Design and data source
A retrospective analysis was performed using data extracted from a medical claims database comprising 451 hospitals and maintained by Medical Data Vision Co., Ltd. (MDV; Tokyo, Japan). The database uses the Combination Diagnostic Procedure/Daily Allowance (DPC/PDPS) system, in which provider reimbursement is calculated on the basis of a flat rate per diem based on diagnosis group. The study protocol was approved by the ethics committees of the Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences of Okayama University (No. 2108-041) and the Graduate School of Medicine from Kurume University (No. 21139) and registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN000044962). Informed consent was not required, as all personal information used in this study was anonymized.
The database included information on hospital admission and discharge dates, age at admission, sex, height, body weight, body mass index (BMI), number of hospital beds of admission, year and type of admission, primary diseases (coded using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision [ICD-10]), comorbidities (used to determine the Charlson Comorbidity Index [CCI]) activities of daily living (ADL) according to the Barthel index (BI) levels of consciousness based on the Japanese Coma Scale (JCS) malnutrition defined as insufficient oral intake for at least 10 days and low body mass index according to the criteria of the Global Leadership Initiative on Malnutrition (GLIM) , medical treatments during hospitalization (using Japan-specific medical claim codes), and discharge outcome status, and other information not used in our study. The total daily doses of parenteral energy, amino acids and ILE prescribed were calculated using the names and compositions of the parenteral nutritional infusion products and the prescribed amounts of these products as they appeared in the database. When recording these doses, day 1 was taken as the day the fast began, day 2 as the second day after the fast began, and so on.
This study included hospitalized adult patients aged 18 years or older who were fasting (receiving no oral or enteral nutrition) for more than 10 consecutive days and were managed with parenteral nutrition, between January 2011 and September 2020. Patients were excluded from the study who underwent surgery or entered the intensive care unit between the day of admission and the start of fasting, were suspected of having end-stage disease (defined as energy doses average prescribed energy doses < 10 kcal/kg or average amino acid doses < 0.5 g/kg on days 4-10), or were considered overfed (which we based on average prescribed energy doses ≥ 30 kcal/ kg on days 4 to 10). The rationale for the use of days 4-10 was that administration of parenteral nutrition usually involves a gradual increase in dose over the first 3-4 days before reaching the full target dose. [7, 8].
The primary endpoint was in-hospital mortality. Secondary endpoints included intravenous catheter infection during hospitalization, deterioration of ADLs at discharge, length of stay (LOS), readmission, and total medical expenses. ADLs at discharge, SD and readmission were recorded only for patients discharged alive, while other data were recorded for all patients. Medical costs were calculated based on Japanese yen and then converted to US dollars (US$) using the 2020 annual exchange rate reported by the Organization for Economic Co-operation and Development (OECD) ($1 US = 107 Japanese yen) . Patients were considered to have deteriorated ADLs when their total BI scores were lower at discharge than at admission. Readmission was defined as readmission to the same hospital within 30 days of discharge.
The variables extracted from the database were categorized as follows: age at admission (18–59, 60–69, 70–79, 80–89 or ≥ 90 years), BMI (< 16.0, 16, 0–18.5, 18.5–22.5, 22.5–25.0 or ≥ 25.0), number of hospital admission beds (< 200, 200–500 or ≥ 500), year of admission (2011–2012, 2013–2014, 2015–2016, 2017–2018, or 2019–2020), type of admission (elective or emergency), primary illness (by ICD-10 code), comorbidities ( ICC of 0, 1, 2 or ≥ 3), ADL (IB of 0, 5-20, 25-40, 45–60, 65–95 or 100), levels of consciousness (JCS of 0 [alert]1–3 [awake]10–30 [arousable]or 100–300 [coma]), and nutritional status (malnutrition defined as BMI < 18.5 if < 70 years old or BMI < 20 if > 70 years). Information about medical treatments (eg, albumin infusion, blood transfusion, ventilator use, dialysis, nutritional support team, and rehabilitation) ordered between day of admission and day 10 was extracted from the database for each patient. Missing values for admission type, BI and JCS were placed in an “unknown” category.
Prescribed doses of parenteral nutrition
The average prescribed daily doses of energy, amino acids and ILE for days 4 to 10 after the start of the fast were calculated for each patient based on the composition of the parenteral nutrition infusion product and the prescribed amount of this infusion and were based on the assumption that nutrient doses often take up to day 4 to reach 100% of their target . Prescribed daily doses of energy and amino acids were calculated in kilocalories (kcal) and grams (g), respectively, and reported per kilogram (kg) of body weight and prescribed daily doses of ILE were calculated and reported as grams and calorie percentage (%) of total non-protein energy administered that day.
Data management and statistical analysis were performed by an independent third party (A2 Healthcare Corporation; Tokyo, Japan) to eliminate arbitrariness and ensure transparency. Categorical variables were summarized as numbers and percentages, and continuous variables were summarized as means and standard deviations (SD). Missing values were not included. First, patients eligible for the study were divided into 2 groups: the ILE group, who were prescribed ILEs for days 4-10, and the non-ILE group, who were not given of ILE on days 4-10. Then propensity score matching (PSM) was used to adjust for confounding factors . The propensity score was estimated by multivariate logistic regression analysis with the ILE group as objective variable and patient characteristics as explanatory variables. The PSM was performed using a one-to-one nearest neighbor method and using thickness width. The thickness value was 0.2 and the matching was done in the thickness values. To confirm the balance of covariates between groups, standardized differences were calculated before and after PSM. A standardized difference of less than 10% was considered to represent a balanced covariate .
To compare the 2 groups for each outcome, both before and after PSM, the student you-test was used for continuous variables and the chi-square test was used for categorical variables. To adjust for differences in the average daily parenteral energy doses prescribed between the 2 groups, even after PSM, multivariate logistic or multiple regression analyses, as appropriate, were performed, with the average daily energy dose prescribed for days 4 to 10 added as an explanatory variable. In these analyses, odds ratios (ORs) or regression coefficients, as appropriate, and 95% confidence intervals (CIs) were calculated, before and after adjusting for energy.
For in-hospital mortality, survival curves were generated for the 2 groups using the Kaplan-Meier method, and a log-rank test was performed. In addition, the Cox proportional hazard model was used to calculate a hazard ratio (HR), as well as a 95% CI, from the ILE group to the non-ILE group, for in-hospital mortality. For these calculations, patients who were discharged alive were censored on the day of discharge, and inpatients who survived for 180 days or more were censored on day 180. All statistical analyzes were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA), with a two-sided significance level of 5%.
Prior to modeling, variance inflation factors (VIFs) of patient characteristics and mean daily doses of parenteral nutrition prescribed were calculated to confirm that there was no multicollinearity between variables based on a multiple regression analysis or a multivariate logistic regression analysis. .
To confirm the robustness of PSM, confounding factors were adjusted by multivariate logistic regression analysis or multiple regression analysis, and an adjustment analysis composed of 2 groups of explanatory variables (Model 1, Model 2) was been carried out. In model 1, the explanatory variables were the 2 groups and the characteristics of the patients. In Model 2, the explanatory variables were those included in Model 1 as well as the average daily parenteral energy prescribed during days 4-10. ORs or regression coefficients, as well as 95% CIs, were calculated for each model.
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