All Patient Refined-Diagnosis Related Groups' (APR-DRGs) Severity of Illness and Risk of Mortality as predictors of in-hospital mortality

The aims of this study were to assess All-Patient Refined Diagnosis-Related Groups' (APR-DRG) Severity of Illness (SOI) and Risk of Mortality (ROM) as predictors of in-hospital mortality, comparing with Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) scores. We performed a retrospective observational study using mainland Portuguese public hospitalizations of adult patients from 2011 to 2016. Model discrimination (C-statistic/ area under the curve) and goodness-of-fit (R-squared) were calculated. Our results comprised 4,176,142 hospitalizations with 5.9% in-hospital deaths. Compared to the CCI and ECI models, the model considering SOI, age and sex showed a statistically significantly higher discrimination in 49.6% (132 out of 266) of APR-DRGs, while in the model with ROM that happened in 33.5% of APR-DRGs. Between these two models, SOI was the best performer for nearly 20% of APR-DRGs. Some particular APR-DRGs have showed good discrimination (e.g. related to burns, viral meningitis or specific transplants). In conclusion, SOI or ROM, combined with age and sex, perform better than more widely used comorbidity indices. Despite ROM being the only score specifically designed for in-hospital mortality prediction, SOI performed better. These findings can be helpful for hospital or organizational models benchmarking or epidemiological analysis.

Characteristics in Pediatric Patients with Coronavirus Disease 2019 in Korea

BACKGROUND

Based on the reports of low prevalence and severity of pediatric severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, the Korean government has released new SARS-CoV-2 infection response and treatment guidelines for children under the age of 12 years. The government has further directed school reopening under strict preventive measures. However, there is still considerable concern on the impact of school reopening on community transmission of Coronavirus disease 2019 (COVID-19). In the present study, we aimed to evaluate the appropriateness of these directives and the severity of SARS-CoV-2 infections in children as compared to adults using sufficient national sample data.

METHODS

In the present study, we evaluated the severity of SARS-CoV-2 infection in pediatric patients as compared to adults by analyzing the length of hospital stays (LOS), medical expenses, and hospital and intensive care unit (ICU) admission rates. A multivariate linear regression analysis was carried out to examine the effects of COVID-19 patients that the characteristics on the LOS and medical expenses, and multivariate logistic regression analysis were performed to identify COVID-19 characteristics that affect hospital and ICU admission rates and to prove the low SARS-CoV-2 infection severity in pediatric patients.

RESULTS

The hospitalization period for children aged 0-9 was 37% shorter and that of patients aged 10-19 years was 31% shorter than those of older age groups (P < 0.001). The analysis of the medical expenses by age showed that on average, medical expenses for children were approximately 4,900 USD lower for children than for patients over 80 years of age. The linear regression analysis also showed that patients who were 0-9 years old spent 87% and those aged 10-19 118% less on medical expenses than those aged 70 and over, even after the correction of other variables (P < 0.001). The probability of hospitalization was the lowest at 10-19 years old (odds ratio [OR], 0.05; 95% confidence interval [CI], 0.03-0.09), and their ICU admission rate was also the lowest at 0.14 (OR, 0.14; 95% CI, 0.08-0.24). On the other hand, the likelihood of hospitalization and ICU admission was the highest in children aged 0-9 years, and among patients under the age of 50 years in general.

CONCLUSION

This study demonstrated the low severity of SARS-CoV-2 infection in younger patients (0-19 years) by analyzing the LOS, medical expenses, hospital, and intensive care unit admission rates as outcome variables. As the possibility to develop severe infection of coronavirus at the age of 10-19 was the lowest, a mitigation policy is also required for middle and high school students. In addition, children with underlying diseases need to be protected from high-risk infection environments.

Performance of severity of illness classification for Clostridium difficile infection to predict need-for-colectomy or inpatient death

BACKGROUND

In current state of practice, disease severity assessment for Clostridium difficile infection (CDI) lacks consensus between different organizations. In the latest guidelines for management of CDI, authors have proposed a new disease severity classification. This classification has been derived from expert opinion and includes previously reported patient related factors that predict unfavorable outcome in CDI.

OBJECTIVE

To evaluate the performance of new disease severity classification to predict CDI-related colectomy or in-patient deaths.

METHODS

This observational study was performed at a 300-bed community hospital catering to a suburban population. All the adult patients discharged during October 2005 through September 2012 and diagnosed with CDI were included in the study. Cases of CDI were identified using the billing database. Demographic and clinical characteristics of CDI cases were extracted from medical chart reviews performed by two physician researchers. Cases were classified as mild-to-moderate, severe, or severe and complicated CDI. Major outcomes measured were in-patient deaths and colectomy attributed to CDI. For risk stratification, each variable of severe and complicated CDI was counted.

RESULTS

In total, 59,897 patients were discharged from our hospital during the study period; 894 of them were diagnosed with CDI. Mean age of CDI cases was 74 years (standard deviation 15 years), 345 (39%) were male, and median length of hospital stay was 7 days (interquartile range 4-13). One hundred ninety-one patients (21%) were classified as mild-to-moderate, 93 patients (10%) as severe, and 610 patients (68%) as severe and complicated. In total, 14 patients underwent colectomy for CDI and 53 patients expired. In 35 of these patients, the cause of death was thought to be CDI. The combined outcome (CDI-related colectomy and/or death in hospital) occurred in 47 patients. None of the patients in mild-to-moderate disease or severe disease had combined outcome. On severe and complicated cases, as the score increased, rate of combined outcome increased significantly (z-12.7, p<0.0001). On plotting receiver-operating curve, the simple variable count had area under the curve of 0.91.

CONCLUSION

The newly proposed disease severity classification for CDI categorized more than two-thirds of patients as severe and complicated. Increase in number of severe and complicated classifying variables increases the chance of adverse outcomes significantly. Patients meeting only one variable could be potentially treated as a severe case instead of severe and complicated. This data needs to validated prospectively before could be used in clinical practice.

Microalbuminuria: An inexpensive, non invasive bedside tool to predict outcome in critically ill patients

This study was conducted to evaluate whether microalbuminuria on admission and after 24 hrs of admission to intensive care unit (ICU) predicts outcome as well as the Acute Physiology and Chronic Health Evaluation (APACHE) II severity illness score, the current accepted method of doing so. The study was carried out in a 20 bed mixed medical-surgical ICU of a tertiary care hospital. Of 525 consecutive adult patients with ICU stay of more than 24 hrs, 238 were included for the study. Patients with pregnancy, menstruation, anuria, macroscopic hematuria, urinary tract infection, marked proteinuria due to renal and post-renal structural diseases, were excluded. Spot urine samples were collected on admission to ICU and 24 hrs thereafter. Urine albumincreatinine ratio (ACR) was measured on ICU admission (ACR1) and after 24 hrs (ACR2) and expressed in mg/g. Patient demographics were noted on admission. For disease severity scoring, APACHE II scores were calculated. Each patient was followed up throughout their ICU stay for a maximum of 28 days and the following outcome data were obtained: ICU length of stay and ICU mortality. Of the 238 patients, 196 survived while 42 patients died in the ICU. Non-survivors had a significantly higher median ACR2 [162.7 mg/g (IQR 69.5-344.3)] in comparison to the survivors who had a median ACR2 = 54.4 mg/g (IQR 19.0-129.1) (P< 0.0001). The median ACR1 [161.0 mg/g (IQR 29.0-369.3)] of non-survivors was higher than the median ACR1 [80.4 mg/g (IQR 35.1-167.6)] of survivors but failed to reach statistical significance (P= 0.0948). In a receiver operating characteristic curve (ROC) analysis, ACR2 emerged as the best indicator of mortality [(area under curve (AUC) of ACR2 = 0.71 > AUC (ACR1) =0.58 > AUC (ΔACR) =0.55] similar to the currently used APACHE II scores (AUC = 0.78) (P=0.3). At a cutoff of 101 mg/g, ACR2 had a sensitivity of 69%, specificity of 67%, positive predictive value of 31% and a negative predictive value of 91% for predicting mortality in the critically ill patients. Absence of significant microalbuminuria at 24 hrs of ICU admission may help to predict survival in the ICU.