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Table 1 Demographics, outcome, comorbidity, and model predictor characteristics of the model development population

From: Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites

  

All Patients

n = 128,941

Training Set

n = 72,437

Testing Set

n = 46,458

 

Demographics a

Measure

Value

    

Age

% (n)

% (n)

% (n)

*

18–29

11.5% (14786)

10.7% (7778)

13.1% (6087)

30–39

17.5% (22607)

18.0% (13053)

18.0% (8361)

40–49

9.45% (12183)

9.49% (6877)

9.69% (4504)

50–59

13.3% (17204)

13.5% (9784)

13.4% (6206)

60–69

18.2% (23500)

18.7% (13556)

17.3% (8026)

70–79

15.8% (20388)

15.8% (11439)

15.1% (7008)

80–89

10.7% (13839)

10.5% (7588)

10.2% (4748)

90+

3.44% (4434)

3.26% (2362)

3.27% (1518)

Ethnicity b

% (n)

% (n)

% (n)

*

Hispanic

9.75% (3467)

9.77% (2336)

8.62% (666)

Not Hispanic

90.3% (32086)

90.2% (21584)

91.4% (7060)

Unknown

-- (93388)

-- (48517)

-- (38732)

 Race

% (n)

% (n)

% (n)

*

Black

10.9% (14033)

11.0% (7933)

10.7% (4987)

East Asian

7.38% (9520)

6.50% (4707)

9.10% (4230)

West Asian

1.66% (2146)

1.68% (1219)

1.74% (807)

White

61.6% (79424)

64.1% (46404)

57.3% (26642)

Other

16.4% (21181)

14.8% (10692)

18.8% (8714)

Unknown

2.05% (2637)

2.05% (1482)

2.32% (1078)

Sex

% (n)

% (n)

% (n)

 

Female

60.1% (77478)

60.3% (43664)

60.5% (28130)

Male

39.9% (51459)

39.7% (28770)

39.4% (18327)

Unknown

0% (4)

0% (3)

0% (1)

Site

% (n)

% (n)

% (n)

*

Tisch

63.4% (81807)

72.3% (52398)

49.2% (22877)

Orthopedic

15.6% (20137)

18.1% (13122)

12.8% (5938)

Brooklyn

20.9% (26997)

9.55% (6917)

38% (17643)

Outcomes c

% (n)

% (n)

% (n)

 

Any known death

7.93% (10229)

9.00% (6521)

5.20% (2414)

*

60-day death

4.15% (5356)

4.05% (2935)

3.57% (1657)

*

  

Median [IQR]

Median [IQR]

Median [IQR]

 

Days from admission to death

53 [6, 205]

83 [12, 306]

21 [1, 92.75]

*

Comorbidities d

Median [IQR]

Median [IQR]

Median [IQR]

 

Charlson Score

1 [0, 2]

1 [0, 2]

0 [0, 2]

*

 

% (n)

% (n)

% (n)

 

AIDS/HIV

0.626% (635)

0.61% (349)

0.506% (176)

 

Cancer (any malignancy)

16.8% (17094)

18.2% (10432)

13.2% (4594)

*

Cerebrovascular disease

10.0% (10149)

9.99% (5716)

8.13% (2826)

*

Chronic obstructive pulmonary disease

17.9% (18218)

18.6% (10649)

13.5% (4703)

*

Congestive heart failure

12.0% (12144)

11.8% (6774)

8.56% (2978)

*

Dementia

3.67% (3721)

3.18% (1819)

3.09% (1075)

 

Diabetes with chronic complications

6.34% (6439)

4.9% (2806)

5.68% (1977)

*

Diabetes without chronic complications

16.8% (17019)

16.2% (9256)

14.4% (4995)

*

Hemiplegia or paraplegia

2.92% (2962)

2.83% (1617)

2.35% (817)

*

Metastatic solid tumor

6.02% (6115)

6.39% (3657)

4.55% (1584)

*

Mild liver disease

6.40% (6495)

6.23% (3566)

5.14% (1787)

*

Moderate or severe liver disease

1.62% (1642)

1.59% (910)

1.11% (385)

*

Myocardial infarction

9.73% (9874)

9.48% (5423)

6.9% (2400)

*

Peptic ulcer disease

1.84% (1871)

1.76% (1009)

1.27% (443)

*

Peripheral vascular disease

13.1% (13278)

13.0% (7446)

9.97% (3469)

*

Renal disease

10.9% (11093)

10.4% (5937)

7.93% (2759)

*

Rheumatoid disease

2.87% (2915)

3.11% (1781)

2.06% (718)

*

Predictors

Range

Measure

Median [IQR]

Median [IQR]

  

1–30 days

# of diagnoses

3 [0, 12]

3 [0, 13]

2 [0, 10]

*

1–30 days

# of lab results

0 [0, 46]

3 [0, 47]

0 [0, 43]

*

1–30 days

# of office visits

3 [1, 6]

3 [1, 6]

2 [1, 5]

*

1–30 days

# of emergency department visits

0 [0, 0]

0 [0, 0]

0 [0, 0]

*

1–30 days

# of hospitalizations

0 [0, 0]

0 [0, 0]

0 [0, 0]

*

1–365 days

# of diagnoses

15 [2, 51]

14 [2, 52]

11 [0, 36]

*

1–365 days

# of lab results

35 [0, 151]

34 [0, 142]

15 [0, 84]

*

1–365 days

# of office visits

11 [5, 25]

11 [5, 25]

9 [4, 20]

*

1–365 days

# of emergency department visits

0 [0, 1]

0 [0, 1]

0 [0, 1]

 

1–365 days

# of hospitalizations

0 [0, 1]

0 [0, 1]

0 [0, 0]

*

  1. *: Differences between training and testing sets are computed with: 1) χ2 tests for demographics; 2) proportion tests for individual comorbidities and mortality rates; and 3) Mann-Whitney tests for Charlson score and days from admission to death. In all cases, statistical significance is indicated (*) for adjusted p < 0.05 using a Bonferroni correction
  2. a: Demographics coded within the EHR at the time of admission
  3. b: Ethnicity contains many missing values which are omitted before computing the proportion and difference between groups
  4. c: Including death and initiation of hospice care
  5. d: Comorbidities are derived from ICD-10 diagnosis codes present in each patient’s year of history pre-admission using the diagnostic groups of the Charlson Comorbidity Index as implemented in the comorbidity R package [24]. Patients with no documented history are omitted from the denominator of each comorbidity