Prediction model for prolonged length of stay in patients with community-acquired pneumonia based on Japanese administrative data

Predictors of Length of Stay, Rehospitalization and Mortality in Community-Acquired Pneumonia Patients: A Retrospective Cohort Study

BACKGROUND

Community-acquired pneumonia (CAP) represents one of the leading causes of hospitalization and has a substantial impact on the financial burden of healthcare. The aim of this study was to identify factors associated with the length of hospital stay (LOHS), rehospitalization and mortality of patients admitted for CAP.

METHODS

A retrospective cohort study was conducted with patients presenting to a Swiss public hospital between January 2019 and December 2019. Zero-truncated negative binomial and multivariable logistic regression analyses were performed to assess risk factors.

RESULTS

A total of 300 patients were analyzed (median 78 years, IQR [67.56, 85.50] and 53% males) with an average LOHS of 7 days (IQR [5.00, 9.00]). Of the 300 patients, 31.6% (97/300) were re-hospitalized within 6 months, 2.7% (8/300) died within 30 days and 11.7% (35/300) died within 1 year. The results showed that sex (IRR = 0.877, 95% CI = 0.776-0.992, p-value = 0.036), age (IRR = 1.007, 95% CI = 1.002-1.012, p-value = 0.003), qSOFA score (IRR = 1.143, 95% CI = 1.049-1.246, p-value = 0.002) and atypical pneumonia (IRR = 1.357, 95% CI = 1.012-1.819, p-value = 0.04) were predictive of LOHS. Diabetes (OR = 2.149, 95% CI = 1.104-4.172, p-value = 0.024), a higher qSOFA score (OR = 1.958, 95% CI = 1.295-3.002, p-value = 0.002) and rehabilitation after discharge (OR = 2.222, 95% CI = 1.017-4.855, p-value = 0.044) were associated with a higher chance of being re-hospitalized within 6 months, whereas mortality within 30 days and within one year were both associated with older age (OR = 1.248, 95% CI = 1.056-1.562, p-value = 0.026 and OR = 1.073, 95% CI = 1.025-1.132, p-value = 0.005, respectively) and the presence of a cancer diagnosis (OR = 32.671, 95% CI = 4.787-369.1, p-value = 0.001 and OR = 4.408, 95% CI = 1.680-11.43, p-value = 0.002, respectively).

CONCLUSION

This study identified routinely available predictors for LOHS, rehospitalization and mortality in patients with CAP, which may further advance our understanding of CAP and thereby improve patient management, discharge planning and hospital costs.

LONG-HOSP Score: A Novel Predictive Score for Length of Hospital Stay in Acute Lower Gastrointestinal Bleeding - A Multicenter Nationwide Study

INTRODUCTION

Length of stay (LOS) in hospital affects cost, patient quality of life, and hospital management; however, existing gastrointestinal bleeding models applicable at hospital admission have not focused on LOS. We aimed to construct a predictive model for LOS in acute lower gastrointestinal bleeding (ALGIB).

METHODS

We retrospectively analyzed the records of 8,547 patients emergently hospitalized for ALGIB at 49 hospitals (the CODE BLUE-J Study). A predictive model for prolonged hospital stay was developed using the baseline characteristics of 7,107 patients and externally validated in 1,440 patients. Furthermore, a multivariate analysis assessed the impact of additional variables during hospitalization on LOS.

RESULTS

Focusing on baseline characteristics, a predictive model for prolonged hospital stay was developed, the LONG-HOSP score, which consisted of low body mass index, laboratory data, old age, nondrinker status, nonsteroidal anti-inflammatory drug use, facility with ≥800 beds, heart rate, oral antithrombotic agent use, symptoms, systolic blood pressure, performance status, and past medical history. The score showed relatively high performance in predicting prolonged hospital stay and high hospitalization costs (area under the curve: 0.70 and 0.73 for derivation, respectively, and 0.66 and 0.71 for external validation, respectively). Next, we focused on in-hospital management. Diagnosis of colitis or colorectal cancer, rebleeding, and the need for blood transfusion, interventional radiology, and surgery prolonged LOS, regardless of the LONG-HOSP score. By contrast, early colonoscopy and endoscopic treatment shortened LOS.

CONCLUSIONS

At hospital admission for ALGIB, our novel predictive model stratified patients by their risk of prolonged hospital stay. During hospitalization, early colonoscopy and endoscopic treatment shortened LOS.

Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors

BACKGROUND

Despite an abundance of information on the risk factors of SARS-CoV-2, there have been few US-wide studies of long-term effects. In this paper we analyzed a large medical claims database of US based individuals to identify common long-term effects as well as their associations with various social and medical risk factors.

METHODS

The medical claims database was obtained from a prominent US based claims data processing company, namely Change Healthcare. In addition to the claims data, the dataset also consisted of various social determinants of health such as race, income, education level and veteran status of the individuals. A self-controlled cohort design (SCCD) observational study was performed to identify ICD-10 codes whose proportion was significantly increased in the outcome period compared to the control period to identify significant long-term effects. A logistic regression-based association analysis was then performed between identified long-term effects and social determinants of health.

RESULTS

Among the over 1.37 million COVID patients in our datasets we found 36 out of 1724 3-digit ICD-10 codes to be statistically significantly increased in the post-COVID period (p-value < 0.05). We also found one combination of ICD-10 codes, corresponding to 'other anemias' and 'hypertension', that was statistically significantly increased in the post-COVID period (p-value < 0.05). Our logistic regression-based association analysis with social determinants of health variables, after adjusting for comorbidities and prior conditions, showed that age and gender were significantly associated with the multiple long-term effects. Race was only associated with 'other sepsis', income was only associated with 'Alopecia areata' (autoimmune disease causing hair loss), while education level was only associated with 'Maternal infectious and parasitic diseases' (p-value < 0.05).

CONCLUSION

We identified several long-term effects of SARS-CoV-2 through a self-controlled study on a cohort of over one million patients. Furthermore, we found that while age and gender are commonly associated with the long-term effects, other social determinants of health such as race, income and education levels have rare or no significant associations.

Comparison of Length of Hospital Stay for Community-Acquired Infections Due to Enteric Pathogens, Influenza Viruses and Multidrug-Resistant Bacteria: A Cross-Sectional Study in Hungary

Community-acquired infections (CAI) can affect the duration of care and mortality of patients. Therefore, we aimed to investigate these as well as factors influencing the length of hospital stay in patients with CAI due to enteric pathogens, influenza viruses and multidrug-resistant (MDR) bacteria. We obtained data on 531 patients with CAI from the medical databases of a Hungarian university hospital and analyzed their characteristics using a regression model. Patients with MDR bacterial infection had the highest mortality (26.24%) and they stayed significantly longer in the hospital than cases with other CAIs. Our results showed that infection by Clostridioides difficile (odds ratio (OR): 6.98, 95% confidence interval (CI): 1.03-47.48; p = 0.047), MDR Escherichia coli (OR: 7.64, 95% CI: 1.24-47.17; p = 0.029), MDR Klebsiella spp. (OR: 7.35, 95% CI: 1.15-47.07; p = 0.035) and hospitalization in the department of pulmonology (OR: 5.48, 95% CI: 1.38-21.76; p = 0.016) and surgery (OR: 4.19, 95% CI: 1.18-14.81; p = 0.026) significantly increased, whereas female sex (OR: 0.62, 95% CI: 0.40-0.97; p = 0.037) and hospitalization in the department of pediatrics (OR: 0.17, 95% CI: 0.04-0.64; p = 0.009) decreased the odds of staying in the hospital for more than 6 days. Our findings provide new information on the epidemiology of CAI and can contribute to the development of public health programs that decrease the burden of infections acquired in the community.