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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