/UOHI_PCI_Log

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UOHI_PCI_Log

How to

  1. Get your PCI data from Richard Jung (rjung@ottawaheart.ca) as an EXCEL SPREADSHEET *.XLSX file. Make sure you save the file without a password so that the Terminal can open it (Open it in Excel -> Go to File - > Passwords and type the current password, then under 'New Password' leave the field empty)

On MACOS

  1. Install Github https://gist.github.com/derhuerst/1b15ff4652a867391f03

  2. On MacOS : Open Terminal by doing CMD + SPACE and searching for 'Terminal'

  3. In the new window clone this GitHub reposity by typing 'git clone https://github.com/robertavram-md/UOHI_PCI_Log.git'

  4. You will have a new folder where Terminal or command Prompt was opened called UOHI_PCI_Log

  5. Change directory to UOHI_PCI_Log by typing the following cd UOHI_PCI_Log

  6. Install Python https://www.python.org/downloads/

  7. Put your PCI data .xlsx file into the folder called UOHI_PCI_Log

  8. Run in terminal pip install pandas

  9. Run this command in terminal python ComputeMetrics.py '**filename**'

For example if your PCI Log book is named avram_18_11_2020.xlsx then you should run python ComputeMetrics.py 'avram_18_11_2020.xlsx'

On Windows:

  1. Install Github https://gist.github.com/derhuerst/1b15ff4652a867391f03

  2. On Windows : Use Windows+R on your keyboard to open “Run” box. Type “cmd” and then click “OK” to open a regular Command Prompt.

  3. In the new window clone this GitHub reposity by typing 'git clone https://github.com/robertavram-md/UOHI_PCI_Log.git'

  4. You will have a new folder where Terminal or command Prompt was opened called UOHI_PCI_Log

  5. Install Python https://www.python.org/downloads/

  6. Put your PCI data .xlsx file into the folder called UOHI_PCI_Log

  7. Run in Command Prompt pip install pandas

  8. Run in Command Prompt python ComputeMetrics.py '**filename**'

For example if your PCI Log book is named avram_18_11_2020.xlsx then you should run python ComputeMetrics.py 'avram_18_11_2020.xlsx'

Output

You will get three files

  1. condensed_summary_.csv Contains the summary of number of cases breakdown as required by the royal college
  2. overall_.csv Contains all your cases, including diagnostics. The last columns in the file can be used to 'filter' the required data
  3. interventions_.csv Contains all the intervention data. The last columns in the file can be used to 'filter' the required data (i.e. select all the Bifurcation cases

Definitions

  1. Calcified cases are defined by any case where you required a 'rotablator', 'guideliner' or 'cutting balloon' np.where(((df_intervention['guideliner_used']=='Yes') | (df_intervention['thrombectomy_used']=='Yes') | (df_intervention['distal_protection_used']=='Yes') | (df_intervention['rotablator_used']=='Yes') | (df_intervention['cutting_balloon_used']=='Yes')| (df_intervention['lm_interv']==True) | (df_intervention['bifurcation_interv']==True)
  2. Complicated cases are defined by any LEFT MAIN PCI, BIFURCATION, CALCIFIED LESION, USE OF ROTABLATOR, THROMBECTOMY CATHETER USED, DISTAL PROTECTION DEVICE USED or GUIDELINER
  3. It is currently impossible to know how many 'bypass' grafts or 'CTOs' you have done unless you specified them as 'free text' in the last box in the CAPITAL_PCI registry entry.
  4. PCI cases include any balloon angioplasty or stent deployment; it does not include simple diagnostic FFR, IFR, IVUS or OCT.
  5. Hemodynamic instability is defined by the presence of either of the following 'ROSC', 'Cardiac arrest complication', 'Arythmia complicated' or 'intubated patient'