BACKGROUND AND PURPOSE: A systematic review found an association between the July start of internships and residencies and higher mortality rates for hospitalized patients, but data related to stroke are limited. We assessed seasonal variations in 30-day risk-adjusted mortality rates (RAMRs) after ischemic stroke by hospital teaching status. METHODS: The analysis included all fee-for-service Medicare beneficiaries aged ≥ 65 years with a primary discharge diagnosis of ischemic stroke (International Classification of Diseases, 9th revision, codes 433, 434, and 436) from 1999 to 2006. Hierarchical linear regression models calculated RAMRs, adjusting for patient demographics and comorbidities. Annual data were combined and reconstructed for time series analyses; RAMRs were calculated for each month. Structural models compared monthly seasonal patterns stratified by hospital teaching status. RESULTS: Of 2 824 694 ischemic stroke discharges, 51.7% were from teaching hospitals. There were seasonal patterns within each calendar year, with the highest 30-day RAMR in the winter and the lowest in the summer, but with a smaller peak in July. Thirty-day RAMRs decreased from 1999 to 2006, as did seasonal variations within each calendar year. Seasonal patterns were similar for teaching and nonteaching hospitals. CONCLUSIONS: The 30-day RAMR decreased overall, but seasonal patterns were present, with the highest RAMR in January and a smaller peak in July. Because patterns were similar for teaching and nonteaching hospitals, the July peak cannot be explained by the introduction of new trainees in the beginning of the academic year. The reasons for these seasonal patterns warrant further investigation.
BACKGROUND AND PURPOSE: A systematic review found an association between the July start of internships and residencies and higher mortality rates for hospitalized patients, but data related to stroke are limited. We assessed seasonal variations in 30-day risk-adjusted mortality rates (RAMRs) after ischemic stroke by hospital teaching status. METHODS: The analysis included all fee-for-service Medicare beneficiaries aged ≥ 65 years with a primary discharge diagnosis of ischemic stroke (International Classification of Diseases, 9th revision, codes 433, 434, and 436) from 1999 to 2006. Hierarchical linear regression models calculated RAMRs, adjusting for patient demographics and comorbidities. Annual data were combined and reconstructed for time series analyses; RAMRs were calculated for each month. Structural models compared monthly seasonal patterns stratified by hospital teaching status. RESULTS: Of 2 824 694 ischemic stroke discharges, 51.7% were from teaching hospitals. There were seasonal patterns within each calendar year, with the highest 30-day RAMR in the winter and the lowest in the summer, but with a smaller peak in July. Thirty-day RAMRs decreased from 1999 to 2006, as did seasonal variations within each calendar year. Seasonal patterns were similar for teaching and nonteaching hospitals. CONCLUSIONS: The 30-day RAMR decreased overall, but seasonal patterns were present, with the highest RAMR in January and a smaller peak in July. Because patterns were similar for teaching and nonteaching hospitals, the July peak cannot be explained by the introduction of new trainees in the beginning of the academic year. The reasons for these seasonal patterns warrant further investigation.
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Authors: Stacy Y Chu; Margueritte Cox; Gregg C Fonarow; Eric E Smith; Lee Schwamm; Deepak L Bhatt; Roland A Matsouaka; Ying Xian; Kevin N Sheth Journal: J Am Heart Assoc Date: 2018-11-20 Impact factor: 5.501
Authors: Jane Nakibuuka; Martha Sajatovic; Joaniter Nankabirwa; Charles Ssendikadiwa; Nelson Kalema; Arthur Kwizera; Jayne Byakika-Tusiime; Anthony J Furlan; James Kayima; Edward Ddumba; Elly Katabira Journal: PLoS One Date: 2016-05-04 Impact factor: 3.240
Authors: Marco Gonzalez-Castellon; Christine Ju; Ying Xian; Adrian Hernandez; Gregg C Fonarow; Lee Schwamm; Eric E Smith; Deepak L Bhatt; Matthew Reeves; Joshua Z Willey Journal: J Am Heart Assoc Date: 2018-01-31 Impact factor: 5.501