2020
DOI: 10.1159/000511205
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Joinpoint Regression Analysis of Trends in Multiple Sclerosis Incidence in Kuwait: 1980–2019

Abstract: <b><i>Background:</i></b> Multiple sclerosis (MS) is a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system with unknown precise etiology. Temporally, a tendency for increasing MS incidence has been recorded worldwide. This cross-sectional cohort study sought to quantify trends in the age-standardized incidence rates (ASIRs) (per million person-years) of MS in Kuwait from 1980 to 2019, overall and by subcohorts defined by age at MS onset, sex, a… Show more

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Cited by 10 publications
(10 citation statements)
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“…The average annual percent change (AAPC) and corresponding 95% confidence interval (CI) were calculated as the weighted average of the segment trends. 17 The clusters were named as hot and cold spots, which were defined as the countries with significant clusters with higher or lower rates. 19 p < 0.05 was considered statistically significant.…”
Section: Discussionmentioning
confidence: 99%
“…The average annual percent change (AAPC) and corresponding 95% confidence interval (CI) were calculated as the weighted average of the segment trends. 17 The clusters were named as hot and cold spots, which were defined as the countries with significant clusters with higher or lower rates. 19 p < 0.05 was considered statistically significant.…”
Section: Discussionmentioning
confidence: 99%
“…We used joinpoint regression analysis to assess the variation in the trends of the rate of vaccinations, SARS-CoV-2 cases, COVID-19-related ICU admissions and COVID-19-related deaths. With this technique, we can identify the week (joinpoint) where a statistically significant abrupt change in temporal trends has occurred [ 15 ]. For vaccinations against SARS-CoV-2, the analysis identified 5 joinpoints leading to 6 periods where different trends were observed ( Table 2 ).…”
Section: Resultsmentioning
confidence: 99%
“…We used a joinpoint regression model in order assess the variation in the trends of the rates of SARS-CoV-2 cases, COVID-19-related ICU admissions and COVID-19-related deaths, as previously described [ 14 ]. Briefly, this model investigates the combinations of trends that result in a statistically significantly better fit to a data series than a single-trend line fitted by Poisson regression or time-series models [ 15 ]. The Joinpoint Regression Program (3.5.2) and SPSS 20 were used to analyze the data.…”
Section: Methodsmentioning
confidence: 99%
“…Using this procedure, it is possible to determine the number of joinpoints that are necessary to assess significant changes in incidence trends over time. This technique is used to identify the calendar year (joinpoint) in which statistically significant abrupt changes in temporal trends occurred ( 21 ). The number and locations of joinpoints and the corresponding p -values were determined by Monte Carlo permutation tests, and the model fit was tested using a Bayesian information criterion.…”
Section: Methodsmentioning
confidence: 99%