ABSTRACT
PURPOSE: To evaluate the burden of illness--length of stay (LOS), total charges, and discharge disposition--among cancers of the lip, oral cavity and pharynx (CLOP) patients with and without palliative care (PC) referral. METHODS: This cross-sectional study utilized the 2017 National inpatient sample database to identify hospitalizations with a primary diagnosis of CLOP. Generalized linear models were used to assess the association between PC referral status and the outcomes-LOS, total charges, and discharge disposition while controlling for patients' characteristics. RESULTS: There were 4165 PC referral among 52, 524 CLOP patients. The geometric mean of LOS for non-PC referral patients was 3.7 days, and for PC referral was 5.02 days, P < 0.001. In the adjusted analysis, CLOP patients with PC referral were more likely to have a higher LOS (Coefficient:1.16; 95% CI, 1.01-1.25) compared to those without PC referral. The geometric mean of total charge among non-PC referral group was 48,308 USD, and CLOP-PC referral was 48,983 USD, P = 0.72. After adjusting for covariates, there was still no significant difference between the PC and non-PC referral groups. Discharge disposition were considerably different across the non-PC vs. PC referral groups. Compared to non-PC referral patients, PC referral patients were more likely to be discharge to skilled nursing facility, intermediate care, and another type of facility (aOR = 7.10; CIs, 5.51-9.12), or home health care (aOR = 4.13; CIs, 3.31-5.15). CONCLUSION: During primary hospitalization, total charges was not different between patient non-PC and PC referral groups; however, the LOS and discharge dispositions were significantly different.
Subject(s)
Neoplasms , Palliative Care , Cost of Illness , Cross-Sectional Studies , Hospitalization , Humans , Length of Stay , Lip , Neoplasms/epidemiology , Neoplasms/therapy , Patient Discharge , Pharynx , Referral and Consultation , Retrospective StudiesABSTRACT
OBJECTIVES: Little is known about maturation of the airway microbiota during early childhood and the consequences of early-life antibiotic exposure. METHODS: In a population-based birth cohort of 902 healthy Finnish children, we applied deep neural network models to investigate the relationship between the nasal microbiota (measured by 16S rRNA gene sequencing at up to three time points) and child age during the first 24 months. We also performed stratified analyses according to antibiotic exposure during the age period 0-2 months. RESULTS: The dense deep neural network analysis successfully modelled the relationship between 232 bacterial genera and child age with a mean absolute error of 4.3 (95%CI 4.0-4.7) months. Similarly, the recurrent neural network analysis also successfully modelled the relationship between 215 genera and child age with a mean absolute error of 0.45 (95%CI 0.42-0.47) months. Among the genera, Staphylococcus spp. and members of the Corynebacteriaceae decreased with age, while Dolosigranulum and Moraxella increased with age in the first 2 years of life (all false discovery rate (FDR) = 0.001). In children without early-life antibiotic exposure, Dolosigranulum increased with age (FDR = 0.001). By contrast, in those with early-life antibiotic exposure, Haemophilus increased with age (FDR = 0.002). CONCLUSIONS: In this prospective birth cohort of healthy children, we demonstrated the development of the nasal microbiota, with shifts in specific genera constituting maturation, in the first 2 years of life. Antibiotic exposures during early infancy were related to different age-discriminatory bacteria.