Systematic screening for age‐related comorbidities: Health care optimization among persons with HIV in an outpatient setting

Abstract

Background

Age‐related comorbidities occur earlier and more frequently in people with HIV (PWH) than in the general population and have emerged as a key challenge in long‐term HIV care. Unfortunately, many of these conditions remain undiagnosed, and systematic screening in clinical practice remains limited. Therefore, we aimed to assess the burden of unrecognized age‐related comorbidities in a clinical outpatient setting.

Methods

This cross‐sectional cohort study was conducted from November 2023 to March 2025 at the HIV outpatient clinic, Copenhagen University Hospital, Rigshospitalet. A structured screening procedure was implemented to assess unrecognized comorbidities among PWH aged ≥60 years. The screening comprised multiple guideline‐recommended risk evaluations, including 10‐year cardiovascular risk score (SCORE2), 10‐year fracture risk assessment (FRAX), assessment of chronic lung disease and frailty.

Results

A total of 387/532 (72.7%) eligible patients participated. Of patients without a history of cardiovascular disease, 203/300 (67.6%) were categorized as high risk and 57/300 (19%) as very‐high risk by SCORE2. Primary preventive lipid‐lowering therapy was prescribed in 75/203 (36.9%) and 18/57 (31.6%) in the high‐risk and very‐high risk groups, respectively. Of participants without prior chronic lung disease, 29/324 (9%) reported symptoms, and 20/260 (7.7%) with available spirometry had airflow limitation. Among PWH without a history of osteoporosis, 127/335 (37.9%) were categorized as high risk of major fracture and/or hip fracture. Pre‐frailty or frailty was identified in 88/387 (22.7%) patients.

Conclusion

The considerable burden of unrecognized age‐related comorbidities in PWH ≥60 years of age highlights the need for a systematic approach to early detection and preventative management.

INTRODUCTION

With the success of antiretroviral therapy (ART), people with HIV (PWH) are increasingly reaching older age. Age‐related comorbidities occur earlier and more frequently in PWH than in the general population, contributing to prolonged exposure to chronic conditions. Consequently, age‐related comorbidities have emerged as a key challenge in long‐term HIV care [1, 2, 3].

Cardiovascular disease (CVD) remains a leading cause of morbidity among PWH, with an estimated two‐fold higher overall risk and a three‐fold higher risk of subclinical coronary artery disease compared with the general population [4, 5]. This elevated risk likely reflects a combination of a higher prevalence of traditional CVD risk factors and HIV‐specific factors such as chronic inflammation and dyslipidaemia [6]. Recently, the Randomized Trial To Prevent Vascular Events in HIV (REPRIEVE) demonstrated that the use of pitavastatin significantly reduced the incidence of major cardiovascular events in PWH with low–moderate traditional CVD risk, underscoring the benefits of proactive preventive management [7]. Consequently, early identification and treatment of CVD risk factors, along with the implementation of preventative strategies, are essential to mitigate the overall disease burden, and further research on implementation strategies in routine clinical care is warranted [8].

Other age‐related comorbidities, including chronic lung disease (CLD), osteoporosis and diabetes, substantially contribute to the overall disease burden among PWH [9, 10, 11]. Recent evidence has identified HIV as an independent risk factor for CLD and chronic obstructive pulmonary disease (COPD), as well as accelerated lung function decline [12, 13, 14]. Similarly, osteoporosis and diabetes appear to be influenced by both HIV‐specific factors and traditional risk factors [15, 16].

Collectively, the accumulation of multiple comorbidities may contribute to functional decline and vulnerability among people ageing with HIV.

Frailty represents a related but distinct multidimensional syndrome that reflects reduced physiological reserve and is associated with an increased risk of hospitalization and death in PWH [17]. Assessing frailty may therefore provide additional insight into the broader picture of health and fitness among PWH.

Due to the higher burden of comorbidities among PWH [10, 18], the European AIDS Clinical Society (EACS) recommends that screening for age‐related comorbidity be included in clinical practice [8, 19]. In Denmark, HIV care is largely centralized in specialized infectious disease clinics, where patients are followed regularly for ART and general health monitoring. Responsibility for screening and management of non‐AIDS age‐related diseases may, however, be shared with primary care and other specialties. In this context, the primary aim of the present study was to evaluate the implementation and yield of a systematic screening for age‐related comorbidities in a clinical setting.

MATERIALS AND METHODS

The study was designed as a cross‐sectional cohort study conducted as a quality improvement initiative from November 1st, 2023, to March 31st, 2025.

Participants

Eligible patients were PWH aged 60 years or older by July 1st, 2024, affiliated with the out‐patient clinic at the Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet. Patients were identified via the electronic health record and patient management system Sundhedsplatformen (Epic), used in the Capital Region of Denmark, according to HIV‐related International Classification of Diseases, 10th edition (ICD‐10) codes [20].

Patients were primarily offered screening when they were attending the department for a routine annual visit; those who could not be reached in person were contacted by phone and offered the opportunity to participate at a more suitable time.

Screening procedures

The screening included assessment of CVD risk, including hypertension and eligibility for primary prevention lipid‐lowering therapy (LLT), CLD, osteoporosis, diabetes and frailty. Information on prior medical history and current medication was obtained from electronic medical records and participant self‐report during the screening visit. Information on lifestyle‐related factors, including current and previous tobacco use, was self‐reported (questionnaire is shown in supplementary). All screening assessments were conducted during in‐person screening visits in the outpatient clinic. Telephone contact was used only for logistical purposes, such as scheduling visits. A previously unrecognized comorbidity required all of the following: (1) absence of relevant diagnostic codes, (2) no documentation of the comorbidity in the electronic patient record, (3) that the participant did not receive pharmacological treatment for the comorbidity and (4) that the comorbidity had not been reported by the participant in the questionnaire.

Baseline comorbidities

CVD

History of atherosclerotic CVD was defined according to European Society of Cardiology (ESC) guidelines and included documented history of ischemic heart disease (e.g., myocardial infarction, angina or prior revascularization) cerebrovascular disease (ischemic stroke or transient ischemic attack) or peripheral arterial disease (claudication, prior peripheral revascularization or amputation or aortic aneurysm) [21]. Hypertension was defined by relevant diagnostic codes or current use of antihypertensive medication, and use of LLT was classified according to indication, distinguishing between established CVD and primary prevention.

CLD

History of CLD was defined by the presence of relevant diagnostic codes (including COPD, asthma, interstitial lung disease or bronchiectasis), records of previous spirometry with obstructive lung disease with forced expiratory volume in 1 s (FEV1) <80% of predicted value and FEV1/forced vital capacity (FVC) ratio <0.70, or the use of lung‐specific inhalation medicine [22].

Osteoporosis

History of osteoporosis was defined according to World Health Organization (WHO) guidelines as a history of a low‐energy fracture, current or past treatment with an antiosteoporosis drug and/or previous dual energy X‐ray absorptiometry (DXA) scan with a bone mass density (BMD) T‐score at the femoral neck or spine of 2.5 standard deviations below the mean value [23].

Diabetes

History of diabetes was defined according to the ESC and European Association for the Study of Diabetes (EASD) guidelines and included the presence of relevant diagnosis codes, current or previous treatment with an antidiabetic drug or a previously recorded blood HbA1c ≥48 mmol/mol [24].

Physical examination

Systolic and diastolic blood pressure (BP) was measured twice electronically with the participant in a relaxed seated position. Spirometry was performed using the EasyOne® ultrasonic spirometer in accordance with American Thoracic Society/European Respiratory Society guidelines, except that participants were standing in an upright position without the use of a nose clip [25]. We assessed the following variables: FEV1, FVC and FEV1/FVC ratio. Predicted values were calculated based on age, gender, ethnicity, height and weight according to international standards [26]. Body mass index (BMI) was calculated as weight (kg)/height (m)² and categorized according to the World Health Organization (WHO) definition [27].

Outcome variables

Outcomes were defined as follows: The 10‐year risk of fatal or non‐fatal cardiovascular event was estimated using the Systematic Coronary Risk Evaluation 2 (SCORE2) algorithm in accordance with ESC guidelines, based on age, sex, smoking status, systolic BP and non‐high‐density lipoprotein cholesterol (non‐HDL‐C) measured up to six months prior to screening. SCORE2 was categorized as low‐moderate risk, high risk and very‐high risk using distinct age‐specific thresholds. Patients with established CVD or isolated cardiovascular risk factors (e.g. diabetes) were categorized as high risk or very‐high risk according to guideline‐defined thresholds [21].

Hypertension was defined as systolic BP >140 mmHg or diastolic BP >90 mmHg (yes/no) [28].

Primary prevention LLT recommendation was coded as yes/no. A “yes” indicated that LLT was recommended according to the EACS guidelines for all patients in the high‐ or very‐high CVD risk category [19]. Achievement of low‐density lipoprotein cholesterol (LDL‐C) targets among patients receiving LLT at the time of screening was coded as yes/no. For individuals at low–moderate risk, the LDL‐C treatment target was ≤2.6 mmol/L, ≤1.8 mmol/L for those at high risk and ≤1.4 mmol/L for very‐high risk [19].

Screening for chronic respiratory symptoms was based on symptom‐related questions adapted from the EACS guidelines, including the presence of exertional dyspnoea, chronic cough and wheezing (yes/no) [19]. Spirometry results were categorized based on guideline‐defined thresholds: airflow obstruction was present if FEV1/FVC was <0.7. Airflow limitation was present if FEV1 was <80% of the predicted value, combined with the FEV1/FVC ratio <0.7. Patients with recent (<2 weeks) respiratory infection symptoms were excluded from testing.

The fracture risk prediction tool (FRAX) version 1.4.7 was used for quantifying the 10‐year risk of major osteoporotic fracture (hip, spine, wrist or humerus) and hip fracture [29]. The femoral neck T‐score was included in the calculation for patients with available BMD data no older than 5 years on the day of screening. Osteoporosis risk was defined as high (yes/no) if the FRAX‐score ≥20% for major osteoporotic fractures and/or ≥3% for hip fractures, according to EACS guidelines [19].

Diabetes was considered present if HbA1c ≥48 mmol/mol.

Frailty was assessed using the FRAIL Scale, including five components: fatigue, resistance (difficulty of climbing stairs), ambulation, number of comorbid illnesses and unintentional weight loss. Frailty was defined as a score ≥3, pre‐frailty as a score of 1–2 and fitness as a score of 0 [19].

After the visit, a summary report documenting existing comorbidities and findings, including calculated risk scores, was documented in the electronic medical records and made available for the physician with treatment responsibility. When screening results suggested increased risk or potential unrecognized comorbidities, participants were offered referral to relevant specialists and/or their general practitioner to support further evaluation and linkage to care. All examinations were conducted by the same healthcare professional (AR) to ensure consistency.

Statistical analysis

Continuous variables are presented as mean ± standard deviation (SD) or median with interquartile range (IQR) for normal or non‐normal distribution, respectively. Differences between groups were assessed using the Wilcoxon rank‐sum test. Categorical variables are reported as frequency and percentage and compared using Fisher's exact test. A p‐value <0.05 was considered statistically significant. All analyses were conducted using R version 4.3.1 [30].

Spirometry was unavailable for 64 (19.7%) participants. All analyses involving spirometry were therefore conducted among participants who completed the test. To assess potential bias related to non‐participation in spirometry, a sensitivity analysis comparing smoking exposure (status and package years) between participants and non‐participants was performed. Finally, to assess potential selection bias for the overall study, age and sex were compared between participants and individuals who declined screening participation but did not opt out of clinical quality projects.

Use of artificial intelligence

A large language model tool (OpenAI) was used to assist in the generation of specific R code based on a predefined statistical analysis plan. All analytical decisions, variable definitions, statistical models and interpretation of results were entirely determined by the authors.

RESULTS

Of 532 PWH eligible for screening, 387 (72.7%) participated and were included in the analyses (Figure 1). Clinical characteristics of participants are shown in Table 1. Median age was 66.2 years. The majority were male (86%), and all were currently receiving ART.

FIGURE 1.

Consort diagram of study inclusion and exclusion. Flow chart illustrating patient inclusion and participation in the structured screening initiative for age‐related comorbidities among people with HIV in the outpatient department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet. Of the total number of patients attending the outpatient clinic during the study period, individuals were included based on predefined eligibility criteria. Patients were excluded due to a lack of consent in alignment with Danish national health regulations governing the collection and sharing of health information. PWH, people with HIV.

TABLE 1.

Baseline characteristics of 387 PWH and relevant comorbidities.

Baseline characteristics	n = 387
Age, median (IQR)	66.2 (62.5–72.0)
Age 60–69, n (%)	262 (67.7)
Age 70–79, n (%)	105 (27.1)
Age > 80, n (%)	20 (5.2)
Sex (male), n (%)	333 (86)
Smoking status, n (%)
Current	81 (20.9)
Previous	160 (41.3)
Never	146 (37.7)
Package years, median (IQR)	25 (14.2–40)
BMI (kg/m2), mean (SD)	25.2 (±4.2)
Underweight, n (%)	13 (3.4)
Normal, n (%)	192 (49.6)
Overweight, n (%)	137 (35.4)
Obese, n (%)	45 (11.6)
History of cardiovascular disease	87 (22.5)
Current antihypertensive treatment	160 (41.3)
Current lipid‐lowering therapy, primary prevention	106 (35.3)
History of Chronic lung disease (yes), n (%)	63 (16.3)
COPD	39 (10.1)
Asthma	21 (5.4)
Other chronic lung disease	3 (0.8)
History osteoporosis	52 (13.4)
History of diabetes mellitus	33 (8.5)
Current antiretroviral treatment (yes), n (%)	387 (100)
NRTI	368 (95.1)
NNRTI	127 (32.8)
PI	46 (11.9)
INSTI	264 (68.2)
Other	3 (0.8)
PI/r eller PI/c	50 (12.9)
HIV viral load <20 copies/ml, n (%)	367 (94.1)

Note: Continuous variables are presented as medians with interquartile ranges (IQR) and means with standard deviations as appropriate. Categorial variables are presented as counts (n) and percentages (%). Smoking status is self‐reported, and pack‐years are reported among current and former smokers only. BMI categories are based on WHO definitions; underweight (<18.5 kg/m²), normal weight (18.5–24.9 kg/m²), overweight (25.0–29.9 kg/m²) and obese (≥30 kg/m²). Cardiovascular disease includes a history of ischemic heart disease, cerebrovascular disease or peripheral arterial disease. Primary prevention refers to lipid‐lowering therapy among participants without known cardiovascular disease. Chronic lung disease includes COPD, asthma, interstitial lung disease or bronchiectasis.

Abbreviations: BMI, body mass index; COPD; chronic pulmonary obstructive disease; INSTI, integrase strand transfer inhibitor; NNRTI, non‐nucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; PI, protease inhibitor.

Non‐participants were older than participants (69 vs. 66.2 years p‐value >0.001), whereas sex distribution was similar between the groups (p‐value = 0.92).

Prevalence of known age‐related comorbidities at the time of screening

A total of 155/387 (40.1%) participants had no prior history of any of the investigated comorbidities. Among those with one or more known comorbidities, hypertension was the most common (160/387 (41.3%)), followed by a history of CVD, reported in 87/387 (22.5%) participants (Table 2).

TABLE 2.

Prevalence of comorbidities, risk factors, frailty and preventative care measures identified through screening among participants without prior history of each specific condition.

	Persons at risk	Screening outcome
Cardiovascular risk (SCORE2), n (%)	300
Low‐moderate risk		40 (13.3)
High risk		203 (67.6)
Very‐high risk		57 (19.0)
SCORE2 percentage, median (IQR)		8.0 (6.0–11.0)
Hypertension, n (%)	227
Systolic BP >140 mmHg (yes)		81 (35.7)
Diastolic BP > 90 mmHg (yes)		53 (23.3)
Elevated BP (systolic and/or diastolic)		93 (41)
Chronic lung disease, n (%)	324
Self‐reported symptoms		29 (9.0)
Declined/unable to perform spirometry		64 (19.8)
Spirometry available	260
Self‐reported symptoms		27 (10.4)
FEV1 <80%		55 (21.2)
FEV1/FVC <0.7		36 (13.8)
FEV1 <80% and FEV/FVC <0.7		20 (7.7)
FEV1 <80% and/or FEV1/FVC <0.7		71 (27.3)
Bone disease, n (%)	335
FRAX major fracture risk ≥20%		14 (4.2)
FRAX hip fracture risk ≥3%		116 (34.6)
Elevated fracture risk (major fracture and/or hip fracture)		127 (37.9)
PWH with no DXA in the last 5 years	240
FRAX major fracture risk ≥20%		6 (2.5)
FRAX hip fracture risk ≥3%		87 (36.2)
Elevated fracture risk (major fracture and/or fracture)		89 (37.1)
Diabetes, n (%)	354
HbA1c ≥48 mmol/mol (yes)		4 (1.1)
Frailty, n (%)	387
0 (fit)		299 (77.3)
1–2 (pre‐frail)		78 (20.2)
3+ (frail)		10 (2.6)

Note: For each condition, the number of individuals at risk (n) and percentage (%) of positive screening results are provided. Self‐reported respiratory symptoms, along with objective measures including (FEV1 < 80%, FEV1/FVC 0.7, and both criteria), are presented among those completing spirometry. FRAX 10‐year risk thresholds for major osteoporotic fracture (≥20%) and hip fracture (≥3%) are presented among participants with no history of osteoporosis and participants with no osteoporosis and no DXA scan within the last 5 years, respectively.

Abbreviations: BP, blood pressure; CCI, Charlson Comorbidity index; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity.

CVD

Among patients with no prior history of CVD, 40/300 (13.3%) were classified as low–moderate risk, 203/300 (67.7%) as high risk and 57/300 (19%) as very‐high risk. In the low–moderate risk group, 12/40 (30%) participants received LLT, 76/203 (37.4%) in the high‐risk group and 18/57 (31.6%) in the very‐high risk group received LLT. The proportion of participants who met the LDL‐C targets specified for their respective SCORE2 risk categories was 8/12 (66.7%) in the low–moderate risk category, 20/76 (26.3%) in the high‐risk category and 1/18 (5.6%) in the very‐high risk category (Figure 2).

FIGURE 2.

Use of lipid‐lowering therapy among 300 participants without cardiovascular disease, stratified by the SCORE2 risk category. Pie chart illustrating proportion of patients (n (%)) receiving lipid‐lowering therapy (inner circle) across three cardiovascular risk categories. Risk categories are defined by the SCORE2 algorithm: Low–moderate risk, high risk and very‐high risk using distinct thresholds based on age: Low to moderate risk (<5% in the 50–69 age group, and <7.5% in the ≥70 age group); high risk (5–10% in the 50–69 age group, 7.5–15% in the ≥70 age group); very high risk (≥10% in the 50–69 age group, ≥15% in the ≥70 age group). Participants included in this figure had no prior history of cardiovascular disease and were therefore considered eligible for primary prevention.

Among individuals not currently treated with antihypertensive medication, 93/227 (41%) had elevated systolic and/or diastolic BP including 81/227 (35.7%) with systolic BP ≥140 mmHg and 53/227 (23.3%) with diastolic BP ≥90 mmHg.

CLD

A total of 63/387 (16.3%) PWH had known CLD at the time of screening. Among those with no history of CLD, 29/324 (9%) reported symptoms of CLD, and 64 (19.8%) either declined or were unable to participate in spirometry testing.

Among participants who had no history of CLD and underwent spirometry (n = 260), 27/260 (10.4%) reported symptoms at the time of screening, including persistent cough 18/260 (6.9%), shortness of breath 14/260 (5.4%) and/or wheezing 3/260 (1.2%). A total of 55/260 (21.1%) had FEV1 below 80% of the predicted value, 36/260 (13.8%) had a FEV1/FVC ratio below 0.7 and both criteria were met in 20/260 (7.7%) participants (Table 2 and Figure 3).

FIGURE 3.

Flow of participants through chronic lung disease screening and spirometry assessment. Flow diagram illustrating process of screening for chronic lung disease. The figure displays the number of participants with known chronic lung disease at baseline, the number who declined or were unable to undergo spirometry and the number who reported respiratory symptoms according to spirometry results. Abbreviations: CLD, chronic lung disease; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; airflow obstruction = FEV1/FVC <0.7; airflow limitation = FEV1 <80% of predicted value and FEV1/FVC <0.7; PWH, people with HIV.

Among the 20 participants with suspected airflow limitation, 8 (40%) had reported one or more symptoms of CLD based on the screening questionnaire. Conversely, among the 27/260 participants who reported symptoms of CLD, 8/27 (29.6%) had spirometry results consistent with airflow limitation and 15/27 (55.5%) had abnormal spirometry results (Figure 3).

A history of smoking was reported in 29/36 (81%) and 15/20 (75%) participants with suspected airflow obstruction (FEV1/FVC <0.7) and airflow limitation (FEV1 <80% and FEV1/FVC <0.7), respectively.

In the sensitivity analysis, smoking status and cumulative tobacco exposure (pack‐years) did not differ significantly between participants who completed spirometry and those who did not (p‐value = 0.83) and (p‐value = 0.33), respectively.

Osteoporosis

Among 335 participants without a history of osteoporosis, 240/335 (71.6%) had no DXA scan performed within the last 5 years. In this group, the FRAX risk assessment identified 6/240 (2.5%) participants with a major fracture risk ≥20% and 87/240 (36.2%) with a hip fracture risk ≥3% (Table 2).

Diabetes

Among participants without a history of diabetes, 4/354 (1.1%) of the participants had HbA1c values ≥48 mmol/mol.

Frailty assessment

According to the FRAIL Scale, 299 (77.3%) were categorized as fit, 78 (20.2%) as pre‐frail and 10 (2.6%) as frail.

Overall, 267/387 (69%) had at least one previously unrecognized condition or risk factor, including high or very‐high cardiovascular risk without recommended LLT, abnormal spirometry (airflow obstruction or limitation), high fracture risk without recent DXA, newly identified diabetes or elevated BP.

DISCUSSION

In this study, we conducted a structured screening for age‐related comorbidities among PWH aged ≥60 years attending routine outpatient care. The screening revealed a substantial burden of previously unrecognized comorbidities and a considerable proportion of participants at increased risk of developing age‐related comorbid conditions. Our findings highlight systematic screening as an important opportunity for early detection and enhanced prevention, as several participants presented with identifiable risk factors or signs of disease that could benefit from timely intervention.

Most of the study population (≥60 years) without previously established CVD were classified as high risk or very‐high risk of CVD by SCORE2, as the algorithm assigns progressively higher risk estimates with increasing age, even in the absence of modifiable risk factors. According to current EACS guidelines, individuals classified as high or very‐high risk are recommended to receive LLT as primary prevention of CVD; however, fewer than half of eligible patients received LLT, and only a minority achieved recommended LDL‐C targets [19].

Despite the increased clinical focus on primary CVD prevention with LLT among PWH in the post‐REPRIEVE era, our findings indicate that significant gaps in LLT uptake remain. Similar gaps between guideline recommendations and observed LLT use have been reported previously [31]. In line with this, Cottino et al. observed lower LLT use particularly among those without established CVD or markedly elevated LDL‐C levels [32]. The observed treatment gap is likely multifactorial; however, our study does not allow us to clarify the role of patient‐related factors, such as concerns about side effects and pill burden, and clinician‐related factors, including competing clinical priorities and the complexity of managing multiple comorbidities [33, 34].

A total of 41% of participants with no prior history of hypertension had elevated blood pressure at screening. While some of these readings may reflect situational factors such as white‐coat hypertension, even transient elevations are clinically important because they are associated with progression to sustained hypertension and increased cardiovascular risk [35]. The prevalence in our cohort was slightly higher than that observed in the Copenhagen Comorbidity in HIV study (COCOMO), which is another cohort including PWH from our site [11], likely reflecting the older age distribution in our cohort, and also indicating that hypertension remains underdiagnosed among PWH and that systematic blood pressure measurement may allow for early detection and intervention.

Among participants with no prior history of CLD, nearly one‐third had abnormal spirometry results, and 20 (7.7%) were identified with de novo airflow limitation at screening. Interpretation of these results should take the diagnostic approach into account. In this study, airflow limitation was defined using a fixed cutoff FEV1 <80% and the FEV1/FVC ratio < 0.7, and although widely used, fixed thresholds may overestimate prevalence in older adults compared with the lower limit of normal criteria [36], as demonstrated by Ronit et al. [37]. Such discrepancies also help contextualize the clinical patterns observed in our cohort, as we observed a clear mismatch between symptoms and spirometric impairment. Our findings align with multiple cohort studies employing systematic spirometry, which have similarly shown both underrecognition of airflow limitation and limited sensitivity of symptom‐based assessment [37, 38, 39]. Furthermore, both the AGE_hIV and the COCOMO cohorts have shown that PWH experience accelerated lung function decline compared with the general population, suggesting that reliance on symptoms or a normal spirometric assessment at a single time point may miss early disease trajectories [13, 14]. Taken together, these observations have important clinical implications, as current guidelines recommend spirometry only in symptomatic individuals. Underrecognition may delay diagnosis and timely intervention, while systematic screening also carries the risk of overdiagnosis, as the choice of diagnostic criteria may further influence prevalence estimates. Given the high prevalence of undetected airflow limitation and the weak correlation with symptoms, symptom‐based screening alone is likely insufficient for early detection of CLD in PWH, although the optimal approach to systematic spirometric screening remains to be defined.

Approximately one‐third of participants were at high risk of major osteoporotic and/or hip fracture, yet only a minority of participants without a prior diagnosis of osteoporosis had undergone DXA scanning within the last 5 years. Current EACS guidelines recommend DXA screening for all men with HIV >50 years and all postmenopausal women, reflecting the higher risk of osteoporosis in these populations. Limited uptake of DXA screening has been reported across different settings, especially among men [40]. While FRAX can serve as a pragmatic tool to identify individuals who may benefit from targeted DXA, reliance on FRAX alone may miss cases, as studies have shown discrepancies between FRAX scores and DXA findings in aging PWH, partly because FRAX does not account for HIV‐specific factors such as ART exposure [41, 42]. In addition, in this study, some participants had been diagnosed with osteoporosis following prior DXA assessment and were therefore not included in the population at risk, affecting prevalence estimates. Nevertheless, our findings highlight the need for a more systematic approach to the detection of osteoporosis in PWH.

In our cohort, most participants were categorized as fit, while one‐third were identified as pre‐frail, and only a minority were frail. Despite the high burden of comorbidities observed in this cohort, the prevalence of frailty was relatively low. This may indicate that frailty captures a distinct dimension of health related to physiological reserve, which may be preserved in a well‐treated population despite multimorbidity. Findings from the AGE_hIV cohort have shown that pre‐frailty and frailty are more prevalent among PWH independent of traditional risk factors [43], and longitudinal data from the same cohort further demonstrate a higher likelihood of progression to more vulnerable frailty in this population [17, 44]. Furthermore, frailty was assessed using the FRAIL scale as recommended for clinical screening by the EACS guidelines, which may contribute to lower frailty estimates compared to more comprehensive frailty instruments. Although traditional factors explain little of the association with adverse outcomes, recognizing pre‐frailty may still facilitate timely clinical intervention.

Few cases of diabetes were identified during screening. Several cardiometabolic risk factors assessed in screening, including HbA1c and lipid measurements, are already part of routine HIV care, whereas blood pressure measurement is not consistently performed at our clinic. Systematic screening may therefore add value by ensuring structured assessment, interpretation and follow‐up.

In healthcare systems where responsibility for screening and prevention of age‐related comorbidities may be shared between HIV clinics, primary care and other specialties, important aspects of preventive care may risk fragmentation. This is also relevant in the Danish setting, where elements of preventive care are not fully integrated within HIV clinics. Our findings suggest that systematic screening for age‐related comorbidities should be considered an integral component of routine HIV care, particularly in healthcare systems where responsibility for preventive care may otherwise be shared across multiple providers. At the same time, HIV care in Denmark is centralized within specialized hospital‐based clinics and supported by universal access to healthcare. The management of age‐related comorbidities is, however, often shared with primary care and other specialties, facilitated by integrated healthcare systems and shared medical records. This organization may support more consistent follow‐up and earlier detection of comorbidities compared to other healthcare settings, where fragmentation may be more pronounced. These differences should be considered when interpreting the generalizability of our findings.

Strengths and limitations

This study benefits from a well‐defined cohort with systematically collected data and a high participation rate, facilitated by flexible screening in a familiar clinical environment. The findings provide relevant real‐world data that are comparable to similar populations in high‐income countries. A further strength is the integrated Danish healthcare system with shared electronic health records across healthcare sectors, which improved our ability to verify previously documented diagnoses and treatments.

Several limitations should be acknowledged. The relatively low prevalence of pre‐frailty and frailty in our cohort may reflect selection bias, as individuals who declined were older, as demonstrated in the sensitivity analysis. This trend likely extends beyond frailty, as older or more vulnerable individuals may be less inclined to participate in screenings due to concerns about stigma, relevance and acceptability [45].

In addition, the study was conducted at a single HIV clinic and included a moderate sample size with no control group, which may limit the generalizability of prevalence estimates. Healthcare organization and responsibility for treatment and prevention of age‐related comorbidities may vary across settings, and this limitation should be considered when interpreting the applicability of the results.

Future perspectives and implications for clinical practice

Future research should include longitudinal follow‐up to evaluate the clinical impact of systematic screening.

The need for improved prevention strategies is already reflected in recent updates to international guidelines: recent EACS recommendations now advocate broader use of statins for primary CVD prevention and introduce specific LDL‐C targets to guide individualized risk management [8, 46, 47]. These developments illustrate how emerging evidence can rapidly inform clinical recommendations. While CVD prevention has gained increasing attention in recent guidelines, comparable initiatives for bone health and CLD remain limited, and structural and organizational barriers to systematic screening and preventive interventions remain key challenges.

CONCLUSION

Systematic screening identified a substantial proportion of unrecognized comorbidities in PWH ≥60 years of age. Our findings highlight the potential to enhance alignment between guideline recommendations and clinical practice, showing that systematic screening can be an effective method to improve the detection and management of non‐AIDS age‐related comorbidities in PWH.

PATIENT CONSENT STATEMENT

Informed consent was not required according to national regulations for this quality improvement project as data were collected as part of routine clinical care and analysed in an anonymous form. Patients who had declined participation in clinical quality projects were excluded in accordance with national health regulations on the collection and sharing of health information.

PERMISSION TO REPRODUCE MATERIAL FROM OTHER SOURCES

Not applicable. No material from other sources has been reproduced in this manuscript.

FUNDING INFORMATION

This work was supported by Gilead Sciences. The funders had no role in the study design, data collection, analysis, interpretation or manuscript preparation.

CONFLICT OF INTEREST STATEMENT

AKHR: has received honoraria and travel grants from Gilead, GSK and Sanofi, and has served as an advisor for GSK and declares no conflict of interest related to this work. AML: Unrestricted research grants from Novo Nordic Foundation, Sygesikring Danmark, Lundbeck Foundation, Svend Andersen Fonden, Copenhagen University Hospital – Rigshospitalet Research Council, Gilead and Pfizer; honoraria for lectures from Gilead, GSK and Pfizer. Support for travelling and conference participation from Gilead. Advisory boards for Gilead, GSK and Pfizer. SS: declares no conflicts of interest related to this work. OK: Within the last 5 years: Unrestricted research grants from Gilead, honoraria for lectures from Gilead, Merck and ViiV, support for travelling and conference participation from Gilead, Merck and ViiV. No advisory boards since 2019. SDN: Within the last 5 years: Unrestricted research grants from Novo Nordic Foundation, Svend Andersen Fonden, Copenhagen University Hospital – Rigshospitalet Research Council, Augustinus Fonden and Gilead, Honoraria for lectures from Gilead, GSK, Takeda. Support for travelling and conference participation from Gilead. Advisory boards for Gilead, GSK, Takeda.

ETHICS STATEMENT

This study was approved as a quality improvement project by the department and hospital administration. Access to retrieve and analyse data was granted by the Department of Health law and conducted in compliance with data protection regulations. For quality improvement projects, data can only be retrieved up to 5 years back in time, meaning older data were not accessed. All variables and outcomes were collected and stored in REDCap according to guidelines for safe digital data storage.

Supporting information

Data S1.

DATA AVAILABILITY STATEMENT

Data are not publicly available due to legal and ethical restrictions related to patient confidentiality.