##Instruction:
Database: thrombosis_prediction
Total Tables: 3
Total Columns: 64

Table Schemas:

Database: thrombosis_prediction
Total Tables: 3
Total Columns: 64

Table Schemas:

Table: Examination (13 columns)
-------------------------------
• ID (integer): identification of the patient
• Examination Date (date): Examination Date
• aCL IgG (real): anti-Cardiolipin antibody (IgG) concentration
• aCL IgM (real): anti-Cardiolipin antibody (IgM) concentration
• ANA (integer): anti-nucleus antibody concentration
• ANA Pattern (text): pattern observed in the sheet of ANA examination
• aCL IgA (integer): anti-Cardiolipin antibody (IgA) concentration
• Diagnosis (text): disease names
• KCT (text): measure of degree of coagulation
  Values: +: positive

-: negative
• RVVT (text): measure of degree of coagulation
  Values: +: positive

-: negative
• LAC (text): measure of degree of coagulation
  Values: +: positive

-: negative
• Symptoms (text): other symptoms observed
• Thrombosis (integer): degree of thrombosis
  Values: 0: negative (no thrombosis)
1: positive (the most serious)
2: positive (severe)3: positive (mild)

Table: Laboratory (44 columns)
------------------------------
• ID (integer): identification of the patient
• Date (date): Date of the laboratory tests (YYMMDD)
• GOT (integer): AST glutamic oxaloacetic transaminase
  Values: Commonsense evidence:

Normal range: N < 60
• GPT (integer): ALT glutamic pyruvic transaminase
  Values: Commonsense evidence:

Normal range: N < 60
• LDH (integer): lactate dehydrogenase
  Values: Commonsense evidence:

Normal range: N < 500
• ALP (integer): alkaliphophatase
  Values: Commonsense evidence:

Normal range: N < 300
• TP (real): total protein
  Values: Commonsense evidence:

Normal range: 6.0 < N < 8.5
• ALB (real): albumin
  Values: Commonsense evidence:

Normal range: 3.5 < N < 5.5
• UA (real): uric acid
  Values: Commonsense evidence:

Normal range: N > 8.0 (Male)N > 6.5 (Female)
• UN (integer): urea nitrogen
  Values: Commonsense evidence:

Normal range: N < 30
• CRE (real): creatinine
  Values: Commonsense evidence:

Normal range: N < 1.5
• T-BIL (real): total bilirubin
  Values: Commonsense evidence:

Normal range: N < 2.0
• T-CHO (integer): total cholesterol
  Values: Commonsense evidence:
Normal range: N < 250
• TG (integer): triglyceride
  Values: Commonsense evidence:

Normal range: N < 200
• CPK (integer): creatinine phosphokinase
  Values: Commonsense evidence:
Normal range: N < 250
• GLU (integer): blood glucose
  Values: Commonsense evidence:
Normal range: N < 180
• WBC (real): White blood cell
  Values: Commonsense evidence:
Normal range: 3.5 < N < 9.0
• RBC (real): Red blood cell
  Values: Commonsense evidence:

Normal range: 3.5 < N < 6.0
• HGB (real): Hemoglobin
  Values: Commonsense evidence:

Normal range: 10 < N < 17
• HCT (real): Hematoclit
  Values: Commonsense evidence:
Normal range: 29 < N < 52
• PLT (integer): platelet
  Values: Commonsense evidence:

Normal range: 100 < N < 400
• PT (real): prothrombin time
  Values: Commonsense evidence:

Normal range: N < 14
• APTT (integer): activated partial prothrombin time
  Values: Commonsense evidence:

Normal range: N < 45
• FG (real): fibrinogen
  Values: Commonsense evidence:

Normal range: 150 < N < 450
• PIC
• TAT
• TAT2
• U-PRO (text): proteinuria
  Values: Commonsense evidence:

Normal range: 0 < N < 30
• IGG (integer): Ig G
  Values: Commonsense evidence:

Normal range: 900 < N < 2000
• IGA (integer): Ig A
  Values: Commonsense evidence:

Normal range: 80 < N < 500
• IGM (integer): Ig M
  Values: Commonsense evidence:

Normal range: 40 < N < 400
• CRP (text): C-reactive protein
  Values: Commonsense evidence:

Normal range: N= -, +-, or N < 1.0
• RA (text): Rhuematoid Factor
  Values: Commonsense evidence:

Normal range: N= -, +-
• RF (text): RAHA
  Values: Commonsense evidence:

Normal range: N < 20
• C3 (integer): complement 3
  Values: Commonsense evidence:

Normal range: N > 35
• C4 (integer): complement 4
  Values: Commonsense evidence:

Normal range: N > 10
• RNP (text): anti-ribonuclear protein
  Values: Commonsense evidence:

Normal range: N= -, +-
• SM (text): anti-SM
  Values: Commonsense evidence:

Normal range: N= -, +-
• SC170 (text): anti-scl70
  Values: Commonsense evidence:

Normal range: N= -, +-
• SSA (text): anti-SSA
  Values: Commonsense evidence:

Normal range: N= -, +-
• SSB (text): anti-SSB
  Values: Commonsense evidence:

Normal range: N= -, +-
• CENTROMEA (text): anti-centromere
  Values: Commonsense evidence:

Normal range: N= -, +-
• DNA (text): anti-DNA
  Values: Commonsense evidence:

Normal range: N < 8
• DNA-II (integer): anti-DNA
  Values: Commonsense evidence:

Normal range: N < 8

Table: Patient (7 columns)
--------------------------
• ID (integer): identification of the patient
• SEX (text): Sex
  Values: F: female; M: male
• Birthday (date): Birthday
• Description (date): the first date when a patient data was recorded
  Values: null or empty: not recorded
• First Date (date): the date when a patient came to the hospital
• Admission (text): patient was admitted to the hospital (+) or followed at the outpatient clinic (-)
  Values: patient was admitted to the hospital (+) or followed at the outpatient clinic (-)
• Diagnosis (text): disease names

##Evidence:
female refers to Sex = 'F'; patient who were born after 1930 refers to year(Birthday) > '1930'; calculation = DIVIDE(COUNT(ID) where year(Birthday) > '1930' and SEX = 'F'), (COUNT(ID) where SEX = 'F')

##Role Access Policy (Column-Level):
Role: DataOperator_3
Accessible Columns: Examination: ALL COLUMNS; Laboratory: ALB, APTT, C3, C4, CENTROMEA, CPK, CRE, DNA, DNA-II, FG, GLU, GOT, GPT, HCT, HGB, ID, IGA, IGM, LDH, PIC, PLT, PT, RBC, RF, RNP, SC170, SM, SSA, SSB, T-BIL, T-CHO, TAT, TG, UN, WBC; Patient: Birthday, Description, Diagnosis, ID, SEX

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: What is the percentage of female patient were born after 1930?
Evidence: female refers to Sex = 'F'; patient who were born after 1930 refers to year(Birthday) > '1930'; calculation = DIVIDE(COUNT(ID) where year(Birthday) > '1930' and SEX = 'F'), (COUNT(ID) where SEX = 'F')
Answer: SELECT CAST(SUM(CASE WHEN STRFTIME('%Y', Birthday) > '1930' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Patient WHERE SEX = 'F'
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT CAST(SUM(CASE WHEN STRFTIME('%Y', Birthday) > '1930' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Patient WHERE SEX = 'F'