The Phoenix Sepsis Criteria in Python

Source: vignettes/python.Rmd

Background

It would be helpful to read the first few sections of the Get started article for details on the Phoenix criteria

Python Module

Install

The python module can be installed via

pip install pheonix-sepsis

Importing the module

The needed modules to run the examples are:

import numpy as np
import pandas as pd
import importlib.resources
import phoenix as phx

Example Data Set

The same example data provided in the R package has also been provided in the python module.

path = importlib.resources.files('phoenix')
sepsis = pd.read_csv(path.joinpath('data').joinpath('sepsis.csv'))
print(sepsis.shape)
## (20, 27)
print(sepsis.head())
##    pid     age  fio2  pao2  spo2  ...     anc    alc creatinine  bilirubin    alt
## 0    1    0.06  0.75   NaN  99.0  ...     NaN    NaN       1.03        NaN   36.0
## 1    2  201.70  0.75  75.3  95.0  ...  14.220  2.220       0.51        0.2   32.0
## 2    3   20.80  1.00  49.5   NaN  ...   2.210  0.190       0.33        0.8  182.0
## 3    4  192.50   NaN   NaN   NaN  ...   3.184  0.645       0.31        8.5   21.0
## 4    5  214.40   NaN  38.7  95.0  ...     NaN    NaN       0.52        NaN    NaN
## 
## [5 rows x 27 columns]
Column Name Note
pid patient identification number
age age in months
fio2 fraction of inspired oxygen
pao2 partial pressure of oxygen in arterial blood (mmHg)
spo2 pulse oximetry
vent indicator for invasive mechanical ventilation
gcs_total total Glasgow Coma Scale
pupil character vector reporting if pupils are reactive or fixed.
platelets platelets measured in 1,000 / microliter
inr international normalized ratio
d_dimer D-dimer; units of mg/L FEU
fibrinogen units of mg/dL
dbp diagnostic blood pressure (mmHg)
sbp systolic blood pressure (mmHg)
lactate units of mmol/L
dobutamine indicator for receiving systemic dobutamine
dopamine indicator for receiving systemic dopamine
epinephrine indicator for receiving systemic epinephrine
milrinone indicator for receiving systemic milrinone
norepinephrine indicator for receiving systemic norepinephrine
vasopressin indicator for receiving systemic vasopressin
glucose units of mg/dL
anc units of 1,000 cells per cubic millimeter
alc units of 1,000 cells per cubic millimeter
creatinine units of mg/dL
bilirubin units of mg/dL
alt units of IU/L

Organ Dysfunction Scores

All eight organ dysfunction scoring functions return integer valued numpy arrays.

Respiratory

Scoring for respiratory dysfunction:

Organ System 0 Points 1 Point 2 Points 3 Points
Respiratory (0-3 points)
Any respiratory support IMVa IMV
  PaO2:FiO2 ≥ 400 < 400 < 200 < 100
  SpO2:FiO2b ≥ 292 < 292 < 220 < 148

a IMV: invasive mechanical ventilation; PaO2: arterial oxygen pressure; SpO2: pulse oximetry oxygen saturation;

bSpO2:FiO2 is only valid when SpO2 ≤ 97.

py_resp = phx.phoenix_respiratory(
    pf_ratio = sepsis["pao2"] / sepsis["fio2"],
    sf_ratio = np.where(sepsis["spo2"] <= 97, sepsis["spo2"] / sepsis["fio2"], np.nan),
    imv      = sepsis["vent"],
    other_respiratory_support = (sepsis["fio2"] > 0.21).astype(int).to_numpy()
)
print(type(py_resp))
## <class 'numpy.ndarray'>
print(py_resp)
## [0 3 3 0 0 3 3 0 3 3 3 1 0 2 3 0 2 3 2 0]

Cardiovascular

Organ System 0 Points 1 Point 2 Points 3 Points
Cardiovascular (0-6 points; sum of medications, Lactate, and MAP)
   Systemic Vasoactive Medicationsc No medications 1 medication 2 or more medications
   Lactated (mmol/L) < 5 5 ⋚ Lactate < 11 ≥ 11
   Agee (months) adjusted MAPf (mmHg)
     0 ≤ Age < 1 ≥ 31 17 ≤ MAP < 31 < 17
     1 ≤ Age < 12 ≥ 39 25 ≤ MAP < 39 < 25
     12 ≤ Age < 24 ≥ 44 31 ≤ MAP < 44 < 31
     24 ≤ Age < 60 ≥ 45 32 ≤ MAP < 45 < 32
     60 ≤ Age < 144 ≥ 49 36 ≤ MAP < 49 < 36
     144 ≤ Age < 216 ≥ 52 38 ≤ MAP < 52 < 38

dLactate can be arterial or venous. Reference range 0.5 - 2.2 mmol/L eAge: measured in months and is not adjusted for prematurity. fMAP - Use measured mean arterial pressure preferentially (invasive arterial if available, or non-invasive oscillometric), alternatively use the calculation diastolic + (systolic - diastolic) / 3

As with the R package, the Python module has a function map to simplify the estimation of mean arterial pressure based on systolic and diagnostic pressures. MAP is approximated as (2/3)DBP + (1/3)SBP.

py_card = phx.phoenix_cardiovascular(
    vasoactives = sepsis["dobutamine"] + sepsis["dopamine"] + sepsis["epinephrine"] +
                  sepsis["milrinone"] + sepsis["norepinephrine"] + sepsis["vasopressin"],
    lactate = sepsis["lactate"],
    age = sepsis["age"],
    map = phx.map(sepsis["sbp"], sepsis["dbp"])
)
print(type(py_card))
## <class 'numpy.ndarray'>
print(py_card)
## [2 2 1 0 0 1 4 0 3 0 3 0 0 2 3 2 2 2 2 1]

Coagulation

Organ System 0 Points 1 Point 2 Points 3 Points
Coagulationg (0-2 points; 1 for each lab; max of 2 points)
   Platelets (1000/μL) ≥ 100 < 100
   INR ≤ 1.3 > 1.3
   D-Dimer (mg/L FEU) ≤ 2 > 2
   Fibrinogen (mg/dL) ≥ 100 < 100

FEU: fibrinogen equivalent units; INR: International normalized ratio;

gCoagulation variable reference ranges: platelets, 150-450 103/μL; D-dimer, < 0.5 mg/L FEU; fibrinogen, 180-410 mg/dL. International normalized ratio reference range is based on local reference prothrombin time.

py_coag = phx.phoenix_coagulation(
    platelets = sepsis['platelets'],
    inr = sepsis['inr'],
    d_dimer = sepsis['d_dimer'],
    fibrinogen = sepsis['fibrinogen']
)
print(type(py_coag))
## <class 'numpy.ndarray'>
print(py_coag)
## [1 1 2 1 0 2 2 1 1 0 1 0 0 1 2 1 1 2 0 1]

Neurologic

Organ System 0 Points 1 Point 2 Points 3 Points
Neurologich (0-2 points)
   GCSi ≥ 11 GCS ≤ 10 Bilaterally fixed pupils

FEU: fibrinogen equivalent units; INR: International normalized ratio;

hNeurologic dysfunction scoring was pragmatically validated in both sedated and on sedated patients and those with and without IMV. iGCS measures level of consciousness based on verbal, eye, and motor response. Values are integers from 3 to 15 with higher scores indicating better neurologic function.

py_neur = phx.phoenix_neurologic(
    gcs = sepsis["gcs_total"],
    fixed_pupils = (sepsis["pupil"] == "both-fixed").astype(int)
)
print(type(py_neur))
## <class 'numpy.ndarray'>
print(py_neur)
## [0 1 0 0 0 1 0 0 1 1 2 0 0 0 0 0 0 0 0 0]

Endocrine

Organ System 0 Points 1 Point 2 Points 3 Points
Endocrine (0-1 point)
   Blood Glucose (mg/dL) 50 ≤ Blood Glucose ≤ 150 < 50; or > 150 
py_endo = phx.phoenix_endocrine(sepsis["glucose"])
print(type(py_endo))
## <class 'numpy.ndarray'>
print(py_endo)
## [0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1]

Immunologic

Organ System 0 Points 1 Point 2 Points 3 Points
Immunologic (0-1 point; point from ANC and/or ALC)
   ANC (cells/mm3) ≥ 500 < 500
   ALC (cells/mm3) ≥ 1000 < 1000

ALC: Absolute lymphocyte count; ANC: Absolute neutrophil count;

py_immu = phx.phoenix_immunologic(sepsis["anc"], sepsis["alc"])
print(type(py_immu))
## <class 'numpy.ndarray'>
print(py_immu)
## [0 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 1 0 1 1]

Renal

Organ System 0 Points 1 Point 2 Points 3 Points
Renal (0-1 point)
   Agee (months) adjusted Creatinine (mg/dL)
     0 ≤ Age < 1 < 0.8 ≥ 0.8
     1 ≤ Age < 12 < 0.3 ≥ 0.3
     12 ≤ Age < 24 < 0.4 ≥ 0.4
     24 ≤ Age < 60 < 0.6 ≥ 0.6
     60 ≤ Age < 144 < 0.7 ≥ 0.7
     144 ≤ Age < 216 < 1.0 ≥ 1.0 
py_renal = phx.phoenix_renal(sepsis["creatinine"], sepsis["age"])
print(type(py_renal))
## <class 'numpy.ndarray'>
print(py_renal)
## [1 0 0 0 0 1 1 0 1 0 1 0 0 0 1 0 0 1 1 0]

Hepatic

Organ System 0 Points 1 Point 2 Points 3 Points
Hepatic (0-1 point; point from total bilirubin and/or ALT)
   Total Bilirubin (mg/dL) < 4 ≥ 4
   ALT (IU/L) ≤ 102 > 102

ALT: alanine aminotransferase;

py_hepatic = phx.phoenix_hepatic(sepsis["bilirubin"], sepsis["alt"])
print(type(py_hepatic))
## <class 'numpy.ndarray'>
print(py_hepatic)
## [0 0 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 0]

Phoenix

The Phoenix score is the sum of the 1. respiratory, 2. cardiovascular, 3. coagulation, and 4. neurologic organ dysfunction scores.

Sepsis is the condition of having a suspected (or confirmed) infection with two or more Phoenix points.

Septic Shock is defined as sepsis with at least one cardiovascular point.

py_phoenix_scores = phx.phoenix(
    pf_ratio = sepsis["pao2"] / sepsis["fio2"],
    sf_ratio = np.where(sepsis["spo2"] <= 97, sepsis["spo2"] / sepsis["fio2"], np.nan),
    imv      = sepsis["vent"],
    other_respiratory_support = (sepsis["fio2"] > 0.21).astype(int).to_numpy(),
    vasoactives = sepsis["dobutamine"] + sepsis["dopamine"] + sepsis["epinephrine"] + sepsis["milrinone"] + sepsis["norepinephrine"] + sepsis["vasopressin"],
    lactate = sepsis["lactate"],
    age = sepsis["age"],
    map = phx.map(sepsis["sbp"], sepsis["dbp"]),
    platelets = sepsis['platelets'],
    inr = sepsis['inr'],
    d_dimer = sepsis['d_dimer'],
    fibrinogen = sepsis['fibrinogen'],
    gcs = sepsis["gcs_total"],
    fixed_pupils = (sepsis["pupil"] == "both-fixed").astype(int),
    )
print(py_phoenix_scores.info())
## <class 'pandas.core.frame.DataFrame'>
## RangeIndex: 20 entries, 0 to 19
## Data columns (total 7 columns):
##  #   Column                        Non-Null Count  Dtype
## ---  ------                        --------------  -----
##  0   phoenix_respiratory_score     20 non-null     int64
##  1   phoenix_cardiovascular_score  20 non-null     int64
##  2   phoenix_coagulation_score     20 non-null     int64
##  3   phoenix_neurologic_score      20 non-null     int64
##  4   phoenix_sepsis_score          20 non-null     int64
##  5   phoenix_sepsis                20 non-null     int64
##  6   phoenix_septic_shock          20 non-null     int64
## dtypes: int64(7)
## memory usage: 1.2 KB
## None
print(py_phoenix_scores.head())
##    phoenix_respiratory_score  ...  phoenix_septic_shock
## 0                          0  ...                     1
## 1                          3  ...                     1
## 2                          3  ...                     1
## 3                          0  ...                     0
## 4                          0  ...                     0
## 
## [5 rows x 7 columns]

Phoenix-8

The Phoenix-8 score is the sum of the Phoenix score along with points form the other four organ systems: 5. endocrine, 6. immunologic, 7. renal, and 8. hepatic.

py_phoenix8_scores = phx.phoenix8(
    pf_ratio = sepsis["pao2"] / sepsis["fio2"],
    sf_ratio = np.where(sepsis["spo2"] <= 97, sepsis["spo2"] / sepsis["fio2"], np.nan),
    imv      = sepsis["vent"],
    other_respiratory_support = (sepsis["fio2"] > 0.21).astype(int).to_numpy(),
    vasoactives = sepsis["dobutamine"] + sepsis["dopamine"] + sepsis["epinephrine"] + sepsis["milrinone"] + sepsis["norepinephrine"] + sepsis["vasopressin"],
    lactate = sepsis["lactate"],
    map = phx.map(sepsis["sbp"], sepsis["dbp"]),
    platelets = sepsis['platelets'],
    inr = sepsis['inr'],
    d_dimer = sepsis['d_dimer'],
    fibrinogen = sepsis['fibrinogen'],
    gcs = sepsis["gcs_total"],
    fixed_pupils = (sepsis["pupil"] == "both-fixed").astype(int),
    glucose = sepsis["glucose"],
    anc = sepsis["anc"],
    alc = sepsis["alc"],
    creatinine = sepsis["creatinine"],
    bilirubin = sepsis["bilirubin"],
    alt = sepsis["alt"],
    age = sepsis["age"]
    )
print(py_phoenix8_scores.info())
## <class 'pandas.core.frame.DataFrame'>
## RangeIndex: 20 entries, 0 to 19
## Data columns (total 12 columns):
##  #   Column                        Non-Null Count  Dtype
## ---  ------                        --------------  -----
##  0   phoenix_respiratory_score     20 non-null     int64
##  1   phoenix_cardiovascular_score  20 non-null     int64
##  2   phoenix_coagulation_score     20 non-null     int64
##  3   phoenix_neurologic_score      20 non-null     int64
##  4   phoenix_sepsis_score          20 non-null     int64
##  5   phoenix_sepsis                20 non-null     int64
##  6   phoenix_septic_shock          20 non-null     int64
##  7   phoenix_endocrine_score       20 non-null     int64
##  8   phoenix_immunologic_score     20 non-null     int64
##  9   phoenix_renal_score           20 non-null     int64
##  10  phoenix_hepatic_score         20 non-null     int64
##  11  phoenix8_score                20 non-null     int64
## dtypes: int64(12)
## memory usage: 2.0 KB
## None
print(py_phoenix8_scores.head())
##    phoenix_respiratory_score  ...  phoenix8_score
## 0                          0  ...               4
## 1                          3  ...               8
## 2                          3  ...               8
## 3                          0  ...               3
## 4                          0  ...               0
## 
## [5 rows x 12 columns]