Abstract
Background
Cardiac autonomic neuropathy (CAN) is a frequent but under-recognized complication of type 2 diabetes mellitus (T2DM) that is strongly associated with arrhythmia, silent myocardial ischemia, and cardiovascular mortality. The use of cardiovascular autonomic reflex tests (CARTs) to assess CAN is often limited in resource-constrained clinical settings. Therefore, symptom-based tools such as the Composite Autonomic Symptom Score-31 (COMPASS-31) have been proposed as screening approaches, but evidence on their feasibility remains scarce. This study assessed the feasibility, diagnostic accuracy, and agreement of the COMPASS-31 for identifying cardiovascular autonomic dysfunction assessed using standardized CARTs among adults with T2DM in Zanzibar.
Methods
A cross-sectional study was conducted among adults with T2DM attending the diabetes clinic at Mnazi Mmoja Hospital, Zanzibar. Participants were recruited using a systematic random sampling technique. Orthostatic symptoms were assessed using the COMPASS-31 questionnaire. Objective autonomic function was assessed using an automated CAN analyser implementing standardized CARTs, including resting heart rate variability, deep breathing test, Valsalva maneuver, heart rate response to standing, postural hypotension, and sustained handgrip test. Agreement between the COMPASS-31 orthostatic intolerance domain and CARTs findings was assessed using Cohen’s kappa. Diagnostic performance measures included sensitivity, specificity, predictive values, likelihood ratios, and accuracy.
Results
Among 364 participants, the COMPASS-31 orthostatic intolerance domains classified 260 (71.4%) as abnormal, while 291 (79.9%) demonstrated abnormal autonomic findings on CARTs assessment. Overall agreement was 86.0%, with substantial agreement beyond chance (κ = 0.62). Sensitivity and specificity of the COMPASS-31 domain were 85.9% and 86.3%, respectively, with positive and negative likelihood ratios of 6.27 and 0.16. Internal consistency of the orthostatic intolerance domain was good (Cronbach’s alpha = 0.82). However, correlations between the orthostatic intolerance domain and CAN analyser findings were weak, and ROC analyses demonstrated poor discrimination (AUC 0.51–0.56).
Conclusion
The COMPASS-31 orthostatic intolerance domain showed substantial agreement and moderate screening performance for detecting CAN in adults with T2DM. These findings support its use as a practical symptom-based screening adjunct to identify individuals who may benefit from further objective autonomic testing, particularly in resource-limited settings.
Keywords: Cardiac autonomic neuropathy, Cardiovascular autonomic reflex tests, Orthostatic intolerance, COMPASS-31, Type 2 diabetes mellitus
Introduction
Cardiac autonomic neuropathy (CAN) is a frequent but often underdiagnosed complication of diabetes mellitus (DM), largely due to its non-specific clinical presentation and complex diagnostic requirements [1–3]. It results from impairment of autonomic control of the cardiovascular system and may occur early in the course of disease, including in people with recently diagnosed diabetes [4]. Reported prevalence estimates vary widely depending on diagnostic criteria and assessment methods [5, 6], ranging from 22% to 62% [6–16].
CAN is clinically important because it is associated with orthostatic hypotension, exercise intolerance, silent ischemia, arrhythmia, and increased cardiovascular mortality [17, 18]. Despite this clinical importance, routine assessment remains limited, particularly in low-resource settings. Cardiovascular autonomic reflex tests (CARTs) are widely used for the objective evaluation of CAN, but they require dedicated equipment, standardized procedures, and trained personnel, which can limit their implementation in routine diabetes care [7, 17–19].
Symptom-based tools may offer a more feasible alternative for preliminary assessment [20]. The Composite Autonomic Symptom Score-31 (COMPASS-31) is a brief and structured questionnaire that quantifies autonomic symptom burden across six domains: orthostatic intolerance, vasomotor, secretomotor, gastrointestinal, bladder, and pupillomotor symptoms [21, 22]. It has been used in several autonomic disorders and in diabetes populations [21], but the extent to which symptom scores reflect objectively measured CAN remains uncertain [17].
Studies have documented moderate to strong associations between various autonomic symptom scales and laboratory-based autonomic function tests in different patient populations [23]. However, discrepancies between self-reported symptoms and objective autonomic measurements raise important questions regarding the reliability of questionnaire-based assessments as standalone diagnostic tools [21, 23, 24]. Factors such as patient perception, comorbid conditions, and variability in autonomic dysfunction progression may contribute to these inconsistencies. Further validation studies are therefore needed to clarify the relationship between symptom burden and objectively measured cardiac autonomic dysfunction in individuals with T2DM [23, 24].
Current guidelines recommend the evaluation of autonomic symptoms in individuals with diabetes, yet validated questionnaires specifically designed for this purpose remain limited. Previous validation studies in other populations have reported moderate diagnostic accuracy, suggesting potential utility as a screening tool, although findings remain inconsistent [23]. Therefore, this study aimed to evaluate the diagnostic accuracy and agreement of the COMPASS-31 orthostatic intolerance domain against cardiovascular autonomic neuropathy defined using standardized cardiovascular autonomic reflex tests (CARTs) measured with an automated CAN analyser (CAN 504 Kody Medical Electronics Private Limited) among adults with T2DM attending a tertiary hospital in Zanzibar.
Materials and methods
Study design and setting
This was a cross-sectional diagnostic accuracy study nested within a broader hospital-based study of autonomic dysfunction among adults with T2DM in Zanzibar. The study was conducted at the diabetes clinic of Mnazi Mmoja Hospital, the main tertiary referral hospital in Zanzibar, from December 2023 to March 2024. All eligible participants were adults aged ≥ 18 years, permanent residents of Zanzibar, and had a confirmed diagnosis of T2DM and were receiving at least one antidiabetic medication. Individuals with conditions likely to affect autonomic function independent of diabetes were excluded. Individuals with serious illnesses of the autonomic nervous system were also excluded, as shown in Fig. 1.
Fig. 1.
Study profile
Socio-demographic and behavioural factors
Social demographic and disease data were gathered using a standardized questionnaire. The study’s goals were explained to the patients, and their consent was obtained. The participants were told to avoid smoking, caffeine, intense exercise, and any drugs that would impair cardiac autonomic function for 24 h before the assessment. A standardised questionnaire was distributed and was used to gather data on their history of diabetes treatment, alcohol use, and smoking. The diabetes treatment history was verified by clinic records based on self-reporting for those participants whose records were available for review.
Physical measurements
Each participant’s height, weight, hip circumference, and waist circumference were measured. Body Mass Index (BMI) was computed by dividing the participant’s weight (in kilograms) by height (in meters squared), and thereafter classified based on the World Health Organization (WHO) classification as underweight (<18.5 kg/m²), normal weight (18.5–24.9 kg/m²), overweight (25.0–29.9 kg/m²), and obesity (≥30.0 kg/m²) [25]. Central obesity was defined as a waist circumference of at least 102 cm for men, and at least 88 cm for women [25]. Hypertension was defined as blood pressure readings of ≥140/90 mmHg based on the American Diabetes Association (ADA) [26], and the use of antihypertensive drugs was deemed indicative of arterial hypertension in the participant. Physical activity was assessed using the Global Physical Activity Questionnaire (GPAQ) administered via KoboToolbox, and MET-minutes per week were calculated according to WHO guidelines [27, 28].
Biochemical measurements
Fasting venous blood samples were obtained from all study participants by certified laboratory professionals during a scheduled morning visit following recruitment. Participants were instructed to fast for at least 8 h prior to sample collection for lipid profile assessment. Approximately 4 mL of venous blood was drawn into vacuum collection tubes at the laboratory unit of MMH. The collected samples were analyzed for glycated hemoglobin (B-HbA1c) and lipid profile parameters, including total cholesterol (mmol/L), LDL-cholesterol (mmol/L), HDL-cholesterol (mmol/L), and triglycerides (mmol/L). Standardized procedures and protocols were followed to measure a range of biochemical characteristics, including fasting glucose, B-HbA1c (DCCT), lipid profile, and renal function.
Assessment of orthostatic intolerance and cardiovascular autonomic neuropathy
Orthostatic intolerance (OI) was assessed using two approaches: The Composite Autonomic Symptom Score-31 (COMPASS-31) questionnaire and the Cardiac Autonomic Neuropathy (CAN) Analyser. The subjective measurement of OI was obtained from the orthostatic intolerance domain of the COMPASS-31 questionnaire, in which participants self-reported the frequency and severity of symptoms such as dizziness, lightheadedness, and near fainting upon standing.
Objective measurement of cardiovascular autonomic function was performed using the CAN Analyser (CAN 504 Kody Medical Electronics Private Limited), based on the standardised cardiovascular reflex tests (CARTs) described by Ewing and Clarke [29] (Table 1).
Table 1.
Cardiovascular autonomic reflex tests used for assessment of cardiac autonomic neuropathy [30]
| Test | Procedure | Physiological index measured | Abnormal threshold |
|---|---|---|---|
| Resting heart rate variability | Participant rested supine for ≥ 5 min with continuous 3-lead ECG monitoring | Baseline resting heart rate | > 100 beats/min |
| Deep breathing test (E: I ratio) | Six deep breaths per minute while supine for 1 min | The difference between the maximum and minimum heart rate during the breathing cycle | < 11 bpm abnormal; 11–14 bpm borderline |
| Heart rate response to standing (30:15 ratio) | Participant moved from supine to standing; RR intervals were measured during the first 30 cardiac cycles | Ratio of longest RR interval (beats 20–40) to shortest RR interval (beats 5–25) | < 1.01 abnormal; 1.01–1.03 borderline |
| Valsalva maneuver | Forced expiration at 40 mmHg for 15 s using a mouthpiece and manometer | Ratio of the longest RR interval after the maneuver to the shortest RR interval during the maneuver | < 1.10 abnormal; 1.10–1.20 borderline |
| Postural hypotension | Blood pressure measured in the supine position and after standing (1–3 min) | Decrease in systolic blood pressure after standing | ≥ 30 mmHg abnormal; 11–29 borderline |
| Sustained handgrip | Handgrip at 30% of maximal voluntary contraction for 3 min | Increase in diastolic blood pressure during handgrip exercise | < 11 mmHg abnormal; 11–15 borderline |
ECG – Electrocardiogram, E: I – Expiration: Inspiration ratio
The CAN 504 analyser computes autonomic indices using ECG-derived R–R intervals and blood pressure measurements based on standard Ewing definitions (E: I ratio as the ratio between maximum and minimum heart rate during deep breathing, and Valsalva ratio as the ratio of longest to shortest R–R intervals during the maneuver). The device is factory-calibrated, and signal quality was verified prior to each assessment to ensure reliable measurements.
Scoring of the orthostatic intolerance domain
The orthostatic intolerance domain of the COMPASS-31 questionnaire consists of four items assessing symptoms of dizziness, faintness, cognitive difficulty, or “goofy” sensations occurring after standing. The first question serves as a screening item (Yes = 1 point; No = 0 points). If the participant responds “No,” subsequent questions are skipped, and the domain score is recorded as 0. If “Yes,” three additional items assess symptom frequency (scored 0–3 for rarely to almost always), symptom severity (scored 1–3 for mild to severe), and symptom progression over the past year (scored 0–3, with higher scores assigned to worsening symptoms and 0 assigned to improvement or resolution).
The raw domain score ranges from 0 to 10. To obtain the weighted domain score, the raw score is multiplied by the orthostatic intolerance weighting factor of 4.0, yielding a maximum possible weighted score of 40. For diagnostic accuracy analysis, the COMPASS-31 orthostatic intolerance domain was dichotomized as positive if the weighted domain score was > 0 and negative if the score was 0. Higher scores indicate greater severity and burden of orthostatic autonomic symptoms [20]. This symptom-based score was used to characterize the presence and severity of orthostatic intolerance and was subsequently compared with objective measures of cardiovascular autonomic function obtained from CARTs.
In contrast to the symptom-based COMPASS-31 assessment, objective autonomic dysfunction was quantified using the CART scoring system. Each cardiovascular autonomic reflex test was scored as 0 (normal), 0.5 (borderline), or 1 (abnormal), and the total CAN score was obtained by summing the scores across all six tests (Table 2). This total score was then used to classify participants into normal cardiac autonomic function, early CAN, definite CAN, or severe CAN, according to standardized criteria. This composite score provided an objective classification of CAN severity, allowing comparison between patient-reported orthostatic symptoms and physiologically measured autonomic dysfunction.
Table 2.
Classification of cardiac autonomic neuropathy severity [30]
| Total score | Interpretation |
|---|---|
| 0 | Normal autonomic function |
| 0.5–1.5 | Early CAN |
| 2–3 | Definite CAN |
| ≥ 3.5 | Severe CAN |
For the primary diagnostic accuracy analysis, participants with a total CART score of 0 were classified as CAN-negative, and those with a score ≥ 0.5 as CAN-positive
Ethical considerations
This study was conducted in accordance with internationally accepted ethical standards, including the Declaration of Helsinki, the Guidelines for Good Clinical Practice (GCP), and the International Council for Harmonisation (ICH) recommendations, as well as the principles of Good Clinical and Laboratory Practice (GCLP) where applicable. Ethical approval was obtained from the Zanzibar Health Research Ethics Committee (ZAHREC; Ref. No. ZAHREC/05/ST/DEC/2023/184) and the Institutional Review Board of the Muhimbili University of Health and Allied Sciences (MUHAS-IRB; Ref. No. MUHAS-REC-02-2023-1528).
Written informed consent was obtained from all participants prior to study enrollment. To ensure confidentiality, all personally identifiable information was removed from the dataset, and unique identification codes were assigned to each participant during data collection. Participants were informed that their participation was voluntary and that they could withdraw from the study at any time without affecting their clinical care.
Statistical analysis
Data were analysed using STATA version 18 software. Continuous variables were summarized as mean ± SD or median (IQR), as appropriate, and categorical variables as frequencies and percentages. The prevalence of abnormal findings was determined using both the COMPASS-31 orthostatic intolerance domain and the CAN analyser. For the primary diagnostic accuracy analysis, the COMPASS-31 orthostatic intolerance domain was compared against the CARTs-defined cardiac autonomic neuropathy. Agreement between the two methods was assessed using Cohen’s kappa coefficient.
Using CART-defined CAN as the reference standard, we evaluated sensitivity, specificity, positive predictive value, negative predictive value, overall accuracy, and positive and negative likelihood ratios. Receiver operating characteristic (ROC) analyses were performed for individual orthostatic intolerance items, and areas under the curve (AUCs) were reported. Spearman’s rank correlation was used to assess associations between COMPASS-31 item scores and objective autonomic findings. Internal consistency of the orthostatic intolerance domain was assessed using Cronbach’s alpha. A two-sided p-value < 0.05 was considered statistically significant.
Results
The mean age of participants was 56.0 ± 10.9 years. Most participants were aged 40–60 years (55.5%), and 66.8% were female. The mean BMI was 28.3 ± 6.4 kg/m², and 68.1% were either overweight or obese. Mean systolic and diastolic blood pressures were 151.1 ± 26.0 mmHg and 87.8 ± 15.3 mmHg, respectively, while 84.1% of participants were hypertensive. Median sedentary time was 45.0 min/day (IQR 30.0–60.0). Additional clinical and biochemical characteristics are presented in Table 3.
Table 3.
Characteristics of study participants (N = 364)
| Variables | Mean (SD) | Frequency (N) |
Percent (%) |
|---|---|---|---|
| Age (years) | 56.0 (10.9) | ||
| < 40 | 28 | 7.7 | |
| 40–60 | 202 | 55.5 | |
| > 60 | 134 | 36.8 | |
| Sex | |||
| Male | 121 | 33.2 | |
| Female | 243 | 66.8 | |
| Duration of Diabetes (years) | |||
| 1–3 | 161 | 44.2 | |
| 4–6 | 44 | 12.1 | |
| 7–9 | 51 | 14.0 | |
| ≥ 10 | 108 | 29.7 | |
| BMI (kg/m²) | 28.3 (6.4) | ||
| Under weight | 11 | 3.0 | |
| Normal | 105 | 28.9 | |
| Overweight | 131 | 36.0 | |
| Obese | 117 | 32.1 | |
| Blood pressure (mmHg) | |||
| Systole | 151.1 (26.0) | ||
| Diastole | 87.8 (15.3) | ||
| Hypertensive (mmHg) | |||
| Normal | 58 | 15.9 | |
| Hypertensive | 306 | 84.1 | |
| Sedentary lifestyle (minutes/day) 1 | 45.0 (30.0–60.0) | ||
| Inactive | 357 | 98.1 | |
| Active | 7 | 1.9 | |
| Oral hypoglycemic agents | |||
| No | 183 | 50.3 | |
| Yes | 181 | 49.7 | |
| S-LDL cholesterol (mmol/L) | 2.9 (1.5) | ||
| Normal | 195 | 53.6 | |
| Abnormal | 169 | 46.4 | |
| S-HDL cholesterol (mmol/L) | 1.5 (0.7) | ||
| Normal | 279 | 76.7 | |
| Abnormal | 85 | 23.4 | |
| S-Triglycerides (mmol/L) | 1.8 (1.1) | ||
| Normal | 194 | 53.3 | |
| Abnormal | 170 | 46.7 | |
| B-HbA1c (DCCT) | 7.3 (2.8) | ||
| Normal | 170 | 46.7 | |
| Abnormal | 194 | 53.3 |
¹Data presented as median (interquartile range) due to non-normal distribution
Table 4 presents the prevalence of orthostatic intolerance and cardiovascular autonomic neuropathy (CAN) assessed using the COMPASS-31 orthostatic intolerance domain and CART-based testing, respectively. The distributions were comparable, although CART classified a higher proportion of participants as abnormal. Using COMPASS-31, 260/364 participants 71.4% were symptom-positive, whereas 291/364 (79.9%) were classified as having CAN based on a CART score ≥ 0.5. Cross-classification of the two methods showed that 313 participants were concordantly classified, yielding an overall agreement of 86.0%, whereas 51 participants were discordantly classified, 14.0%.
Table 4.
Prevalence of orthostatic intolerance from COMPASS-31 versus CART-defined cardiovascular autonomic neuropathy (N = 364)
| Method | Normal (n, %) | Abnormal (n, %) |
|---|---|---|
| COMPASS-31 orthostatic intolerance domain | 104 (28.6) | 260 (71.4) |
| CART-defined CAN | 73 (20.1) | 291 (79.9) |
Table 5 summarizes the distribution of orthostatic intolerance symptoms among 364 participants as measured by the COMPASS-31 questionnaire. Among the COMPASS-31 orthostatic intolerance items, 260 participants 71.4% reported symptoms on standing. Among those reporting symptoms, 46.2% reported them rarely, 34.2% occasionally, 17.3% frequently, and 2.3% almost always. Most participants described their symptoms as mild 78.5%, while 19.2% reported moderate symptoms and 2.3% reported severe symptoms. Internal consistency of the orthostatic intolerance domain was good (Cronbach’s alpha = 0.82).
Table 5.
Frequency and percentage of the reported components for Orthostatic Intolerance from the COMPASS-31 questionnaire
| COMPASS-31 components | Frequency (N) | Percent (%) | |
|---|---|---|---|
| Orthostatic symptoms on standing | |||
| Yes | 260 | 71.4 | |
| No | 104 | 28.6 | |
| Symptom frequency | |||
| Rarely | 120 | 46.2 | |
| Occasionally | 89 | 34.2 | |
| Frequently | 45 | 17.3 | |
| Almost always | 6 | 2.3 | |
| Symptom severity | |||
| Mild | 204 | 78.5 | |
| Moderate | 50 | 19.2 | |
| Severe | 6 | 2.3 | |
| Symptom experiences over the past year | |||
| Completely gone | 110 | 42.0 | |
| Gotten much better | 94 | 36.0 | |
| Gotten somewhat better | 28 | 11.0 | |
| Stayed about the same | 22 | 8.0 | |
| Gotten somewhat worse | 4 | 2.0 | |
| Gotten much worse | 2 | 1.0 | |
The diagnostic performance of the COMPASS-31 orthostatic intolerance domain compared with CART-defined cardiovascular autonomic neuropathy is presented in Table 6. The COMPASS-31 domain demonstrated a sensitivity of 85.9% and specificity of 86.3%, with a positive predictive value of 96.2% and a negative predictive value of 60.6%, resulting in an overall diagnostic accuracy of 86.0%.
Table 6.
Diagnostic Comparison of the COMPASS-31 Orthostatic Intolerance Domain Against CART-defined Cardiovascular Autonomic Neuropathy
| CAN (Positive) | CAN (Negative) | Total | |
|---|---|---|---|
| COMPASS-31 (Positive) | 250 (True Positive) | 10 (False Positive) | 260 |
|
COMPASS-31 (Negative) |
41 (False Negative) | 63 (True Negative) | 104 |
| Total | 291 | 73 | 364 |
Kappa (κ) = 0.62 − Substantial agreement
Spearman’s correlation analysis showed weak associations between individual COMPASS-31 items and analyser findings (Table 7). Only the symptom progression item showed a weak but statistically significant positive correlation (r = 0.113, p = 0.040). In ROC analyses, individual questionnaire components showed poor discriminative ability, with AUCs ranging from 0.51 to 0.56 (Fig. 2).
Table 7.
Spearman Correlation and ROC Analysis of COMPASS-31 Orthostatic Intolerance Components Against CART-defined Cardiovascular Autonomic Neuropathy
| COMPASS-31 domain | r | p-value | AUC | SE | (95%; CI) |
|---|---|---|---|---|---|
| Orthostatic intolerance | 0.011 | 0.832 | 0.523 | 0.027 | 0.470–0.577 |
| Orthostatic symptoms on standing | -0.017 | 0.741 | 0.513 | 0.031 | 0.453–0.573 |
| Symptom frequency | 0.067 | 0.196 | 0.547 | 0.028 | 0.491–0.603 |
| Symptom severity | 0.053 | 0.313 | 0.544 | 0.027 | 0.492–0.596 |
| Symptom experiences over the past year | 0.113 | 0.040 | 0.562 | 0.031 | 0.501–0.622 |
Data are presented as correlation coefficients (r), p-values, and area under the receiver operating characteristic curve (AUC) with standard errors (SE) and 95% confidence intervals (CI)
Fig. 2.
ROC curves for COMPASS-31 components against CAN analyser
Discussion
Among adults with T2DM attending a tertiary hospital in Zanzibar, the COMPASS-31 orthostatic intolerance domain showed high concordance with CART-defined cardiovascular autonomic neuropathy, achieving 86.0% classification accuracy as a binary screening measure. Notably, this performance occurred despite weak item-level correlations and poor discrimination, indicating its value as a pragmatic triage tool rather than a diagnostic substitute. Given the strong links between CAN and arrhythmia, silent myocardial ischemia, and excess cardiovascular mortality, these findings highlight the potential of a low-cost, symptom-based approach to support early detection in resource-limited settings where formal autonomic testing is limited.
This study provides evidence from a sub-Saharan African setting, where objective autonomic testing is rarely incorporated into routine diabetes care. To our knowledge, evidence evaluating the diagnostic performance of the COMPASS-31 orthostatic intolerance domain against standardized CARTs in sub-Saharan African populations with T2DM remains limited. However, correlations between individual symptom components and analyser findings were weak, and ROC analyses showed poor item-level discrimination, with AUCs ranging from 0.51 to 0.56.
This apparent discrepancy reflects the difference between agreement and discrimination. Cohen’s kappa evaluates concordance in binary classification, whereas ROC analysis assesses discriminative ability across thresholds. The high prevalence of CAN (79.9%) likely increased agreement while reducing discrimination. In addition, symptom-based measures such as COMPASS-31 may reflect more established rather than early autonomic dysfunction.
The distinction between symptom burden and physiological dysfunction is important when interpreting these results [31]. COMPASS-31 captures patients’ subjective experience of autonomic symptoms, including those occurring on standing, whereas objective autonomic tests detect physiological responses reflecting cardiovascular autonomic dysfunction [20]. These constructs are related but not identical [22]. Some individuals may have physiological autonomic impairment without prominent symptoms [32, 33], while others may report dizziness or light-headedness due to causes unrelated to autonomic dysfunction [34].
Autonomic dysfunction in diabetes may initially affect vagal fibers before producing overt hemodynamic manifestations, which may partly explain why physiological abnormalities can precede clinically recognizable symptoms [35]. This discrepancy may explain why overall classification performance appeared acceptable, whereas item-level correlations remained weak [36].
Autonomic dysfunction reflects complex neurophysiological processes [37] and does not consistently translate into symptom perception [38], while the clinical expression of CAN varies across populations [39].
Our findings align with several validation studies conducted in other regions, where the COMPASS-31 questionnaire demonstrated fair correlations with objective measures of autonomic dysfunction and showed low diagnostic accuracy [23]. However, the magnitude of agreement observed in our study appears slightly higher than that reported in some previous validation studies, which may reflect differences in study populations, disease duration, and autonomic testing protocols.
Recent studies have proposed alternative screening approaches for CAN, such as the ProCVT smart-sheet, which combines clinical and physiological variables [40]. In addition, CAN has been linked to ectopic fat distribution in some populations, although this association appears less consistent in T2DM [41]. These findings highlight the complexity of autonomic dysfunction and the need for context-specific validation of screening tools.
The observed results are broadly consistent with those of C. Greco et al., who reported that COMPASS-31 had fair diagnostic accuracy for CAN [23]. It has been proposed that the COMPASS-31 may serve as a helpful initial screening tool [36]. However, symptom-based questionnaires cannot replace objective autonomic testing, and CARTs remain the reference standard for diagnosing CAN [31]. When used alongside standardized reflex testing, COMPASS-31 may therefore contribute to a more comprehensive assessment of autonomic dysfunction in individuals with T2DM.
According to research by Ruchi Singh et al. [19], those who score poorly on the COMPASS-31 must still be assessed using Ewing’s battery to distinguish between “Early CAN” and “No CAN.” Also, D’Ippolito et al. suggested that integrating COMPASS-31 with CARTs may support a stepwise screening strategy for CAN, in which abnormal findings prompt further autonomic testing, while concordant normal results make CAN unlikely [22].
The relatively weak alignment observed in our setting may also reflect contextual factors. Symptom recognition and reporting can be influenced by language, health literacy, sociocultural interpretation of bodily symptoms, and normalization of chronic dizziness or fatigue. These issues may be especially relevant in low-resource settings and support the need for local validation before widespread implementation of standardized symptom tools. However, formal evaluation of individual symptom components and validation of cultural or linguistic influences on COMPASS-31 responses were not performed.
Moreover, symptoms of orthostatic intolerance may be missed or misattributed to other comorbidities in diabetes [7], reducing the sensitivity of symptom-based tools like COMPASS-31 in detecting early autonomic dysfunction. From a clinical perspective, these findings suggest that the COMPASS-31 orthostatic intolerance domain may serve as a practical first-line screening tool to identify individuals who may benefit from further cardiovascular autonomic evaluation using standardized reflex testing.
The findings from this study underscore the need for further refinement and contextual adaptation of autonomic symptom assessment tools like the COMPASS-31 for use in sub-Saharan African settings. Previous studies have also demonstrated that cardiovascular autonomic reflex test abnormalities may not consistently correlate with symptom severity, highlighting the complex relationship between patient-reported symptoms and physiological autonomic impairment [42, 43].
This study has several strengths. It provides data from an underrepresented Zanzibar setting, applies both symptom-based and objective assessment, and evaluates diagnostic agreement using multiple complementary measures. In addition, the study employed a standardized battery of CARTs using an automated analyser, which minimized operator-dependent variability in autonomic measurements.
However, several limitations should be considered. First, the single tertiary referral setting may limit generalizability and overestimate disease burden due to referral bias. Second, the analysis was restricted to the orthostatic intolerance domain, without assessing its relationship with the total COMPASS-31 score. Third, although standardized CARTs were used, the orthostatic intolerance domain captures only one dimension of autonomic dysfunction.
In addition, the high prevalence of hypertension and overweight/obesity in the study population may have influenced autonomic function measures, and stratified diagnostic accuracy across these clinical subgroups was not performed. Finally, self-reported symptoms may have introduced reporting bias and misclassification, reflected in the observed false-positive and false-negative results. Furthermore, the cross-sectional design precludes evaluation of the temporal relationship between symptom development and physiological autonomic dysfunction.
Future studies should assess the performance of the total COMPASS-31 score, examine optimal locally relevant cutoffs, and evaluate whether cultural or linguistic adaptation improves performance. Prospective studies incorporating broader autonomic reflex testing may further clarify the role of COMPASS-31 in screening strategies for diabetic autonomic neuropathy in resource-limited settings.
Clinical implications
The findings of this study have important clinical implications for diabetes care in resource-limited settings. In many regions of sub-Saharan Africa, routine cardiovascular autonomic testing is rarely available in clinical practice. A simple symptom-based tool such as the COMPASS-31 orthostatic intolerance domain may therefore provide a practical first-line screening approach to identify individuals who may benefit from further cardiovascular autonomic evaluation. Integrating symptom-based screening with targeted autonomic testing could help improve early detection of CAN and facilitate timely risk stratification in people with T2DM.
Conclusion
This study demonstrates that the COMPASS-31 orthostatic intolerance domain showed substantial agreement and useful screening performance against CART-defined cardiovascular autonomic neuropathy. These findings support the use of COMPASS-31 as a practical symptom-based screening adjunct to prioritize patients for further objective autonomic testing in settings where CARTs are limited. Further studies should evaluate the full COMPASS-31 instrument, determine optimal screening thresholds, and explore its role within integrated screening strategies for CAN in individuals with T2DM.
Acknowledgements
We would like to sincerely acknowledge The State University of Zanzibar (SUZA) for providing institutional and administrative support for this study. We are grateful to Mnazi Mmoja Hospital (MMH), Zanzibar, for granting permission to conduct the research and for facilitating access to study participants and clinical support during data collection. We also appreciate Mayo Clinic for providing training in autonomic function testing, which strengthened the methodological rigor of this work.
Abbreviations
- CAN
Cardiac Autonomic Neuropathy
- COMPASS-31
Composite Autonomic Symptom Score
- OI
Orthostatic Intolerance
- MMH
Mnazi Mmoja Hospital
- T2DM
Type 2 Diabetes Mellitus
- ROC
Receiver Operating Characteristic
- AUC
Area under the curve
Author contributions
HTH and FLM conceived the study, HTH led patient recruitment, oversaw data collection and analysis, and drafted the manuscript. RMA and AGK contributed to study design, participated in data collection and analysis, and were involved in manuscript preparation. MN, KR and FLM reviewed the final manuscript and contributed to the discussion. All authors have reviewed and approved the final version of the manuscript.
Funding
The authors received no specific funding for this work.
Data availability
The data used to support the findings of this study are available from the corresponding author upon request.
Declarations
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Fisher VL, Tahrani AA. Cardiac autonomic neuropathy in patients with diabetes mellitus: current perspectives. Diabetes, metabolic syndrome and obesity: targets and therapy. 2017:419 – 34. [DOI] [PMC free article] [PubMed]
- 2.Brown P. Diabetes Distilled: Cardiovascular autonomic neuropathy–prevention, identification and management. Diabetes Prim Care. 2024;26:227–8. [Google Scholar]
- 3.Eleftheriadou A, Spallone V, Tahrani AA, Alam U. Cardiovascular autonomic neuropathy in diabetes: an update with a focus on management. Diabetologia. 2024:1–15. [DOI] [PMC free article] [PubMed]
- 4.Duque A, Mediano MFF, De Lorenzo A, Rodrigues LF Jr. Cardiovascular autonomic neuropathy in diabetes: Pathophysiology, clinical assessment and implications. World J diabetes. 2021;12(6):855. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Vinik AI, Maser RE, Mitchell BD, Freeman R. Diabetic autonomic neuropathy. Diabetes Care. 2003;26(5):1553–79. [DOI] [PubMed] [Google Scholar]
- 6.AlOlaiwi LA, AlHarbi TJ, Tourkmani AM. Prevalence of cardiovascular autonomic neuropathy and gastroparesis symptoms among patients with type 2 diabetes who attend a primary health care center. PLoS ONE. 2018;13(12):e0209500. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Pop-Busui R, Boulton AJ, Feldman EL, Bril V, Freeman R, Malik RA, et al. Diabetic neuropathy: a position statement by the American Diabetes Association. Diabetes Care. 2016;40(1):136. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Valensi P, Paries J, Attali J, for Research FG. Cardiac autonomic neuropathy in diabetic patients: influence of diabetes duration, obesity, and microangiopathic complications—the French multicenter study. Metabolism. 2003;52(7):815–20. [DOI] [PubMed] [Google Scholar]
- 9.Eze C, Onwuekwe I, Ogunniyi A. The frequency and pattern of cardiac autonomic neuropathy (CAN) in type 2 dm patients in a diabetic clinic in Enugu south-east Nigeria. Niger J Med. 2013;22(1):24–31. [PubMed] [Google Scholar]
- 10.Voulgari C, Psallas M, Kokkinos A, Argiana V, Katsilambros N, Tentolouris N. The association between cardiac autonomic neuropathy with metabolic and other factors in subjects with type 1 and type 2 diabetes. J Diabetes Complicat. 2011;25(3):159–67. [DOI] [PubMed] [Google Scholar]
- 11.Tahrani AA, Dubb K, Raymond NT, Begum S, Altaf QA, Sadiqi H, et al. Cardiac autonomic neuropathy predicts renal function decline in patients with type 2 diabetes: a cohort study. Diabetologia. 2014;57:1249–56. [DOI] [PubMed] [Google Scholar]
- 12.Chen H, Hwu C, Kuo B, Chiang S, Kwok C, Lee S, et al. Abnormal cardiovascular reflex tests are predictors of mortality in type 2 diabetes mellitus. Diabet Med. 2001;18(4):268–73. [DOI] [PubMed] [Google Scholar]
- 13.Pappachan J, Sebastian J, Bino B, Jayaprakash K, Vijayakumar K, Sujathan P, et al. Cardiac autonomic neuropathy in diabetes mellitus: prevalence, risk factors and utility of corrected QT interval in the ECG for its diagnosis. Postgrad Med J. 2008;84(990):205–10. [DOI] [PubMed] [Google Scholar]
- 14.Ayad F, Belhadj M, Pariés J, Attali J, Valensi P. Association between cardiac autonomic neuropathy and hypertension and its potential influence on diabetic complications. Diabet Med. 2010;27(7):804–11. [DOI] [PubMed] [Google Scholar]
- 15.Memon A. Cardiac autonomic neuropathy in type 2 diabetes mellitus using Bellavere’s score system. Int J health Sci. 2017;11(5):26. [PMC free article] [PubMed] [Google Scholar]
- 16.Kempler P, Tesfaye S, Chaturvedi N, Stevens LK, Webb DJ, Eaton S, et al. Autonomic neuropathy is associated with increased cardiovascular risk factors: the EURODIAB IDDM Complications Study. Diabet Med. 2002;19(11):900–9. [DOI] [PubMed] [Google Scholar]
- 17.Vinik AI, Ziegler D. Diabetic cardiovascular autonomic neuropathy. Circulation. 2007;115(3):387–97. [DOI] [PubMed] [Google Scholar]
- 18.Spallone V, Ziegler D, Freeman R, Bernardi L, Frontoni S, Pop-Busui R, et al. Cardiovascular autonomic neuropathy in diabetes: clinical impact, assessment, diagnosis, and management. Diab/Metab Res Rev. 2011;27(7):639–53. [DOI] [PubMed] [Google Scholar]
- 19.Singh R, Arbaz M, Rai NK, Joshi R. Diagnostic accuracy of composite autonomic symptom scale 31 (COMPASS-31) in early detection of autonomic dysfunction in type 2 diabetes mellitus. Diabetes, metabolic syndrome and obesity: targets and therapy. 2019:1735–42. [DOI] [PMC free article] [PubMed]
- 20.Sletten DM, Suarez GA, Low PA, Mandrekar J, Singer W, editors. COMPASS 31: a refined and abbreviated composite autonomic symptom score. Mayo Clinic Proceedings; 2012: Elsevier. [DOI] [PMC free article] [PubMed]
- 21.Treister R, O’Neil K, Downs HM, Oaklander AL. Validation of the composite autonomic symptom scale 31 (COMPASS-31) in patients with and without small fiber polyneuropathy. Eur J Neurol. 2015;22(7):1124–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.D’Ippolito I, Menduni M, D’Amato C, Andreadi A, Lauro D, Spallone V. Does the relationship of the autonomic symptoms questionnaire COMPASS 31 with cardiovascular autonomic tests differ between type 1 and type 2 diabetes mellitus? Diabetes Metabolism J. 2024;48(6):1114–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Greco C, Di Gennaro F, D’amato C, Morganti R, Corradini D, Sun A, et al. Validation of the Composite Autonomic Symptom Score 31 (COMPASS 31) for the assessment of symptoms of autonomic neuropathy in people with diabetes. Diabet Med. 2017;34(6):834–8. [DOI] [PubMed] [Google Scholar]
- 24.Zhang Z, Ma Y, Fu L, Li L, Liu J, Peng H, et al. Combination of composite autonomic symptom score 31 and heart rate variability for diagnosis of cardiovascular autonomic neuropathy in people with type 2 diabetes. J Diabetes Res. 2020;2020(1):5316769. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Haji HT, Ebrahim A, Khamis AG, Ali RM, Ramaiya K, Mashili FL. Associations of oral hypoglycemic use, fruit intake, and diabetes duration with gastrointestinal autonomic dysfunction in type 2 diabetes patients in Zanzibar. Sci Rep. 2025;15(1):41643. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Muntner P, Whelton PK, Woodward M, Carey RM. A comparison of the 2017 American College of Cardiology/American Heart Association blood pressure guideline and the 2017 American Diabetes Association diabetes and hypertension position statement for US adults with diabetes. Diabetes Care. 2018;41(11):2322–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Cleland CL, Hunter RF, Kee F, Cupples ME, Sallis JF, Tully MA. Validity of the global physical activity questionnaire (GPAQ) in assessing levels and change in moderate-vigorous physical activity and sedentary behaviour. BMC Public Health. 2014;14:1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Stelmach M. Physical activity assessment tools in monitoring physical activity: the Global Physical Activity Questionnaire (GPAQ), the International Physical Activity Questionnaire (IPAQ) or accelerometers–choosing the best tools. Health Probl Civiliz. 2018;12(1):57–63. [Google Scholar]
- 29.Bellavere F, Bosello G, Fedele D, Cardone C, Ferri M. Diagnosis and management of diabetic autonomic neuropathy. Br Med J (Clinical Res ed). 1983;287(6384):61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Migisha R, Agaba DC, Katamba G, Kwaga T, Tumwesigye R, Miranda SL, et al. Prevalence and correlates of cardiovascular autonomic neuropathy among patients with diabetes in Uganda: a hospital-based cross-sectional study. Global Heart. 2020;15(1):21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Novak P, Systrom DM, Marciano SP, Knief A, Felsenstein D, Giannetti MP, et al. Mismatch between subjective and objective dysautonomia. Sci Rep. 2024;14(1):2513. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Freeman R, Illigens BM, Lapusca R, Campagnolo M, Abuzinadah AR, Bonyhay I, et al. Symptom recognition is impaired in patients with orthostatic hypotension. Hypertension. 2020;75(5):1325–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Wieling W, Kaufmann H, Claydon VE, van Wijnen VK, Harms MP, Juraschek SP, et al. Diagnosis and treatment of orthostatic hypotension. Lancet Neurol. 2022;21(8):735–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Lei LY, Chew DS, Raj SR. Differential diagnosis of orthostatic hypotension. Auton Neurosci. 2020;228:102713. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Balcıoğlu AS, Müderrisoğlu H. Diabetes and cardiac autonomic neuropathy: clinical manifestations, cardiovascular consequences, diagnosis and treatment. World J diabetes. 2015;6(1):80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Singh R, Rai N, Arbaz M, Joshi R, Bharashankar R. F158. Diagnostic accuracy of composite autonomic symptom scale 31 (COMPASS-31) in early detection of autonomic dysfunction in type 2 diabetes mellitus. Clin Neurophysiol. 2018;129:e127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Varzideh F, Jankauskas SS, Mone P, Kansakar U, Santulli G. Autonomic neurotransmission in cardiovascular regulation and pathophysiology. Front NeuroSci. 2026;19:1739330. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Arshad MF, Walkinshaw E, Solomon AL, Bernjak A, Rombach I, Leelarathna L, et al. Diabetic autonomic neuropathy does not impede improvement in hypoglycaemia awareness in adults: Sub-study results from the HypoCOMPaSS trial. Diabet Med. 2024;41(9):e15340. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Davis TM, Tan E, Davis WA. Prevalence and prognostic significance of cardiac autonomic neuropathy in community-based people with type 2 diabetes: the Fremantle Diabetes Study Phase II. Cardiovasc Diabetol. 2024;23(1):102. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Bitsch Poulsen M, Julu P, Røikjer J, Drewes AM, Brock C. The ProCVT smart-sheet as a new screening tool for cardiovascular autonomic neuropathy: a feasibility study. Front Endocrinol. 2025;16:1653881. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Risi R, Amendolara R, Pantano AL, Fassino V, D’Onofrio L, Coraggio L, et al. Cardiac autonomic neuropathy is associated with ectopic fat distribution in autoimmune but not in type 2 diabetes. Cardiovasc Diabetol. 2025;24(1):74. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Spallone V, Morganti R, Fedele T, D’Amato C, Maiello MR. Reappraisal of the diagnostic role of orthostatic hypotension in diabetes. Clin Auton Res. 2009;19:58–64. [DOI] [PubMed] [Google Scholar]
- 43.Low PA, Benrud-Larson LM, Sletten DM, Opfer-Gehrking TL, Weigand SD, O’Brien PC, et al. Autonomic symptoms and diabetic neuropathy: a population-based study. Diabetes Care. 2004;27(12):2942–7. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used to support the findings of this study are available from the corresponding author upon request.


