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Performance of Recommended Screening Tests for Undiagnosed Diabetes and Dysglycemia

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To evaluate the performance, in settings typical of opportunistic and community screening programs, of screening tests currently recommended by the American Diabetes Association (ADA) for detecting undiagnosed diabetes. Volunteers aged > or =20 years without previously diagnosed diabetes (n = 1,471) completed a brief questionnaire and underwent recording of postprandial time and measurement of capillary blood glucose (CBG) with a portable sensor. Participants subsequently underwent a 75-g oral glucose tolerance test; fasting serum glucose (FSG) and 2-h postload serum glucose (2-h SG) concentrations were measured. The screening tests we studied included the ADA risk assessment questionnaire, the recommended CBG cut point of 140 mg/dl, and an alternative CBG cut point of 120 mg/dl. Each screening test was evaluated against several diagnostic criteria for diabetes (FSG > or =126 mg/dl, 2-h SG > or =200 mg/dl, or either) and dysglycemia (FSG > or =110 mg/dl, 2-h SG > or =140 mg/dl, or either). Among all participants, 10.7% had undiagnosed diabetes (FSG > or =126 or 2-h SG > or =200 mg/dl), 52.1% had a positive result on the questionnaire, 9.5% had CBG > or =140 mg/dl, and 18.4% had CBG > or =120 mg/dl. The questionnaire was 72-78% sensitive and 50-51% specific for the three diabetes diagnostic criteria; CBG > or =140 mg/dl was 56-65% sensitive and 95-96% specific, and CBG > or =120 mg/dl was 75-84% sensitive and 86-90% specific. CBG > or =120 mg/dl was 44-62% sensitive and 89-90% specific for dysglycemia. Low specificity may limit the usefulness of the ADA questionnaire. Lowering the cut point for a casual CBG test (e.g., to 120 mg/dl) may improve sensitivity and still provide adequate specificity.
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Performance of Recommended Screening
Tests for Undiagnosed Diabetes and
Dysglycemia
DEBORAH B. ROLKA,
MS
1
K. M. VENKAT NARAYAN,
MD
1
THEODORE J. THOMPSON,
MS
1
DONA GOLDMAN,
BSN
,
MPH
2
JOANN LINDENMAYER,
DVM
,
MPH
2
KATE ALICH,
MS, RD
3
DARCY BACALL,
RN
,
CDE
3
EVAN M. BENJAMIN,
MD
4
BETTY LAMB,
RN
,
MSN
1
DENNIS O. STUART,
MD
5
MICHAEL M. ENGELGAU,
MD
1
OBJECTIVE To evaluate the performance, in settings typical of opportunistic and com-
munity screening programs, of screening tests currently recommended by the American Diabetes
Association (ADA) for detecting undiagnosed diabetes.
RESEARCH DESIGN AND METHODS Volunteers aged 20 years without previ-
ously diagnosed diabetes (n 1,471) completed a brief questionnaire and underwent recording
of postprandial time and measurement of capillary blood glucose (CBG) with a portable sensor.
Participants subsequently underwent a 75-g oral glucose tolerance test; fasting serum glucose
(FSG) and 2-h postload serum glucose (2-h SG) concentrations were measured. The screening
tests we studied included the ADA risk assessment questionnaire, the recommended CBG cut
point of 140 mg/dl, and an alternative CBG cut point of 120 mg/dl. Each screening test was
evaluated against several diagnostic criteria for diabetes (FSG 126 mg/dl, 2-h SG 200 mg/dl,
or either) and dysglycemia (FSG 110 mg/dl, 2-h SG 140 mg/dl, or either).
RESULTS Among all participants, 10.7% had undiagnosed diabetes (FSG 126 or 2-h SG
200 mg/dl), 52.1% had a positive result on the questionnaire, 9.5% had CBG 140 mg/dl, and
18.4% had CBG 120 mg/dl. The questionnaire was 72–78% sensitive and 50 –51% specific for
the three diabetes diagnostic criteria; CBG 140 mg/dl was 56 65% sensitive and 95–96%
specific, and CBG 120 mg/dl was 75–84% sensitive and 86–90% specific. CBG 120 mg/dl
was 44 62% sensitive and 89–90% specific for dysglycemia.
CONCLUSIONS Low specificity may limit the usefulness of the ADA questionnaire.
Lowering the cut point for a casual CBG test (e.g., to 120 mg/dl) may improve sensitivity and still
provide adequate specificity.
Diabetes Care 24:1899 –1903, 2001
S
creening for undiagnosed diabetes
has been favored by some (1– 4) but
discouraged by others (5,6). A com-
prehensive review (7) found indirect evi-
dence supporting an opportunistic
screening approach (i.e., screening sub-
jects visiting a health care provider for
reasons unrelated to diabetes) but noted
that currently recommended screening
strategies have not been fully evaluated.
Understanding the performance of
screening strategies will also be important
if the interventions of the ongoing Diabe-
tes Prevention Program (8) are found to
be effective in reducing the onset of dia-
betes in subjects with impaired glucose
tolerance.
We evaluated the performance, in set-
tings typical of opportunistic and com-
munity screening programs, of several
screening strategies for type 2 diabetes
that are currently recommended by the
American Diabetes Association (ADA)
(4). The screening tests we evaluated in-
cluded the ADA risk assessment question-
naire and tests based on casual capillary
blood glucose (CBG) measures. The diag-
nostic criteria for this study were diabetes,
impaired fasting glucose (IFG), and im-
paired glucose tolerance (IGT), as deter-
mined by fasting serum glucose (FSG) or
2-h postload serum glucose (2-h SG) con-
centrations measured as part of a single
75-g oral glucose tolerance test (OGTT).
RESEARCH DESIGN AND
METHODS Between September
1995 and July 1998, 1,471 volunteers
aged 20 years were recruited by health
care systems serving communities in
Springfield, MA; Robeson County, NC;
and Providence, Pawtucket, and Central
Falls, RI. Participants were recruited dur-
ing routine health center visits and at
community health fairs. Informed con-
sent was obtained from all participants,
and the study protocol was approved by
the institutional review boards at the Cen-
ters for Disease Control and Prevention
and each of the study sites. Persons who
had self-reported previously diagnosed
diabetes, had been pregnant or breast-
feeding within the previous 3 months, or
had been hospitalized within the previous
6 months were not eligible to participate
in the study.
Screening tests were administered at
recruitment. Eligible participants com-
pleted a 14-item questionnaire that in-
cluded the 7 items needed to score the
ADA questionnaire test (Table 1). A por-
table sensor (Accu Chek Advantage;
Roche Diagnostics, Indianapolis, IN) was
used to obtain a whole-blood glucose
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
From the
1
Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia; the
2
Rhode Island Department of Health, Providence, Rhode Island; the
3
Massachusetts Department of Public
Health, Boston, Massachusetts; the
4
Baystate Medical Center, Springfield, Massachusetts; and the
5
Robeson
Health Care Corporation, Fairmont, North Carolina.
Address correspondence and reprint requests to Deborah B. Rolka, Mailstop K-10, 4770 Buford Highway
NE, Atlanta, GA 30341. E-mail: drolka@cdc.gov.
Received for publication 6 March 2001 and accepted in revised form 26 July 2001.
Abbreviations: 2-h SG, 2-h postload serum glucose; ADA, American Diabetes Association; CBG, capillary
blood glucose; FSG, fasting serum glucose; IFG, impaired fasting glucose; IGT, impaired glucose tolerance;
OGTT, oral glucose tolerance test; WHO, World Health Organization.
A table elsewhere in this issue shows conventional and Syste`me International (SI) units and conversion
factors for many substances.
Epidemiology/Health Services/Psychosocial Research
ORIGINAL ARTICLE
DIABETES CARE, VOLUME 24, NUMBER 11, NOVEMBER 2001 1899
level from a capillary (nger stick) sample
from each eligible participant, and time
since ingestion of any food or drink ex-
cept water (postprandial time) was re-
corded.
Participants were scheduled to return
for a 75-g OGTT on a subsequent morn-
ing (usually within 7 days) after fasting
overnight for 10 h. During this visit,
fasting and 2-h postload venous blood
specimens were collected and FSG and
2-h SG concentrations were analyzed in a
clinical laboratory using glucose oxidase
methodology.
We computed the sensitivity (i.e.,
proportion of participants with a positive
test, among those who satised the crite-
rion) and specicity (i.e., proportion of
participants with a negative test, among
those who did not satisfy the criterion) of
four screening tests for six diagnostic cri-
teria.
To investigate how covariates may ef-
fect performance characteristics and the
choice of appropriate cut points for the
CBG, we t multiple regression models
relating CBG to diabetes (FSG 126 mg/
dl), age (45 or 45 years), postprandial
time (8or8 h), sex, and race/ethnicity
(Hispanic, non-Hispanic white, or Afri-
can-American). We also computed the
sensitivity and specicity of the four
screening tests for FSG 126 mg/dl sep-
arately by sex and race/ethnicity.
CBG measurements were valid in all
but 3 of the 1,471 eligible participants,
but postprandial time was not recorded
for 44 participants (3.0%). FSG values
were not recorded for 380 participants
(26%), and 2-h SG values were not re-
corded for 403 participants (27%). To re-
duce the potential for bias, we applied the
standard statistical technique of multiple
imputation (9). Every estimate we report
is the arithmetic mean of estimates ob-
tained from 10 imputed data sets. We
used the software program NORM (10) to
impute missing values and we used SAS
software (SAS Institute, Cary, NC) (11) to
analyze the data and combine the esti-
mates.
RESULTS Participants included
Hispanics (58%), non-Hispanic whites
(19%), African-Americans (12%), Native
Americans (4%), and others (7%). The
mean age of the participants was 44 years
(20 44 years, 43%; 45 64 years, 25%;
6589 years, 32%), and 70% of the par-
ticipants were women. A total of 34% of
the participants had a parent with diabe-
tes, and 17% had a sibling with diabetes;
67% of the participants reported little or
no physical activity in most weeks, and
51% of participants had BMI 27 kg/m
2
.
A total of 52% of all participants had a
positive score (10 points) on the ADA
questionnaire; 9.5% had CBG 140 mg/
dl, and 18.4% had CBG 120 mg/dl.
Fasting and 2-h diagnostic criteria for di-
abetes, impaired glucose, and normogly-
cemia resulted in somewhat different
classications of participants (Table 2).
We estimated that 157 subjects (10.7%)
had undiagnosed diabetes, according to
one or both of the two criteria, and that an
additional 221 (15.0%) had impaired glu-
cose (IFG or IGT) without satisfying ei-
ther of the criteria for diabetes.
The ADA questionnaire was moder-
ately sensitive (69 78%) for all diagnostic
criteria for diabetes and dysglycemia;
however, its specicity did not exceed
54% (Table 3). The cut point of 140 mg/dl
for CBG was quite specic (9597%) for
all of the diagnostic criteria but only 56
65% sensitive for diabetes and 28 41%
sensitive for dysglycemia.
Empirical receiver operating charac-
teristic curves suggest that a CBG cut
point of 120 mg/dl may yield a good bal-
ance of sensitivity and specicity (Fig. 1).
Indeed, this test was 75 84% sensitive for
diabetes, 44 62% sensitive for dysglyce-
mia, and 8690% specic for all of the
diagnostic criteria.
The ADA recommends that, in com-
munity screening programs, glycemic
testing should be performed only after ad-
ministration of a risk assessment ques-
tionnaire (4). This combination (a
positive ADA questionnaire and CBG
120 mg/dl) was less sensitive and more
specic than either the questionnaire or
CBG 120 mg/dl alone (Table 3). The
ADA also recommends using a capillary
blood glucose cut point of 110 mg/dl (in-
stead of 140 mg/dl) for subjects who have
fasted for 8 h (4). Among study partic-
ipants who had not eaten for 8 h (37%
of all participants), CBG 110 mg/dl was
8295% sensitive and 86 89% specic
for diabetes and 51 80% sensitive and
8994% specic for dysglycemia.
The ADA questionnaire was less sen-
sitive (65 vs. 77%) and more specic (56
vs. 47%) for diabetes (FSG 126 mg/dl)
in men than in women. The CBG tests
were more sensitive and less specic
among men than in women. CBG 140
mg/dl was 81% sensitive and 95% specic
in men and 56% sensitive and 96% spe-
cic in women. CBG 120 mg/dl was
90% sensitive and 86% specicinmen
and 80% sensitive and 88% specicin
women.
We derived estimated receiver oper-
ating characteristic curves from a linear
regression in which the natural log of
CBG was modeled as a function of dia-
betes (FSG 126 mg/dl), age, postpran-
dial time, and sex. We assumed normally
Table 1Scoring the questionnaire test
Item Points
1. Woman who delivered a
macrosomic (9 lb) infant
1
2. One or more siblings with
diabetes
1
3. One or more parents with
diabetes
1
4. BMI 27 kg/m
2
5
5. Age 65 years and little
or no physical activity in
most weeks
5
6. Age 4564 years 5
7. Age 65 years 9
Subjects with a total of 10 points were considered
to have had a positive result of the screening test.
Table 2Classification of participants by OGTT results
ISG
2-h SG
140 mg/dl
(normoglycemia)
140199 mg/dl
(IGT)
200 mg/dl
(diabetes) Total
110 mg/dl (normoglycemia) 1,093 (74.3) 124 (8.4) 17 (1.2) 1,234 (83.9)
110125 mg/dl (IFG) 63 (4.3) 34 (2.3) 15 (1.0) 112 (7.6)
126 mg/dl (diabetes) 20 (1.3) 27 (1.9) 78 (5.3) 125 (8.5)
Total 1,176 (79.9) 185 (12.6) 110 (7.5) 1,471 (100)
Data are means (% of total) from 10 imputed data sets. A total of 3% of participants had missing FSG values,
and 27% had missing 2-h SG values.
Performance of diabetes screening tests
1900 DIABETES CARE, VOLUME 24, NUMBER 11, NOVEMBER 2001
Figure 1—Empirical receiver operating characteristic curves. Sensitivity vs. 1-specificity of CBG is plotted over a range of CBG cut points for
diabetes (top row) and dysglycemia (bottom row). Diagnostic criteria are FSG 126 mg/dl (A), 2-h SG 200 mg/dl (B), FSG 126 mg/dl or 2-h
SG 200 mg/dl (C), FSG 110 mg/dl (D), 2-h SG 140 mg/dl (E), FSG 110 mg/dl or 2-h SG 140 mg/dl (F).
Table 3Sensitivity and specicity of four screening tests for six diabetes and dysglycemia criteria
ADA Questionnaire CBG 140 mg/dl CBG 120 mg/dl
ADA questionnaire and
CBG 120 mg/dl
Sensitivity Specicity Sensitivity Specicity Sensitivity Specicity Sensitivity Specicity
Diabetes criterion:
FSG 126 mg/dl 72 (6975) 50 (4950) 65 (6368) 96 (9596) 84 (7889) 88 (8788) 63 (5868) 93 (9293)
2-h SG 200 mg/dl 78 (7384) 50 (5051) 62 (5568) 95 (9495) 78 (7284) 86 (8687) 60 (5467) 92 (9193)
FSG 126 mg/dl or 2-h
SG 200 mg/dl
75 (7279) 51 (5051) 56 (5359) 96 (9696) 75 (7080) 88 (8889) 58 (5462) 94 (9394)
Dysglycemia criterion:
FSG 110 mg/dl 69 (6672) 51 (5052) 41 (3943) 97 (9697) 62 (5766) 90 (8991) 45 (4248) 95 (9495)
2-h SG 140 mg/dl 72 (6975) 53 (5254) 33 (3135) 96 (9697) 48 (4550) 89 (8890) 36 (3439) 94 (9495)
FSG 110 mg/dl or 2-h
SG 140 mg/dl
69 (6771) 54 (5355) 28 (2729) 97 (9797) 44 (4147) 90 (9091) 32 (3034) 95 (9596)
Data are % (95% CI). The 95% CIs account only for the uncertainty due to missing data and are computed as (mean point estimate) [(t
.975, 9
) (1 1/10)
1/2
(SD of 10 point estimates)].
Rolka and Associates
DIABETES CARE, VOLUME 24, NUMBER 11, NOVEMBER 2001 1901
distributed errors and heterogeneous
variances (varying by diabetes and post-
prandial time). Cut points for the CBG
test that were optimal (maximizing the
sum of sensitivity and specicity) tended
to be lower for younger subjects and those
with longer postprandial times and higher
for men. CBG performed somewhat bet-
ter (larger areas under the curves) for men
than for women and for subjects with
postprandial time 8 h than for those
with postprandial time 8 h (Fig. 2).
The sensitivities and specicities of
the four screening tests varied little by
race or ethnicity, and we did not nd sub-
stantial racial or ethnic differences in the
performance of CBG for diabetes (FSG
126 mg/dl) after controlling for age,
postprandial time, and sex.
CONCLUSIONS This is the rst
comprehensive evaluation of screening
tests that use a questionnaire or casual
CBG measure to detect undiagnosed dia-
betes or dysglycemia in patient popula-
tions and settings typical of current U.S.
screening initiatives. Using several diag-
nostic criteria for diabetes and dysglyce-
mia, we found that the ADA questionnaire
favored sensitivity, whereas CBG 140
mg/dl (the recommended cut point) fa-
vored specicity.
The ADA questionnaire was devel-
oped from the Second U.S. National
Health and Nutritional Examination Sur-
vey using a binary classication algorithm
(12). The ADA questionnaire yielded
lower specicity in our study than it did
in previous evaluations. In the current
study, the questionnaire was 78% sensi-
tive and 50% specic for the World
Health Organization (WHO) diabetes cri-
terion (2-h SG 200 mg/dl) (13). Sensi-
tivity for this WHO criterion was 79%,
and specicity was 65% in the initial eval-
uation of the ADA questionnaire (12). In
an evaluation that was conducted using
the Netherlands Hoorn Study popula-
tion, sensitivity was 72% and specicity
was 56% (14).
CBG screening tests for diabetes have
been suggested because they use current
self-monitoring technology and require
minimal technical skill and laboratory
support compared with more laboratory-
based tests (e.g., serum glucose or HbA
1c
).
Previous evaluations of CBG screening
tests have reported sensitivities of 50
70% at 90% specicity (15,16). In our
study, CBG was 70% sensitive for the
WHO diabetes criterion (13) at 90% spec-
icity.
The performance of CBG tests may
depend on postprandial time and other
factors such as age or sex (7,15,17). Con-
sistent with a previous study (15), we
found that optimal CBG cut points may
be lower for younger subjects and those
with longer (8 h) postprandial times. In
contrast with that study, in which the best
performance was observed among those
with the shortest postprandial times (15),
we found that CBG performed somewhat
better in individuals with longer post-
prandial times than in those with post-
prandial times 8 h. In our study, we also
observed better performance and slightly
higher optimal cut points in men than in
women.
Diabetes screening tests have been
evaluated in homogeneous populations
(15,1822) but rarely in racially hetero-
geneous populations. We were able to ex-
amine the potential effects of race or
ethnicity and found that the performance
characteristics of the ADA questionnaire
and the CBG measure did not vary sub-
stantially by race or ethnicity.
Detection of IFG or IGT is not a goal
of most current diabetes screening efforts.
This may change, however, if the lifestyle
and/or medication interventions of the
Diabetes Prevention Program (8) are
shown to be effective. We included diag-
nostic criteria for dysglycemia (i.e., diabe-
tes and IFG or IGT) and examined the
performance of current diabetes screen-
ing tests when applied to these broader
diagnostic criteria. Our data suggest that
CBG measures do not discriminate dys-
glycemia from normoglycemia as well as
they discriminate subjects with diabetes
from those without diabetes.
Our study has some limitations. Be-
cause our volunteers and participating
clinics were not probability samples, we
do not make formal statistical inference
beyond the study population. We believe
that the participation of subjects from ur-
ban and rural areas in three states yielded
a study population reecting the hetero-
geneity of U.S. populations. However, be-
cause it would be inappropriate to use this
study population to develop new screen-
ing tests and strategies, we focused our
evaluation on existing screening tests.
Missing data may have biased our esti-
mates for the study population; we at-
tempted to minimize this bias through the
use of multiple imputation. Also, clinical
diagnosis requires repeat testing, and the
diagnostic criteria that we dened are
based on a single OGTT. Therefore, our
sensitivities and specicities were esti-
mated relative to imperfect criteria.
Our estimates can be used to help
project resource needs and expected
yields. For example, suppose that a pro-
gram plans to use a casual CBG test to
screen a population of 5,000 individuals
for diabetes (FSG 126 mg/dl). We esti-
mated that the screening test CBG 120
mg/dl is 84% sensitive and 88% specic.
If the population prevalence of diabetes is
assumed to be 8%, then screening with
CBG 120 mg/dl can be projected to
Figure 2Estimated receiver operating characteristic curves by age, sex, and postprandial time.
Sensitivity and specicity of CBG for the diabetes criterion of FSG 126 mg/dl were estimated
using the multiple regression model described in the text, in which the natural log of CBG is
modeled as a function of diabetes, age, postprandial time, sex, and diabetes sex.
Performance of diabetes screening tests
1902 DIABETES CARE, VOLUME 24, NUMBER 11, NOVEMBER 2001
yield 8% 84% 5,000 336 true
positives (new cases), 92% 12%
5,000 552 false positives, and 8%
16% 5,000 64 false negatives
(missed cases). The projected positive pre-
dictive value (proportion of actual cases
among those who have positive tests)
would be 336 (336 552) 29.8%.
The U.S. Preventive Services Task
Force has voiced concern about the lack
of a practical screening test that is both
sensitive and specic (5). We found that
the usefulness of the ADA questionnaire
as a screening test may indeed be limit-
ed by its low specicity. The casual CBG
measure offers better performance and
the exibility to select threshold cut points
that balance sensitivity and specicity
with the available resources; lowering the
cut point (e.g., to 120 mg/dl) may im-
prove sensitivity and still provide ade-
quate specicity.
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Rolka and Associates
DIABETES CARE, VOLUME 24, NUMBER 11, NOVEMBER 2001 1903
... 6 Prediabetes is not clearly defined by RBG despite several studies that have attempted to define cut-off values of RBG against HbA1c. [6][7][8][9][10][11][12][13][14][15] More convenient point-of-care (POC) HbA1c kits are now available that show good correlation with laboratory-based HbA1c estimation. 16 It is, therefore, appropriate to validate POC HbA1c against RBG in community screening. ...
... Studies using POC HbA1c as a reference test have included specific disease cohorts only, or had a small sample size within hospital settings or conducted post-hoc analysis on previously recruited study cohorts and most importantly, did not compare the accuracy of these tests with known non-laboratory (NL) based diabetes risk scores. [6][7][8][9][10][11][12][13][14][15] Due to the large numbers of undiagnosed diabetes, it is also useful to investigate whether it is more efficient to triage people at risk of diabetes in the population using non-invasive diabetes risk scores, such as Madras Diabetes Research Foundation-Indian Diabetes Risk Score (MDRF-IDRS) 18 to further reduce the cost of screening with POC HbA1c or RBG. ...
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Introduction The aim of this study is to develop practical and affordable models to (a) diagnose people with diabetes and prediabetes and (b) identify those at risk of diabetes complications so that these models can be applied to the population in low-income and middle-income countries (LMIC) where laboratory tests are unaffordable. Methods and analysis This statistical and economic modelling study will be done on at least 48 000 prospectively recruited participants aged 40 years or above through community screening across 20 predefined regions in India. Each participant will be tested for capillary random blood glucose (RBG) and complete a detailed health-related questionnaire. People with known diabetes and all participants with predefined levels of RBG will undergo further tests, including point-of-care (POC) glycated haemoglobin (HbA1c), POC lipid profile and POC urine test for microalbuminuria, retinal photography using non-mydriatic hand-held retinal camera, visual acuity assessment in both eyes and complete quality of life questionnaires. The primary aim of the study is to develop a model and assess its diagnostic performance to predict HbA1c diagnosed diabetes from simple tests that can be applied in resource-limited settings; secondary outcomes include RBG cut-off for definition of prediabetes, diagnostic accuracy of cost-effective risk stratification models for diabetic retinopathy and models for identifying those at risk of complications of diabetes. Diagnostic accuracy inter-tests agreement, statistical and economic modelling will be performed, accounting for clustering effects. Ethics and dissemination The Indian Council of Medical Research/Health Ministry Screening Committee (HMSC/2018–0494 dated 17 December 2018 and institutional ethics committees of all the participating institutions approved the study. Results will be published in peer-reviewed journals and will be presented at national and international conferences. Trial registration number ISRCTN57962668 V1.0 24/09/2018.
... 6,7 Previous studies have also reported that gender, body mass index (BMI), pregnancy, and metabolic status are associated with diabetes. 8,9 Early detection and symptomatic treatment are crucial to ensure the healthy life and well-being of individuals with prediabetes. [10][11][12][13] With the continuous advancement of technology, machine learning and deep learning techniques have become very useful in early prediction and disease analysis. ...
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Objectives Diabetes is a metabolic disease and early detection is crucial to ensuring a healthy life for people with prediabetes. Community care plays an important role in public health, but the association between community follow-up of key life characteristics and diabetes risk remains unclear. Based on the method of optimal feature selection and risk scorecard, follow-up data of diabetes patients are modeled to assess diabetes risk. Methods We conducted a study on the diabetes risk assessment model and risk scorecard using follow-up data from diabetes patients in Haizhu District, Guangzhou, from 2016 to 2023. The raw data underwent preprocessing and imbalance handling. Subsequently, features relevant to diabetes were selected and optimized to determine the optimal subset of features associated with community follow-up and diabetes risk. We established the diabetes risk assessment model. Furthermore, for a comprehensible and interpretable risk expression, the Weight of Evidence transformation method was applied to features. The transformed features were discretized using the quantile binning method to design the risk scorecard, mapping the model's output to five risk levels. Results In constructing the diabetes risk assessment model, the Random Forest classifier achieved the highest accuracy. The risk scorecard obtained an accuracy of 85.16%, precision of 87.30%, recall of 80.26%, and an F1 score of 83.27% on the unbalanced research dataset. The performance loss compared to the diabetes risk assessment model was minimal, suggesting that the binning method used for constructing the diabetes risk scorecard is reasonable, with very low feature information loss. Conclusion The methods provided in this article demonstrate effectiveness and reliability in the assessment of diabetes risk. The assessment model and scorecard can be directly applied to community doctors for large-scale risk identification and early warning and can also be used for individual self-examination to reduce risk factor levels.
... Traditionally supervised learning algorithms are used for training the model with labeled data, and testing data is used for evaluation using testing data. Earlier studies reported that sex, pregnancy, body mass index (BMI), and metabolic status are associated with diabetes [13,14]. ...
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With the growing numbers of diabetic patients across North America, the United States of America has recorded a higher percentage of people diagnosed with diabetes. The number constitutes 11 percent of the total population in the USA. These numbers spread across various races, ethnicity, gender, and income bracket. In the United States of America, diabetes is common among adults with a family income lower than the federal poverty level. Numerous scholars have developed predicting and classifying models to analyze diabetic data to infer the result generated by their models to support clinical decisions. In this paper, predictive analytics using dynamic machine learning algorithms will detect patterns and relationships from pregnancy data. Instant diagnosis and prediction of diabetes will give patients more time for preventive care and appropriate treatment. The physician used the precision and accuracy of the model to advise patients medically on risk factors and the better way to manage diabetes. The predictive model built in Waikato Environment for Knowledge Analysis (WEKA) was used to analyze pregnancy over 2500 patient data using Naïve Bayes and Decision Tree algorithms. The data served as input data to train the model using these attributes (Pregnancy week, Glucose, Skin Thickness, Blood Pressure, BMI, Age, Insulin, Diabetes Pedigree Score, and Outcome). An incremental data pre-processing method was adopted to remove noisy data. The data was calibrated into 70 percent for training and 30 percent for testing. Decision Tree accuracy and the precision rate is at an average of 80 percent, while Naïve Bayes underperforms because of its inability to learn and identify patterns within the datasets. Keywords: Pregnancy; Algorithms; CRISP-DM; Patient; WEKA
... 5,[9][10][11] Some earlier articles have also pointed that body mass index (BMI), sex, metabolic status, and pregnancy are associated with diabetes. 8,12 Recently, some articles have point-ed out the diabetes risk factors using logistic regression adopting machine learning algorithms. 13,14 Most of the previous articles have focused on diabetes risk factors based on the logistic regression analysis, where the response is a dichotomous discrete variable, which loses a lot of information. ...
... The model's strength, to some part, stems from the fact that it was built using data from a large national representative sample in South China and verified using data from an external population in North China. Data that have been included in other published nomogram models concerning daily consumption of vegetables, fruits, or berries (27) and use of steroids (28) were not available in our study questionnaire. It is not clear to what extent these missing variables will affect the need to assess risk of isolated high 2-hour plasma glucose. ...
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A tool was constructed to assess need of an oral glucose tolerance test (OGTT) in patients whose fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are normal. Data was collected from the longitudinal REACTION study conducted from June to November 2011 (14,686 subjects, aged ≥ 40 y). In people without a prior history of diabetes, isolated high 2-hour plasma glucose was defined as 2-hour plasma glucose ≥ 11.1 mmol/L, FPG < 7.0 mmol/L, and HbA1c < 6.5%. A predictive nomogram for high 2-hour plasma glucose was developed via stepwise logistic regression. Discrimination and calibration of the nomogram were evaluated by the area under the receiver operating characteristic curve (AUC) and Hosmer-Lemeshow test; performance was externally validated in Northeast China. Parameters in the model included gender, age, drinking status, marriage status, history of hypertension and hyperlipidemia, waist-to-hip ratio, FPG, and HbA1c. All variables were noninvasive, except FPG and HbA1c. The AUC of the nomogram for isolated high 2-hour plasma glucose was 0.759 (0.727-0.791) in the development dataset. The AUCs of the internal and externally validation datasets were 0.781 (0.712-0.833) and 0.803 (0.778-0.829), respectively. Application of the nomogram during the validation study showed good calibration, and the decision curve analysis indicated that the nomogram was clinically useful. This practical nomogram model may be a reliable screening tool to detect isolated high 2-hour plasma glucose for individualized assessment in patients with normal FPG and HbA1c. It should simplify clinical practice, and help clinicians in decision-making.
... The estimated sample size was calculated using a power of 85% and a sampling error of 5% with sensitivity of the screening tool of 72% [11], and an estimated diabetes prevalence of 14.4% [12]. The minimum sample size needed is 176, which was increased by four patients to account for potential dropouts. ...
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Introduction The prevalence of type 2 diabetes (T2D) is growing worldwide. This study aimed to assess the sensitivity and specificity of the American Diabetes Association (ADA) and the United States Centers for Disease Control and Prevention's diabetes risk test in identifying Saudi Arabian patients at risk of developing T2D. Methods We conducted a one-month cross-sectional study that included patients older than 18 years who visited primary care facilities for any health concern in Riyadh City, Saudi Arabia. We used the Arabic language version of the ADA Prediabetes Risk Test questionnaire, a validated and reliable tool, to collect data. For this study, we analyzed the data using IBM SPSS Statistics for Windows, version 24.0 (IBM Corp., Armonk, New York). Moreover, we calculated sensitivity and specificity, positive predictive values (PPV), negative predictive value (NPV), the area under the curve (AUC), and Youden’s index. Results A total of 180 participants were included in the study (121 women and 59 men; mean age = 45 years). The ADA Prediabetes Risk Test sensitivity was 78.9, specificity was 82, PPV was 32, and NPV was 76. Youden’s index was 60.9 and the AUC was 0.6. Conclusion The ADA prediabetes risk assessment tool is highly sensitive and specific for determining the disease. It is a reliable and valid tool that has not yet been implemented to a great extent in Saudi Arabia. Therefore, future work should study the tool’s effectiveness in risk assessment in additional local Saudi Arabian communities.
... The main risk factors of diabetes are considered to be an unhealthy diet, aging, family history, ethnic groups, obesity, sedentary lifestyle, and previous history of gestational diabetes [6,7,12]. Previous studies have also reported that sex, body mass index (BMI), pregnancy, and metabolic status are associated with diabetes [13,14]. ...
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Diabetes mellitus is one of the most common human diseases worldwide and may cause several health-related complications. It is responsible for considerable morbidity, mortality, and economic loss. A timely diagnosis and prediction of this disease could provide patients with an opportunity to take the appropriate preventive and treatment strategies. To improve the understanding of risk factors, we predict type 2 diabetes for Pima Indian women utilizing a logistic regression model and decision tree—a machine learning algorithm. Our analysis finds five main predictors of type 2 diabetes: glucose, pregnancy, body mass index (BMI), diabetes pedigree function, and age. We further explore a classification tree to complement and validate our analysis. The six-fold classification tree indicates glucose, BMI, and age are important factors, while the ten-node tree implies glucose, BMI, pregnancy, diabetes pedigree function, and age as the significant predictors. Our preferred specification yields a prediction accuracy of 78.26% and a cross-validation error rate of 21.74%. We argue that our model can be applied to make a reasonable prediction of of type 2 diabetes, and could potentially be used to complement existing preventive measures to curb the incidence of diabetes and reduce associated costs.
... The recent consensus report of the joint workshop of the International Diabetes Federation and the European Federation of Periodontology reports that dentists dealing with patients without a diagnosis of diabetes are encouraged to apply screening methods and assess their risk for having diabetes, in order to refer to a physician for further testing identified subjects . In fact, the importance of validated questionnaires has been shown in a number of studies and they can be used with reasonable accuracy for prediabetes/diabetes screening (Bang et al., 2009;Herman, Smith, Thompson, Engelgau, & Aubert, 1995;Poltavskiy, Kim, & Bang, 2016;Rolka et al., 2001). This approach is certainly low-cost and therefore suitable for large-scale assessments both in clinical and community settings especially in low income countries. ...
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Abstract Objective: The aim of the study was to propose an efficient chairside clinical strategy for the identification of undiagnosed hyperglycaemia in periodontal clinics. Material and methods: Α chairside system was used for assessment of glycated hemoglobin 1c (HbA1c) and active Matrix Metalloproteinase-8 levels (aMMP-8) were analyzed by immunotest in patients (n = 150) who fulfilled the criteria for screening of the Centers for Disease Control and Prevention. Full-mouth periodontal parameters were assessed and various data such as Body Mass Index (BMI), smoking and education were recorded. Results: Thirty-one patients out of 150 tested were found with unknown hyperglycaemia (20.7%). Regarding sex, education, parent with diabetes, normal BMI, smoking, age ≥45 years and prior testing for diabetes, no differences were observed between subjects displaying HbA1c < 5.7 and ≥5.7% (Pearson's Chi-square test, p > .05). Subgroups differed regarding BMI (kg/m2 ), tooth count, percentages of 4 and 5 mm pockets (Mann-Whitney and z-test, p < .05). The diagnostic performance for HbA1c ≥5.7 was tested by Receiving Operator Characteristic curves and Areas Under the Curve (AUC) for the following: age ≥ 45 years and BMI (AUC 0.651, p = .010), the above and aMMP-8 (AUC 0.660, p = .006), age ≥ 45 years, BMI and Stage of Periodontitis (AUC 0.711, p < .001) and age ≥ 45 years, BMI, aMMP-8 and stage of periodontitis (AUC 0.713, p < .001). Conclusions: Findings of the study suggest that the combination of stage of periodontitis, increasing age, BMI and aMMP-8, without chairside HbA1c assessment appears to be a viable screening strategy for referring dental patients for testing for prediabetes/diabetes. Keywords: diabetes; diagnosis; matrix metalloproteinase.
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Diabetes is a major cause of morbidity and mortality, though these outcomes are not due to the immediate effects of the disorder. They are instead related to the diseases that develop as a result of chronic diabetes mellitus. These include diseases of large blood vessels,microvascular disease, and peripheral ,coronary heart diseases, arterial disease) and small blood vessels (microvascular disease, including retinal and renal vascular disease), as well as diseases of the nerves. Keywords: DM type II, multy sectoral strategies
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Objectives: Owing to increase in prevalence of obesity and metabolic syndrome in Indian children and adolescents, this study is conducted to assess the predictive value of IAP 2015 and WHO 2007 BMI for age cut-offs in identifying metabolic risk in Indian children. Methods: Cross-sectional multicentric school-based study on 9-18-year-old healthy children (n=1,418) randomly selected from three states of India. Results: WHO 2007 and IAP 2015 charts classified 222 (15.7%) and 271 (19.1%) as overweight/obese, respectively. A total of 192 (13.5%) subjects had metabolic risk. Of these 47 (25%) and 36 (18.75%) were classified as having normal body mass index (BMI) by WHO and IAP, respectively. In identifying metabolic risk, IAP 2015 and WHO 2007 charts showed a sensitivity of 81.3 and 75%, negative predictive value 96.5% as against 94.8%, positive predictive value 57.5 and 64.8%, and specificity of 89.7 and 91.6%, respectively. Conclusions: Owing to obesity epidemic and high metabolic risk in Indians, IAP 2015 charts (as against the WHO 2007 references) which had a higher sensitivity in identifying metabolic risk may be more suitable in Indian children and adolescents.
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The Diabetes Prevention Program is a randomized clinical trial testing strategies to prevent or delay the development of type 2 diabetes in high-risk individuals with elevated fasting plasma glucose concentrations and impaired glucose tolerance. The 27 clinical centers in the U.S. are recruiting at least 3,000 participants of both sexes, similar to 50% of whom are minority patients and 20% of whom are greater than or equal to 65 years old, to be assigned at random to one of three intervention groups. an intensive lifestyle intervention focusing on a healthy diet and exercise and two masked medication treatment groups-metformin or placebo-combined with standard diet and exercise recommendations. Participants are being recruited during a 2 2/3-year period, and all will be followed for an additional 3 1/3 to 5 years after the close of recruitment to a common closing dare in 2002. The primary outcome is the development of diabetes, diagnosed by fasting or post-challenge plasma glucose concentrations meeting the 1997 American Diabetes Association criteria. The 3,000 participants will provide 90% power to detect a 33% reduction in an expected diabetes incidence rate of at least 6.5% per year in the placebo group. Secondary outcomes include cardiovascular disease and its risk factors; changes in glycemia, beta-cell function, insulin sensitivity obesity diet, physical activity and health-related quality; of life: and occurrence of adverse events. A fourth treatment group troglitazone combined with standard diet and exercise recommendations-was included initially but discontinued because of the liver toxicity of the drug. This randomized clinical trial will test the possibility of preventing or delaying the onset of type 2 diabetes in individuals at high risk.
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The Diabetes Prevention Program is a randomized clinical trial testing strategies to prevent or delay the development of type 2 diabetes in high- risk individuals with elevated fasting plasma glucose concentrations and impaired glucose tolerance. The 27 clinical centers in the U.S. are recruiting at least 3,000 participants of both sexes, ~50% of whom are minority patients and 20% of whom are ≥65 years old, to be assigned at random to one of three intervention groups: an intensive lifestyle intervention focusing on a healthy diet and exercise and two masked medication treatment groups - metformin or placebo - combined with standard diet and exercise recommendations. Participants are being recruited during a 2 2/3-year period, and all will be followed for an additional 3 1/3 to 5 years after the close of recruitment to a common closing date in 2002. The primary outcome is the development of diabetes, diagnosed by fasting or post- challenge plasma glucose concentrations meeting the 1997 American Diabetes Association criteria. The 3,000 participants will provide 90% power to detect a 33% reduction in an expected diabetes incidence rate of at least 6.5% per year in the placebo group. Secondary outcomes include cardiovascular disease and its risk factors; changes in glycemia, β-cell function, insulin sensitivity, obesity, diet, physical activity, and health-related quality of life; and occurrence of adverse events. A fourth treatment group - troglitazone combined with standard diet and exercise recommendations - was included initially but discontinued because of the liver toxicity of the drug. This randomized clinical trial will test the possibility of preventing or delaying the onset of type 2 diabetes in individuals at high risk.
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The role and value of screening for diabetes mellitus is still unclear. If asymptomatic subjects are to be screened, then a fasting plasma glucose > 6.6 mmol 1−1 or a venous plasma glucose 2 h after a 75 g oral glucose load > 8.0 mmol 1−1 or the presence of any glucose in a urine sample passed 2 h after a main meal should be regarded as a positive result. A fasting plasma glucose in the range 5.5–6.6 mmol 1−1 is an equivocal result which should lead to retesting in 6–12 months if there is any risk factor for diabetes (obesity, family history of diabetes, Asian/African racial origin). Other screening tests or combinations of tests are not recommended. Screening should be restricted to subjects between 40 and 75 years and should be undertaken only every 5 years (3 years if a risk factor for diabetes is present), ideally in parallel with other health screening initiatives. No diagnosis should be made or treatment begun on the basis of a single screening test; subjects with a positive result should have further investigations as necessary to reach a diagnosis in line with WHO criteria.
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Introduction Assumptions EM and Inference by Data Augmentation Methods for Normal Data More on the Normal Model Methods for Categorical Data Loglinear Models Methods for Mixed Data Further Topics Appendices References Index
Article
Blood glucose 2 h after an oral glucose load (2hBG) and glycohaemoglobin (GHb) (Corning agar-gel electrophoresis) levels were used as screening tests in a general practice diabetic screening programme. The diagnosis of diabetes (DM) was based on a separate oral glucose tolerance test (OGTT) in 223 of 1040 screened subjects, selected as a stratified sample biased towards higher levels of 2hBG and GHb. The GHb assay was also repeated at the recall examination and urine was tested for glycosuria before and after glucose administration. At a cut-off level of 8.1%, the screening GHb assay correctly identified 90% of all probable diabetics with a specificity of 85.3% (95% CI 83.3–87.3%) and a positive predictive value of 14.0% (9.0–19.0%). The specificity of the screening GHb assay as a screening test for true DM was 45.8% (39.0–52.4%) at 90% sensitivity, and that of the recall GHb assay was 64.5% (57.9–71.1%). The screening 2hBG was 93.3% (88.9–97.7%) specific at 90% sensitivity as a screening test for true DM diagnosed by OGTT at recall. The test characteristics for fasting glycosuria were: sensitivity 16.7% (0–37.8%) and specificity 98.0% (96.0–100.0%). Equivalent values for the post-glucose test for glycosuria were: 72.7% (46.4–99.0%) and 77.4% (70.1–84.7%), respectively. While GHb assay is a poorer screening test for DM than the 2hBG at the single cut-off level quoted, comparison of the accuracy of the two tests shows that the GHb assay is only marginally less accurate. It is superior to testing for glycosuria as a screening test for DM and can be performed on any random blood sample, facilitating its use in population screening.
Article
To examine the efficiency of fasting plasma glucose (FPG) as a screening test for non-insulin-dependent diabetes mellitus (NIDDM). RESEARCH AND METHODS DESIGN: A population-based evaluation was made of FPG as screening test for NIDDM in an upper middle-class white community of Rancho Bernardo, California. NIDDM was defined by 2-h postchallenge plasma glucose (PCPG) level greater than or equal to 11.1 mM, the cutoff point recommended by the World Health Organization. Participants comprised a population-based sample of 1851 men and women 50-79 yr of age that represented 80% of surviving participants surveyed between 1972 and 1974 for the Lipid Research Clinic Prevalence Study. Those with insulin-dependent diabetes were excluded. Analyses were stratified by age after logistic regression indicated that FPG and age (but not gender) were significantly related to probability of disease. As FPG cutoff points increased, sensitivity and percentage of the population to be recalled for confirmation decreased, whereas specificity and positive predictive value increased. Negative predictive value was consistently in the 90% range. Specificity did not change with age. In contrast, at virtually every FPG cutoff point, sensitivity decreased with increasing age. For example, at FPG greater than or equal to 6.7 mM, sensitivity was 65.6% for those 50-64 yr of age and 40.0% for those 65-79 yr of age. At FPG greater than or equal to 7.2 mM, these sensitivities were 46.9 and 28.5%, respectively. Positive predictive value increased with increasing age, reflecting the increasing prevalence of NIDDM with age. Poorer sensitivity with increasing age reflects the fact that the numerator of the sensitivity equation is not affected by age (mean FPG did not vary significantly between age-groups), whereas the denominator increases with age (mean PCPG increased from 6.6 mM for subjects 50-64 yr of age to 8.2 mM for subjects 65-79 yr of age). Nevertheless, because the clinical significance of increasing PCPG with age in older adults is unknown, age-specific screening criteria probably are not warranted.
Article
To determine the efficacy of HbA1c and fructosamine as alternatives to fasting plasma glucose (FPG) for diabetes screening. Receiver operating characteristic (ROC) analysis was conducted on the above tests. Comparison among tests was based on the area under ROC curve of a test. World Health Organization criteria for classifying glucose tolerance status of the subjects was used. The study consisted of subjects (n = 583) who visited the clinic from September to October 1989 and all diabetic cases (n = 36) from November 1989 to March 1990, after excluding those less than 40 yr of age or with hypoglycemic therapies (469 were normal, 88 with impaired glucose tolerance ( IGT], and 62 with diabetes). Area under ROC curve of HbA1c was not different from that of FPG. Area under curve of fructosamine was significantly smaller than that of FPG. For all tests, overall efficacy of a test to detect IGT and diabetes was considerably diminished compared with detection of diabetes alone. The discriminating ability of HbA1c is almost the same as that of FPG, therefore HbA1c is a good alternative to FPG. Fructosamine is not suitable for diabetes screening.
Article
A 14%, simple random sample of the King Saud University Community consisting of students, faculty and staff was screened for diabetes mellitus. The screening procedures used consisted of rine testing by means of the urine dipstick and blood glucose estimation in the fasting state by means of the reflomat glucose, a glucose oxidase meter. Participants whose fasting blood glucose (FBG) were 140 mg/dl or more were referred to the diabetes clinic for further evaluation and possible inclusion into the subsequent retrospective study. A period prevalence of 6.0% was observed for FBG > 140 mg/dl and all the referrals were confirmed for adult onset diabetes mellitus. The prevalence was similar to that in the USA and suggested that the rapid socio-economic changes in Saudi Arabia made a minimal contribution to the prevalence of diabetes mellitus.