Session Information
Session Type: ACR Poster Session B
Session Time: 9:00AM-11:00AM
Background/Purpose: Down syndrome (Trisomy 21) is known to have higher prevalence of certain conditions including cardiac defects, hypothyroidism, hearing defects and early Alzheimer’s disease, but no studies have looked at the association between Downs syndrome and gout.
Objective: The aim of this study is to estimate the prevalence of gout among Down syndrome patients compared to non-down syndrome patients.
Methods: We reviewed electronic health record (EHR) data over 14 years (1999-2013) from 25,840,730 patients using a third-party cloud-based platform (Explorys, Cleveland OH). 994,793 patients from our institution (The MetroHealth System) were analyzed. International Classification of Disease – 9 (ICD-9) diagnoses codes were used to define Downs syndrome and gout. Prevalence data was compiled among patient diagnoses of Downs syndrome only, gout only, both Downs Syndrome and gout, and neither Downs Syndrome or gout. The odds ratio of a gout diagnosis in a Downs Syndrome patient relative to a non-Downs syndrome patient was calculated
Results: Among the almost 26 million patient cohort, the odds ratio of a gout diagnosis in a patient with Downs sydrome diagnosis compared to a patient without Downs syndrome diagnosis was 3.66 [95% CI 3.32-4.03] and within the MetroHealth system subset, the odds ratio was 4.26 [2.81-6.46].
Conclusion: In the setting of a Downs syndrome patient presenting with articular pain, gout should be higher on the differential diagnoses than in non-Downs syndrome patients. This study also illustrates the potential of aggregated EHR data from tens of millions of patients to create a new paradigm for case series and disease association identification.
Table 1: Metrohealth patients with both DS and gout.
|
Case Series # |
Sex |
Race/Ethnicitya |
BMI (Kg/m2)b |
Age @ 1st Gout Diagnosis |
Encounters w/ Gout ICD-9 |
|
1 |
♂ |
Caucasian |
35.5 |
32 |
46 |
|
2 |
♂ |
Caucasian |
24.6 |
40 |
4 |
|
3 |
♂ |
32.3 |
61 |
2 |
|
|
4 |
♂ |
Caucasian |
20.1 |
30 |
17 |
|
5 |
♂ |
21.1 |
27 |
2 |
|
|
6 |
♂ |
46 |
4 |
||
|
7 |
♂ |
32.3 |
38 |
1 |
|
|
8 |
♂ |
African American |
44.9 |
38 |
12 |
|
9 |
♂ |
Caucasian |
36.2 |
31 |
5 |
|
10 |
♂ |
African American |
45.8 |
32 |
55 |
|
11 |
♂ |
23.0 |
31 |
4 |
|
|
12 |
♂ |
43 |
1 |
||
|
13 |
♂ |
Caucasian |
28.8 |
41 |
1 |
|
14 |
♂ |
32.3 |
52 |
2 |
|
|
15 |
♂ |
Caucasian |
22.2 |
33 |
1 |
|
16 |
♀ |
87 |
1 |
||
|
17 |
♂ |
57 |
1 |
||
|
18 |
♀ |
Caucasian |
38.5 |
41 |
2 |
|
19 |
♀ |
53 |
1 |
||
|
20 |
♀ |
Caucasian |
27.2 |
75 |
10 |
|
21 |
♂ |
African American |
23.4 |
43 |
8 |
|
22 |
♂ |
30.1 |
59 |
1 |
|
|
23 |
♀ |
African American |
37.9 |
52 |
8 |
|
a Demographic and BMIb EHR data was not collected for all patients. |
|||||
Table 2: Odds of simultaneous DS and gout stratifi
|
Attribute |
Stratum |
Cohortsc (N) |
All Cohorts |
DS and Both Populations |
|||
|
Both |
DS |
Gout |
Neither |
ORa(CId) |
ORb (CId) |
||
|
Sex |
Female |
80 |
4,890 |
81,890 |
13,405,820 |
2.68 (2.15-3.34) |
1 (Ref.) |
|
Male |
340 |
5,200 |
191,310 |
11,353,200 |
3.88 -(3.48-4.33) |
4.00 (3.12-5.11) |
|
|
Race/Ethnicity |
Caucasian |
260 |
5,720 |
159,500 |
11,435,490 |
3.26 (2.88-3.69) |
1 (Ref.) |
|
African American |
50 |
1,090 |
45,100 |
2,347,990 |
2.39 (1.80-3.17) |
1.01 (0.74-1.38) |
|
|
Asian |
0 |
200 |
10520 |
542130 |
n/a (n/a) |
n/a (n/a) |
|
|
Hispanic |
0 |
300 |
1820 |
430390 |
n/a (n/a) |
n/a (n/a) |
|
|
Other/Unknown |
30 |
1430 |
26830 |
3177560 |
2.48 (1.73-3.57) |
0.46 (0.31-0.68) |
|
|
BMI |
Normal |
80 |
2,220 |
47,310 |
3,162,740 |
2.41 (1.93-3.01) |
1 (Ref.) |
|
Overweight [25 – 30 Kg/m2] |
110 |
1,830 |
90,570 |
3,024,850 |
2.01 (1.66-2.43) |
1.67 (1.24-2.24) |
|
|
Obesity Class I [30-35 Kg/m2] |
120 |
1,380 |
79,290 |
1,861,410 |
2.04 (1.69-2.46) |
2.41 (1.80-3.23) |
|
|
Obesity Class II [35-40 Kg/m2] |
90 |
830 |
46,920 |
900,010 |
2.08 (1.67-2.59) |
3.01 (2.20-4.11) |
|
|
Obesity Class III [ > 40 Kg/m2] |
70 |
580 |
27,960 |
514,970 |
2.22 (1.73-2.85) |
3.35 (2.40-4.68) |
|
|
Age |
< 25 |
0 |
4920 |
500 |
5259510 |
n/a (n/a) |
n/a (n/a) |
|
25-29 |
20 |
650 |
1,140 |
1,516,400 |
40.93 (26.13-64.11) |
1 (Ref.) |
|
|
30-34 |
30 |
550 |
2,780 |
1,594,390 |
31.28 (21.62-45.26) |
1.77 (1.00-3.16) |
|
|
35-39 |
40 |
520 |
5,080 |
1,486,980 |
22.52 (16.30-31.09) |
2.50 (1.44-4.33) |
|
|
40-44 |
40 |
600 |
8,800 |
1,527,330 |
11.57 (8.40-15.95) |
2.17 (1.25-3.75) |
|
|
45-49 |
80 |
670 |
12,530 |
1,571,560 |
14.98 (11.87-18.90) |
3.88 (2.34-6.41) |
|
|
50-54 |
80 |
800 |
18,010 |
1,745,050 |
9.69 (7.70-12.20) |
3.25 (1.97-5.36) |
|
|
55-59 |
60 |
680 |
24,000 |
1,760,990 |
6.47 (4.97-8.43) |
2.87 (1.71-4.81) |
|
|
60-64 |
40 |
430 |
28,780 |
1,633,450 |
5.28 (3.82-7.30) |
3.02 (1.74-5.24) |
|
|
65-69 |
20 |
170 |
33,110 |
1,494,440 |
5.31 (3.34-8.44) |
3.82 (2.01-7.27) |
|
|
>70 |
0 |
110 |
137920 |
5101390 |
n/a (n/a) |
n/a (n/a) |
|
|
a Odds of a DS patient having a gout diagnose relative to a non-DS patient within a particular stratum. b Odds of a DS patient having a gout diagnoses relative to the reference stratum. c Cohorts do not total all 25,840,730 patients because attribute specific data is available for approximately 96% of patients. d All CI intervals are 95%. |
Refer
To cite this abstract in AMA style:
Igoe A, Roller BA, Elangovan A, Kaelber KL, Kaelber D. A Case Series of Gout and Downs Syndrome – a New Paradigm for Detecting Disease Associations Using Big Data [abstract]. Arthritis Rheumatol. 2017; 69 (suppl 10). https://acrabstracts.org/abstract/a-case-series-of-gout-and-downs-syndrome-a-new-paradigm-for-detecting-disease-associations-using-big-data/. Accessed .« Back to 2017 ACR/ARHP Annual Meeting
ACR Meeting Abstracts - https://acrabstracts.org/abstract/a-case-series-of-gout-and-downs-syndrome-a-new-paradigm-for-detecting-disease-associations-using-big-data/