Publications by MT
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Table 1 Baseline characteristics of groups Characteristic Overall, N = 8371 Cardiac surgery, N = 6061 NOT Cardiac surgery, N = 2311 p-value2 surgery_date 2018-01-29 to 2023-01-14 2018-01-29 to 2023-01-14 2019-03-19 to 2023-01-03 0.3 afib_type 0.044 Paroxysmal atrial fibrillation 439 (52%) 328 (54%) 111 (48%) Unspecified atrial...
1267 sym 11 tbl
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Table 1 Baseline characteristics of groups Characteristic Overall, N = 8371 Cardiac surgery, N = 6061 NOT Cardiac surgery, N = 2311 p-value2 surgery_date 2018-01-29 to 2023-01-14 2018-01-29 to 2023-01-14 2019-03-19 to 2023-01-03 0.3 afib_type 0.044 Paroxysmal atrial fibrillation 439 (52%) 328 (54%) 111 (48%) Unspecified atrial...
1281 sym 12 tbl
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Hello everyone! I created this report using our REDCap COVID-19 imaging database. Data collection This table shows how much data we have already collected in REDCap. Tables with outcomes We tentatively chose the primary endpoint as a composite of: Death Intubation Vasopressor use during hospitalization In hospital cardiac arrest Thi...
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3/30 10:50
Characteristic MV1 js-crossover MV2 mim-crossover log(OR)1 95% CI1 p-value log(OR)1 95% CI1 p-value black -0.34 -1.2, 0.48 0.4 -1.8 -3.8, -0.42 0.027 heart_rate_1 0.07 -0.03, 0.17 0.2 0.14 -0.01, 0.27 0.049 beats_accepted -0.01 -0.02, 0.00 0.14 -0.01 -0.02, 0.00 0.063 bmi_combined 0.07 0.02, 0.13 0.010 0.11 0.03, 0.19 0.007 es_volume_1 0....
4 sym 1 tbl
COVID-19 Variables
Variable analysis COVID-19 Imaging database In this document I wanted to have a quick look at variables that we decided to collect in the remaining patients, focusing on variable counts and missing values. This way we can reevaluate our list of variables to recollect and also see the weaknesses in our collected data and prevent the mistakes in th...
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Intro Results might change a little bit as we clean data more but should not change too much and I assume that we our statistical significance / insignificance will remain where it is now. Figure 1 For now it is in the format that we had in our manuscript, I will likely change it so the bars PRE and POST intervention are by the side with p valu...
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MUGA 4/10/2021
knitr::opts_chunk$set( echo = TRUE, warning = FALSE, fig.align = "center", dev = "png", cache = TRUE, error = FALSE, include = TRUE, message = FALSE) library("labelled") library("knitr") library("gdtools") library("rlang") library("htmltools") library("kableExtra") library("reactable") library("ggthemes") library...
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Intervention all participants Variable Overall, N = 181 before intervention, N = 91 after intervention, N = 90 p-value1 please_specify_your_role_in_the_hospital, n (%) 0.008 Attending physician 4 (2.2%) 2 (2.2%) 2 (2.2%) Fellow 3 (1.7%) 3 (3.3%) 0 (0%) Not listed above, please specify 16 (8.8%) 9 (9.9%) 7 (7.8%) Nurse 97 (54%) 38 (42%) 59 ...
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Document
General information: Basic information Metadata for the file “combined_cpet_se_after_mi.csv”. Each row represents one patient. Authors of the dataset: Krzysztof Smarz, Department of Cardiology, Centre of Postgraduate Medical Education, Grochowski Hospital, Warsaw, Poland Maciej Tysarowski, Department of Medicine, Rutgers New Jersey Medical ...
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