“…Over 24 months, 586 drug-resistant ESKAPEE HAIs occurred in 439 patients (0.3% of 179,629 inpatients) with a mean age of 63 years, with 43% being treated in intensive care units (ICUs), and having a 45% inpatient mortality rate. Interrupted time series analysis revealed increasing infection rates before the intervention that were sharply interrupted by abrupt drops for most pathogens and henceforth remained stable in the ICUs but progressively increased in ordinary wards. …”
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“…The effect of the 2008 and 2010 FDA DSCs was measured using interrupted time-series analysis. Subgroups of patients with greater cardiovascular risk were also examined. …”
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“…METHODS: We conducted a population-based time series analysis using national administrative health databases in Canada. …”
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“…The Seasonal Decomposition of Time Series by Loess was used for time series analysis. RESULTS: The total number of consultations increased after the start of the pandemic and peaked around the beginning of 2022, before subsequently falling despite the increase in the number of COVID-19 infections. …”
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“…Therefore, we propose a deep learning model that combines machine vision and time series analysis. This model aims to meet the requirement of timely and accurate detection of aggressive behavior in large-scale sheep farming. …”
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“…Our interrupted time series analysis showed an average increase in visits by 2.52 per 10,000 person-months and in prescriptions by 6.69 per 10,000 person-months across all ages and sexes. …”
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“…And our work provides an alternative framework for time series analysis.…”
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“…To evaluate the impact of the campaign, we tracked online metrics, including website visits, and conducted an interrupted time-series analysis of foot traffic data in our target states for all tanning salons documented on SafeGraph from January 1, 2018 to 3 months after the campaign. …”
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“…An interrupted time-series analysis based on a linear regression was used. …”
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“…METHODS: We evaluated changes in the trends for each procedure after its inclusion in the EBI’s first list of guidelines using interrupted time series analysis. We explored whether there was any evidence of spill-over effects onto related or substitute procedures, as well as exploring changes in geographical variation following the publication of national guidance. …”
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“…Given the similarities in their sociocultural history, a time series analysis was conducted to assess recent sex and age trends of suicide in the Indigenous and general populations in the United States, Australia and New Zealand. …”
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“…Descriptive and time-trend analyses were applied to the data. Time series analysis was analyzed using the best fit autoregressive integrated moving average (ARIMA) model to look for seasonality in trends and forecasting. …”
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“…METHODS: In this time-series analysis, we compared the outcomes of patients who participated in the pharmacist-led opioid de-escalation (PLODE) program after completing concurrent radiotherapy (CRT) between June 2018 and February 2019 against patients who completed CRT between June 2017 and March 2018 and did not participate in the program. …”
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“…METHODS: Using electronic health records from a large pediatric primary care network in 2018–2022, we cross-sectionally examined 163,042 well visits of 2–17 year-olds living in Philadelphia county in order to examine (1) the pandemic’s effect on obesity prevalence and (2) moderation by census-tract-level neighborhood socioeconomic disadvantage, crime, food and physical activity-related environments using interrupted-time-series analysis, Poisson regression, and logistic regression. …”
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“…Data from the District Health Information System (DHIS) were used to conduct an interrupted time series analysis that assessed the changes in TB investigations and confirmed TB cases during four pandemic periods: lockdown and the subsequent three peaks of infection compared to the two years prior (2018–2022). …”
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“…METHOD: Descriptive statistics and time-series analysis explored monthly NHS App use from January 2019–May 2021. …”
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“…We performed an interrupted time series analysis to examine the trend of cancer-related telehealth use within 1 month of diagnosis relative to the timing of the COVID-19 public health emergency and multivariable logistic regressions to examine factors—specifically, state parity laws and regulations on cross-state practice—associated with telehealth. …”
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“…Next, interrupted time series analysis examined changes in online misogyny prevalence, before and during COVID-19. …”
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“…We used an interrupted time series analysis to examine monthly psychiatric admission trend before and after service implementation, considering socioeconomic and environmental covariates. …”
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“…Specifically, 90-day mortality was 22% and 13.2% for underweight and normal weight respectively, versus 7–9% for others (p < 0.001). Multivariate time series analysis revealed underweight individuals had a significantly higher 5-year mortality risk (HR 1.41 (95% CI 1.27–1.58, p < 0.001)), while overweight and obese categories had a reduced risk (overweight—HR 0.76 (95% CI 0.72–0.80, p < 0.001), obesity class I—HR 0.71 (95% CI 0.66–0.76, p < 0.001), obesity class II—HR 0.77 (95% CI 0.70–0.85, p < 0.001), and obesity class III—HR 0.79 (95% CI 0.67–0.92, p = 0.003)). (4) Conclusions: In this comprehensive study, obesity was independently associated with decreased short- and long-term mortality. …”
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