External validation of the International Risk Prediction Algorithm for the onset of generalized anxiety and/or panic syndromes (The Predict A) in the US general population

2019 ◽  
Vol 64 ◽  
pp. 40-44 ◽  
Author(s):  
Yeshambel T. Nigatu ◽  
JianLi Wang
Author(s):  
Sherry M Bumpus ◽  
Steven T Heidt ◽  
Rachel Krallman ◽  
Eva Kline-Rogers

Background: Fibromuscular dysplasia (FMD) is a polyvascular disorder that may result in narrowing, aneurysm, or dissection of affected arteries. A recent qualitative study illuminated common themes relative to being diagnosed and living with FMD. This study sought to quantitatively explore these themes in a larger sample. Methods: Patients from a single site in the US Registry for FMD (USRFMD) were eligible to participate. Subjects received an initial survey packet and up to two reminders between July and September 2015; surveys were returned via U.S. mail or online. Surveys were linked to the USRFMD database, from which clinical data was drawn. The survey included valid and reliable instruments including the Patient Health Questionnaire (PHQ) 9, PHQ-15, and the Generalized Anxiety Disorder Questionnaire. Results: Of 91 surveys mailed, 72 were completed (79.1%). Most respondents were female (94.4%, n=68) and white (97.2%, n=70), with a mean age at diagnosis of 52.7 ± 11.9 years and had been living with FMD for a mean of 9.7 ± 8.1 years. Medical history did not differ significantly between participants and non-participants. Screening showed that 21.7% of patients experienced moderate depression, 40.7% experienced significant physical symptoms, and 10.4% experienced moderate generalized anxiety. Though not statistically significant, there was a trend towards reduced mental health symptoms over time (Figure 1) and higher symptomatology with treatment delays of 1-5 years (data not shown). No differences were found in mental health based on number or location of vessels affected by FMD. Patients who had experienced an adverse event (e.g. stroke, TIA, MI, dissection, renal infarction, mesenteric ischemia) reported more physical symptoms (57.1% v. 23.1%, p=.014). Conclusion: Among patients from a single center participating in the USRFMD, rates of anxiety and depression are nearly double that of the general population. Trends indicate that depression, physical symptoms, and anxiety may decrease over time. Given the higher rates of anxiety, depression, and somatoform symptoms compared to the general population, greater efforts are needed to make earlier diagnoses and support patients, particularly in the early stages post-diagnosis.


2010 ◽  
Vol 26 (5) ◽  
pp. 359-368 ◽  
Author(s):  
Emilie Bérard ◽  
Vanina Bongard ◽  
Dominique Arveiler ◽  
Philippe Amouyel ◽  
Aline Wagner ◽  
...  

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2021-217580
Author(s):  
Colin R Simpson ◽  
Chris Robertson ◽  
Steven Kerr ◽  
Ting Shi ◽  
Eleftheria Vasileiou ◽  
...  

BackgroundThe QCovid algorithm is a risk prediction tool that can be used to stratify individuals by risk of COVID-19 hospitalisation and mortality. Version 1 of the algorithm was trained using data covering 10.5 million patients in England in the period 24 January 2020 to 30 April 2020. We carried out an external validation of version 1 of the QCovid algorithm in Scotland.MethodsWe established a national COVID-19 data platform using individual level data for the population of Scotland (5.4 million residents). Primary care data were linked to reverse-transcription PCR (RT-PCR) virology testing, hospitalisation and mortality data. We assessed the performance of the QCovid algorithm in predicting COVID-19 hospitalisations and deaths in our dataset for two time periods matching the original study: 1 March 2020 to 30 April 2020, and 1 May 2020 to 30 June 2020.ResultsOur dataset comprised 5 384 819 individuals, representing 99% of the estimated population (5 463 300) resident in Scotland in 2020. The algorithm showed good calibration in the first period, but systematic overestimation of risk in the second period, prior to temporal recalibration. Harrell’s C for deaths in females and males in the first period was 0.95 (95% CI 0.94 to 0.95) and 0.93 (95% CI 0.92 to 0.93), respectively. Harrell’s C for hospitalisations in females and males in the first period was 0.81 (95% CI 0.80 to 0.82) and 0.82 (95% CI 0.81 to 0.82), respectively.ConclusionsVersion 1 of the QCovid algorithm showed high levels of discrimination in predicting the risk of COVID-19 hospitalisations and deaths in adults resident in Scotland for the original two time periods studied, but is likely to need ongoing recalibration prospectively.


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