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Meta-analysis of dolutegravir-based ART and risk-stratified HIV care in UgandaHIV Treatment Works Better Now, But One Problem Remains

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Key Takeaway
Consider the proposed risk-stratified model for integrated HIV care as an association-based approach, not a proven intervention.

This is a meta-analysis and cohort review of dolutegravir-based antiretroviral therapy (ART) and a proposed risk-stratified model for integrated HIV care. The scope includes people living with HIV in Uganda's The AIDS Support Organization (TASO) routine-care cohort and a regional systematic review and meta-analysis, with sample sizes of 54,348 and 29,829, respectively.

The authors synthesized findings on viral non-suppression (VL >= 1,000 copies/mL). In the TASO cohort, the viral non-suppression rate was 6.4% (2,145/33,384). In the regional meta-analysis, the viral non-suppression rate was 19.4%. Secondary outcomes included advanced HIV disease, tuberculosis co-occurrence, and non-communicable disease co-occurrence.

The authors propose using routine electronic health record signals to trigger rapid follow-up and integrate TB and non-communicable disease management within HIV platforms. However, the source reports associations and does not establish causation for the proposed model. Certainty of evidence is not reported, and follow-up duration was not reported.

Practice relevance is restrained; the proposed model may strengthen durable viral suppression, but it is not proven effective. Limitations were not reported in the source.

The Hidden Gap in HIV Care

In East Africa, HIV is still a major health concern. The region has made huge progress. More people than ever are on treatment. Death rates have dropped. But two problems remain.

First, some patients have what doctors call viral non-suppression. This means the amount of HIV in their blood stays high, even with medication. In the study, 6.4 percent of patients had this problem. That is about 1 in 15 people.

Second, many patients also face other health issues. Tuberculosis (TB) is common. So are non-communicable diseases like high blood pressure and diabetes. These conditions make HIV care more complex.

The old way of thinking was simple. Give patients the best drug, and the virus will go away. But that is not what happens for everyone.

What Changes With This New Approach

The researchers propose something different. Instead of treating every patient the same way, they want to use data to find the people who need extra support.

Think of it like a smoke detector. Right now, doctors wait until a patient misses an appointment or gets very sick. This new model would use electronic health records to spot problems early. It would send an alert when a patient's viral load starts to rise.

The system would then trigger a specific response. The patient would get extra help with taking their medication. They would also get support for other problems, like food insecurity or unstable housing. These social issues often make it harder for people to stay on treatment.

This does not mean the current drugs are failing. It means the system around the drugs needs to be smarter.

How the Numbers Break Down

The study included 54,348 people living with HIV in Uganda. All were part of a large care program called TASO. Most patients were taking integrase inhibitors, the modern class of HIV drugs that includes dolutegravir.

Among those with a recorded viral load test, 6.4 percent had viral non-suppression. That means 2,145 people out of 33,384 tested still had high virus levels.

The researchers also did a broader review of other studies. They looked at data from nearly 30,000 patients across East Africa. In that larger group, the rate of viral non-suppression was 19.4 percent. That is almost 1 in 5 people.

Why the difference? The TASO program in Uganda has strong support systems. Other areas may not have the same resources. This shows that where you get care matters as much as what drug you take.

But There Is a Catch

The new model sounds promising. But it has not been tested yet. The researchers have designed it based on what they learned from the data. They know which patients are most likely to struggle. They know what kind of support works best.

But designing a model and making it work in real clinics are two different things.

The model relies on electronic health records. It needs a system that can flag patients automatically. It also needs trained staff to respond to those alerts. In many parts of East Africa, clinics are understaffed and overworked.

The researchers are honest about this. They call their proposal a "pragmatic, data-enabled, risk-stratified model." In plain English, it is a smart plan that uses the tools already available. But it still needs to prove itself.

What This Means for Patients

If this model works, it could change how HIV care is delivered. Instead of waiting for patients to get sick, clinics would reach out to them early. Patients who struggle with medication would get extra support. Those with TB or diabetes would get care for both conditions in one place.

This is not a new drug or a cure. It is a better way to use the tools we already have.

For now, the message is simple. If you or someone you know is living with HIV, staying in care matters. Regular viral load tests are important. If the virus is not controlled, there are options. Talk to your doctor about what extra support might help.

What Happens Next

The researchers have laid out a clear next step. They want to test this model in real clinics. They have proposed a minimum dashboard that tracks three things: how fast patients get follow-up care, whether high-risk patients receive support, and how well HIV care is integrated with TB and NCD treatment.

This kind of research takes time. Building the data systems takes time. Training staff takes time. And proving that the model actually helps patients takes even longer.

But the goal is clear. The world has set a target called 95-95-95. That means 95 percent of people with HIV know their status, 95 percent are on treatment, and 95 percent have suppressed virus. The drugs can get us there. Now the systems need to catch up.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedMay 2026
View Original Abstract ↓
Despite widespread rollout of dolutegravir-based (DTG) antiretroviral therapy (ART) in East Africa, viral non-suppression, advanced HIV disease (AHD), and multimorbidity persist, reflecting gaps in service response rather than regimen potency alone. In Uganda’s The AIDS Support Organization (TASO) routine-care cohort (2014–2024; n = 54,348 people living with HIV), integrase inhibitor uptake is near universal, yet AHD remains common, and tuberculosis (TB) and non-communicable diseases (NCD) increasingly co-occur within HIV care. Among clients with a recorded most recent viral load, 6.4% (2,145/33,384) had viral non-suppression (VL ≥ 1,000 copies/mL). Second, our regional systematic review and meta-analysis (2016–2023; n = 29,829) estimates viral non-suppression at 19.4% and indicates that failure concentrates in predictable social and clinical risk strata. We propose that durable suppression may be strengthened by an accountable, time-bound viral load (VL) cascade, paired with targeted support for clients at elevated clinical and social risk. Building on WHO and national differentiated service delivery and AHD guidance, we outline a pragmatic, data-enabled, risk-stratified model that uses routine electronic health record (EHR) signals to trigger rapid viral non-suppression follow-up, guide delivery of a proposed time-limited adherence and socioeconomic stability bundle, and integrate TB and NCD management within HIV platforms. A minimum actionable dashboard focused on cascade timeliness, high-risk package delivery, and integrated care can translate ART scale-up into durable suppression, fewer preventable AHD complications, and faster progress toward 95–95–95.
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