Predictors of Rehospitalization and Mortality in Diabetes-Related Hospital Admissions

Nomogram Predicting 90-Day Readmission in Patients with Diabetes: A Prospective Study

Purpose

Readmission within a period time of discharge is common and costly. Diabetic patients are at risk of readmission because of comorbidities and complications. It is crucial to monitor patients with diabetes with risk factors for readmission and provide them with target suggestions. We aim to develop a nomogram to predict the risk of readmission within 90 days of discharge in diabetic patients.

Patients and Methods

This is a prospective observational survey. A total of 784 adult patients with diabetes recruited in two tertiary hospitals in central China were randomly assigned to a training set or a validation set at a ratio of 7:3. Depression, anxiety, self-care, physical activity, and sedentary behavior were assessed during hospitalization. A 90-day follow-up was conducted after discharge. Multivariate logistic regression was employed to develop a nomogram, which was validated with the use of a validation set. The AUC, calibration plot, and clinical decision curve were used to assess the discrimination, calibration, and clinical usefulness of the nomogram, respectively.

Results

In this study, the 90-day readmission rate in our study population was 18.6%. Predictors in the final nomogram were previous admissions within 1 year of the index admission, self-care scores, anxiety scores, physical activity, and complicating with lower extremity vasculopathy. The AUC values of the predictive model and the validation set were 0.905 (95% CI=0.874-0.936) and 0.882 (95% CI=0.816-0.947). Hosmer-Lemeshow test values were p = 0.604 and p = 0.308 (both > 0.05). Calibration curves showed significant agreement between the nomogram model and actual observations. Decision curve analysis indicated that the nomogram improved the clinical net benefit within a probability threshold of 0.02-0.96.

Conclusion

The nomogram constructed in this study was a convenient tool to evaluate the risk of 90-day readmission in patients with diabetes and contributed to clinicians screening the high-risk populations.

Hospital Readmissions for Fluid Overload among Individuals with Diabetes and Diabetic Kidney Disease: Risk Factors and Multivariable Prediction Models

AIMS

Hospital readmissions due to recurrent fluid overload in diabetes and diabetic kidney disease can be avoided with evidence-based interventions. We aimed to identify at-risk patients who can benefit from these interventions by developing risk prediction models for readmissions for fluid overload in people living with diabetes and diabetic kidney disease.

METHODS

This was a single-center retrospective cohort study of 1,531 adults with diabetes and diabetic kidney disease hospitalized for fluid overload, congestive heart failure, pulmonary edema, and generalized edema between 2015 and 2017. The multivariable regression models for 30-day and 90-day readmission for fluid overload were compared with the LACE score for discrimination, calibration, sensitivity, specificity, and net reclassification index (NRI).

RESULTS

Readmissions for fluid overload within 30 days and 90 days occurred in 8.6% and 17.2% of patients with diabetes, and 8.2% and 18.3% of patients with diabetic kidney disease, respectively. After adjusting for demographics, comorbidities, clinical parameters, and medications, a history of alcoholism (HR 3.85, 95% CI: 1.41-10.55) and prior hospitalization for fluid overload (HR 2.50, 95% CI: 1.26-4.96) were independently associated with 30-day readmission in patients with diabetic kidney disease, as well as in individuals with diabetes. Additionally, current smoking, absence of hypertension, and high-dose intravenous furosemide were also associated with 30-day readmission in individuals with diabetes. Prior hospitalization for fluid overload (HR 2.43, 95% CI: 1.50-3.94), cardiovascular disease (HR 1.44, 95% CI: 1.03-2.02), eGFR ≤45 mL/min/1.73 m2 (HR 1.39, 95% CI: 1.003-1.93) was independently associated with 90-day readmissions in individuals with diabetic kidney disease. Additionally, thiazide prescription at discharge reduced 90-day readmission in diabetic kidney disease, while the need for high-dose intravenous furosemide predicted 90-day readmission in diabetes. The clinical and clinico-psychological models for 90-day readmission in individuals with diabetes and diabetic kidney disease had better discrimination and calibration than the LACE score. The NRI for the clinico-psychosocial models to predict 30- and 90-day readmissions in diabetes was 22.4% and 28.9%, respectively. The NRI for the clinico-psychosocial models to predict 30- and 90-day readmissions in diabetic kidney disease was 5.6% and 38.9%, respectively.

CONCLUSION

The risk models can potentially be used to identify patients at risk of readmission for fluid overload for evidence-based interventions, such as patient education or transitional care programs to reduce preventable hospitalizations.

Nationwide clinico-epidemiological treatment analysis of adult patients with tumors of cerebellopontine angle and internal acoustic meatus in Poland during 2011-2020

OBJECTIVE

The aim of this study is to report the epidemiologic characteristics of tumors of the cerebellopontine angle (CPAT) and internal acoustic meatus in adult Polish population throughout the second decade of XXI century and to analyze their treatment.

MATERIAL AND METHODS

A retrospective analysis of patients with cerebellopontine angle (CPA) and internal acoustic meatus tumors diagnosed in Poland in 2011-2020 was performed. Data recorded in the National Health Fund (NHF) database were analyzed. International Classification of Diseases codes (ICD-9 and ICD-10) were used to identify study group patients and treatment procedures.

RESULTS

From 2011 to 2020 6,173 Polish adult patients were diagnosed with cerebellopontine angle and internal acoustic meatus tumors. The average incidence in Poland is 1.99 per 100,000 residents/year. It mostly affects women (61.64%), and the average age of patients is 53.78 years. The incidence has steadily increased over the past decade. Treatment has changed significantly over the years, with a definite increase in the number of patients treated with radiotherapy (from 0.54 to 19.34%), and a decrease in surgical therapies (from 41.67 to 6.8%). The most common symptoms were vertigo and/or dizziness (43.48%) and sensorineural hearing loss (39.58%). 4.65% of patients suffered from sudden deafness, in this group of patients the risk of CPAT detection was the highest (6.25 / 1000 patients).

CONCLUSIONS

The total incidence of CPAT and demographic characteristics of patients were comparable to other studies. Our study demonstrated the increased number of patients are being treated with radiotherapy and fewer with microsurgery. Sudden sensorineural hearing loss (SSNHL) is an uncommon manifestation of CPAT but proper diagnosis should be undertaken because the risk of diagnosis such tumors is greater in this group.

Obesity Metabolic Phenotypes and Unplanned Readmission Risk in Diabetic Kidney Disease: An Observational Study from the Nationwide Readmission Database

BACKGROUND AND AIM

Obesity is a potentially modifiable factor for reducing readmissions, with heterogeneity that varies according to the metabolic status. Our objective was to examine the independent or mutual relationship between obesity and metabolic abnormalities and diabetic kidney disease (DKD)-related hospitalizations.

METHODS

493,570 subjects with DKD were enrolled in the 2018 Nationwide Readmission Database (NRD, United States). The at-risk population was reclassified into refined obesity subtypes based on the body mass index (BMI) classification of metabolic abnormalities (hypertension and/or dyslipidemia) to investigate the 180 d readmission risk and hospitalization costs related to DKD.

RESULTS

The overall readmission rate was 34.1%. Patients with metabolic abnormalities, regardless of obesity, had a significantly higher risk of readmission compared to non-obese counterparts (adjusted HR, 1.11 [95% CI, 1.07-1.14]; 1.12 [95% CI, 1.08-1.15]). Hypertension appeared to be the only metabolic factor associated with readmission among individuals with DKD. Obesity without metabolic abnormalities was independently associated with readmission (adjusted HR,1.08 [1.01,1.14]), especially among males and those >65 years (adjusted HR,1.10 [1.01-1.21]; 1.20 [1.10-1.31]). Women or those ≤65 years with metabolic abnormalities (all p <0.050) had elevated readmission rates, regardless of obesity; however, no such trend was observed in obese subjects without metabolic abnormalities (adjusted HR, 1.06 [0.98,1.16]). Additionally, obesity and metabolic abnormalities were associated with elevated hospitalization costs (all p <0.0001).

CONCLUSIONS

Increased BMI and hypertension are positively associated with readmissions and related costs among patients with DKD, which should be considered in future studies.

Hospital-care utilization and medical cost patterns among patients with insulin-dependent diabetes

OBJECTIVE

Using claims data from an integrated payer-provider, we compared the costs incurred by insulin-dependent diabetes mellitus (IDDM) patients who received Hospital Inpatient/Observation/Emergency Department care (HIghER care) for diabetes-related events with those who did not receive such care to identify a target population for interventions in future studies.

METHODS

A retrospective study pooled real-world claims data for IDDM with type 1 or type 2 DM between July 1, 2018 and June 30, 2019. Medical claims were used to calculate the total and diabetes-related allowed medical costs to the Enterprise and per-member per month (pmpm) costs.

RESULTS

A total of 19,378 members' medical and prescription drug coverage were analyzed. Only 8.4% of the IDDM population received HIghER care but incurred 20% of medical expenses, and nearly 40% of diabetes-related medical costs. For HIghER care patients, medical spending was higher in every inpatient and outpatient category (Wilcoxon two sample tests, all p < 0.0001). Non-diabetes related prescription drug costs were greater in this group (Wilcoxon, Z = 2.2879, p = 0.0221), but diabetes-related prescription drug costs were higher for non-HIghER care (Wilcoxon, Z = -9.5918, p < 0.0001). In a longitudinal study of 29,602 patients over 24 months, prior-year receipt of HIghER care was a significant predictor of HIghER care the subsequent year (odds ratio 3.28) CONCLUSIONS: Medical spending for HIghER care patients was disproportionately high and greater in every inpatient and outpatient category. Receipt of HIghER care in the previous year was highly predictive of HIghER care episodes the following year.