition occurs in 30% to 70% of patients with advanced heart failure and increases the risk of postoperative adverse events. The main objective of this study was to assess the nutritional status of patients prior to left ventricular assist device (LVAD) implantation using different methods of malnutrition assessment and to evaluate the relationship between nutritional status and postoperative adverse events. A retrospective cohort study included 120 patients aged 26-74 years referred for LVAD surgery. Preoperative nutritional status (NRS-2002-Nutritional Risk Score 2002, NRI-Nutritional Risk Index, PNI-Prognostic Nutritional Index; TLC-total lymphocyte count) and postoperative adverse events were assessed. Moderate to severe malnutrition was found in 55.8%, 43.3%, 40.0%, and 20% of all patients, respectively, according to the PNI, NRI, TLC, and NRS-2002 scores. Patients with a TLC < 1200 cells/m3 had a higher risk of postoperative acute renal failure [hazard ratio (HR): 2.5; 95% confidence interval (95% CI): 1.01-6.3] and death during the observation period [HR = 2.1; 95% CI: 1.2-3.5]. Moderate to severe malnutrition was also associated with a significantly increased risk of in-hospital death [for the NRI score, HR = 4.9 (95% CI: 1.1-22.0); for the PNI score, HR = 5.0 (95% CI: 1.1-22.3)]. In conclusion, moderate to severe malnutrition prior to LVAD implantation has been identified as a risk factor for postoperative acute renal failure and mortality. Assessment of nutritional risk may improve patient selection and early initiation of nutritional support.

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer

BACKGROUND

Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis.

METHODS

Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set's prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve.

RESULTS

From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients.

CONCLUSIONS

This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.

Pretreatment Nutritional Status in Combination with Inflammation Affects Chemotherapy Interruption in Women with Ovarian, Fallopian Tube, and Peritoneal Cancer

BACKGROUND

Discontinuing chemotherapy worsens cancer prognosis. This study aimed to investigate the relationship between nutritional status at the start of chemotherapy and chemotherapy discontinuation in patients with ovarian, fallopian tube, and primary peritoneal cancer.

METHODS

This was a retrospective cohort study. One hundred and forty-six patients to whom weekly paclitaxel and carboplatin were administered as postoperative chemotherapy were included. Six courses in 21-day cycles were defined as complete treatment. As nutritional indicators, body mass index, weight change rate, serum albumin, total lymphocyte count, prognostic nutritional index, and C-reactive protein-to-albumin ratio (CAR) were compared between complete and incomplete treatment groups. Patients were divided into two groups according to CAR. The number of chemotherapy cycles was compared between these two groups. A Cox proportional hazard model was used for covariate adjustment.

RESULTS

Several indicators differed between complete and incomplete treatment groups, and among the indicators, CAR had the highest discriminatory ability. The number of chemotherapy cycles was shorter in the high CAR group than in the low CAR group. A high CAR was associated with chemotherapy interruption even after adjusting for covariates.

CONCLUSION

Based on CAR, nutritional status before chemotherapy is suggested to be associated with the risk of chemotherapy discontinuation.

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.

Nutritional and prognostic significance of abdominal wall thickness measured during percutaneous endoscopic gastrostomy in older individuals with dysphagia

BACKGROUND & AIMS

The significance of abdominal wall thickness (AWT) for nutritional assessment remains unclear. This study aimed to evaluate the nutritional and prognostic significance of AWT measured during percutaneous endoscopic gastrostomy (PEG) in older patients with dysphagia.

METHODS

This single-center retrospective cohort study enrolled older adults with dysphagia who underwent PEG for enteral nutrition using the introducer technique between February 2010 and January 2019. We examined the association between AWT measured during PEG and nutritional status items, including body mass index (BMI), serum albumin (Alb), total lymphocyte count (TLC), total cholesterol (TC), hemoglobin (Hb), and C-reactive protein (CRP). The shaft length of the PEG tube inserted, which is an approximation value of the AWT, was used for statistical analysis. Patients were divided into three groups: low-AWT group (shaft length ≤2.5 cm), medium-AWT group (shaft length 3.0-3.5 cm), and high-AWT group (shaft length ≥4.0 cm). We performed the Kruskal-Wallis test and multiple linear regression analysis with multiple imputation. We performed survival analysis using the Kaplan-Meier method, log-rank test, and Cox regression analysis.

RESULTS

A total of 520 patients were identified: 115, 258, and 147 patients in the low-AWT, medium-AWT, and high-AWT groups, respectively. Higher AWT was significantly associated with higher BMI, Alb, TLC, TC, Hb, and lower CRP levels. Multiple linear regression analysis revealed that BMI and TLC were significant predictors of AWT (BMI: coefficient 1.16E-01, 95% confidence interval [CI], 9.77E-02-1.33E-01, P < 0.001; TLC: coefficient 1.18E-04, 95% CI, 2.72E-05-2.09E-04, P = 0.011). The median survival time was the longest in the high-AWT group (low-AWT, 359 days; medium-AWT, 851 days; high-AWT, 1662 days; P < 0.001). The hazard ratio for the high-AWT group relative to the medium-AWT group was 0.59 (95% CI, 0.41-0.85, P = 0.004), and that relative to the low-AWT group was 0.34 (95% CI, 0.24-0.51, P < 0.001).

CONCLUSIONS

Higher AWT was associated with better nutritional status and survival. AWT may help assess nutritional status and predict survival in older dysphagic patients with PEG.

Controlling Nutritional Status Score as a Predictive Marker of In-hospital Mortality in Older Adult Patients

The controlling nutritional status (CONUT) score assesses nutritional status and is associated with short- and long-term prognoses in some diseases, but the significance of the CONUT score for the prediction of in-hospital mortality in older adults is unknown. The purpose was to determine the importance of the CONUT score for the prediction of in-hospital mortality, short-term complications, length of hospital stay, and hospital costs in older adults. Our retrospective cohort study analyzed data from 11,795 older adult patients from two multicenter cohort studies. We performed receiver operating characteristic curve analysis using in-hospital mortality as the endpoint and determined the appropriate CONUT score cut-off by the Youden index. The patients were divided into two high and low groups according to the CONUT cut-off value, and the differences in clinical characteristics and in-hospital clinical outcomes between the two groups were compared. We compared the accuracy of the CONUT score and other nutrition-related tools in predicting in-hospital mortality by calculating the area under the receiver operating characteristic curve and performed univariate and multivariate analyses of predictors of in-hospital mortality. Among all the patients, 178 (1.5%) patients experienced in-hospital death. The optimal cut-off values was 5.5 for the CONUT score. The high CONUT group had a higher incidence of short-term complications and prolonged hospital stay than the low CONUT group (CONUT score <6), but hospital costs were not significantly higher. The CONUT score had the highest predictive ability for in-hospital mortality among the five nutrition-related parameters compared. Multivariate analysis showed that a high CONUT score (CONUT score ≥ 6) was an independent predictor of in-hospital mortality. In conclusion, the present study demonstrated that the CONUT score could be used to predict in-hospital mortality in older adults.