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Standing heart rates reveal overlap between long COVID and POTS (opens in a new tab)

medicalxpress.com · 2026-09-17

Short answerEvidenceSource

Short answer

Mostly supported

Mostly supported.

The claims we could check match the study, but some claims were not covered by the evidence reviewed.

  • 4 supported
  • 1 not covered

Checked against the study summary. The full text wasn't available, so some details couldn't be settled either way.

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1
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NewsLink checks it

Mostly supported

Every claim we could check holds up. Four of five claims match the study. This overall rating is based only on the claims we could check. One claim the study doesn't address.

  • 4 supported
  • 1 not covered
Open claim evidence
3
Then inspect each claim

Evidence layer

Claim by claim

Each claim gets a verdict. Expand it to see the evidence directly below.

5 claims in this story

Showing all 5 claimsChoose a verdict to focus the list.

Claim 1 of 5Not coveredThe article says the study is believed to be the first to look at autonomic symptoms, heart rate response, inflammatory markers and autoantibodies in people with long COVID, POTS and healthy volunteers.View evidenceHide evidence

Why this verdict

The paper profile supports that the study assessed autonomic symptoms/phenotype, heart-rate response, inflammatory cytokines, and autoantibodies across POTS, PASC, and healthy controls. However, the abstract-level profile does not verify the novelty/priority claim that it is believed to be the first study to do so.

1

Study evidence

Participants with POTS demonstrated significantly greater orthostatic tachycardia compared with controls and participants with PASC.Mean supine-to-standing HR change: POTS 46.3 ± 14.0 bpm; PASC 34.6 ± 13.7 bpm; controls 12.7 ± 6.6 bpm (overall P < 0.001; POTS vs PASC P = 0.005).

“In this cross-sectional study (August 2021 to December 2022), we recruited patients with POTS (n=24) or PASC (n=24) and healthy controls (n=19).”
2

Study evidence

Serum interleukin-2 (IL-2) was lower in participants with POTS compared with healthy controls.

“Participants underwent ... serum cytokine”
Claim 2 of 5SupportedNew Adelaide University research suggests that for some people with long COVID symptoms such as dizziness, fatigue, brain fog and a racing heart may also indicate postural orthostatic tachycardia syndrome (POTS).View evidenceHide evidence

Why this verdict

The abstract-level profile supports substantial overlap between PASC/long COVID and POTS: 62.5% of PASC participants met formal POTS criteria, and POTS/PASC groups had greater orthostatic intolerance/autonomic symptom burden than controls. The story frames this as hedged and associational, not as proof that long COVID causes POTS.

1

Study evidence

Participants with POTS demonstrated significantly greater orthostatic tachycardia compared with controls and participants with PASC.Mean supine-to-standing HR change: POTS 46.3 ± 14.0 bpm; PASC 34.6 ± 13.7 bpm; controls 12.7 ± 6.6 bpm (overall P < 0.001; POTS vs PASC P = 0.005).

“In this cross-sectional study (August 2021 to December 2022), we recruited patients with POTS (n=24) or PASC (n=24) and healthy controls (n=19).”
2

Study evidence

Electronic patient-reported outcome measures showed greater fatigue, orthostatic intolerance, autonomic symptom burden, and reduced health-related quality of life in participants with POTS and PASC compared with healthy controls.

“Patient-reported outcome measures were collected via secure electronic link.”
Claim 3 of 5SupportedThe study compared heart rate changes, symptoms and immune profiles among people with POTS, long COVID and healthy participants, and found that 62.5% of the long COVID participants also met the diagnostic criteria for POTS.View evidenceHide evidence

As stated62.5%

Why this verdict

The paper profile describes a cross-sectional comparison among POTS, PASC, and healthy controls, including active stand heart-rate testing, patient-reported symptoms, serum cytokines, and adrenergic autoantibody assays. The reported figure that 62.5% of PASC participants met formal POTS criteria is explicitly supported.

1

Study evidence

Participants with POTS demonstrated significantly greater orthostatic tachycardia compared with controls and participants with PASC.Mean supine-to-standing HR change: POTS 46.3 ± 14.0 bpm; PASC 34.6 ± 13.7 bpm; controls 12.7 ± 6.6 bpm (overall P < 0.001; POTS vs PASC P = 0.005).

“In this cross-sectional study (August 2021 to December 2022), we recruited patients with POTS (n=24) or PASC (n=24) and healthy controls (n=19).”
2

Study evidence

Serum interleukin-2 (IL-2) was lower in participants with POTS compared with healthy controls.

“Participants underwent ... serum cytokine”
Claim 4 of 5SupportedOn standing, average heart rates rose by 46 beats per minute in the POTS group and 35 beats per minute in the long COVID group, compared with 13 beats per minute in healthy volunteers.View evidenceHide evidence

As stated46 bpm, 35 bpm, 13 bpm

Why this verdict

The heart-rate changes match the abstract-level findings: mean supine-to-standing HR change was 46.3 bpm in POTS, 34.6 bpm in PASC, and 12.7 bpm in controls, reasonably rounded in the story to 46, 35, and 13 bpm.

1

Study evidence

Participants with POTS demonstrated significantly greater orthostatic tachycardia compared with controls and participants with PASC.Mean supine-to-standing HR change: POTS 46.3 ± 14.0 bpm; PASC 34.6 ± 13.7 bpm; controls 12.7 ± 6.6 bpm (overall P < 0.001; POTS vs PASC P = 0.005).

“In this cross-sectional study (August 2021 to December 2022), we recruited patients with POTS (n=24) or PASC (n=24) and healthy controls (n=19).”
Claim 5 of 5SupportedResearchers also reported subtle differences in inflammatory markers and said the blood tests suggest low-grade inflammation may play a role in POTS.View evidenceHide evidence

Why this verdict

The profile reports cytokine differences—lower IL-2 and higher IL-8 in POTS versus controls, and higher TNF-α in POTS cases versus non-POTS—consistent with the story’s hedged statement that inflammatory markers suggest low-grade inflammation may play a role. The abstract also reports that multivariate biomarker models lacked predictive utility, which tempers diagnostic implications but does not negate the hedged immune-contribution claim.

1

Study evidence

Serum interleukin-2 (IL-2) was lower in participants with POTS compared with healthy controls.

“Participants underwent ... serum cytokine”
2

Study evidence

Cell-based adrenergic autoantibody activation measures did not differ significantly among POTS, PASC, and healthy control groups.

“multivariate biomarker models lacked predictive utility for POTS diagnosis.”
Then look for missing context

Context layer

What the story left out

Important study details the story did not include.

  • Serum cytokine findings showed specific inflammatory-marker differences, but cytokine/autoantibody biomarker models lacked predictive utility for POTS diagnosis.

    The story mentions subtle inflammatory-marker differences and a possible role for low-grade inflammation, but it does not appear to convey the important negative finding that multivariate biomarker models lacked predictive utility for diagnosing POTS.

    From cross-sectional cytokine profiling; Predictive multivariable modeling (secondary analysis)

  • Adrenergic autoantibody activation measures did not differ significantly among POTS, PASC, and control groups.

    The story notes autoantibodies as part of what the study assessed, but the material null result for autoantibody activation is not reflected.

    From Cross-sectional ex-vivo cell-based autoantibody activation assay

  • The study had modest sample sizes: POTS n=24, PASC n=24, controls n=19, limiting precision and generalizability.

    The supplied story caveats do not mention the small group sizes, which is an interpretation-relevant limitation for the strength and generalizability of the findings.

    From cross-sectional observational group comparison; cross-sectional cytokine profiling; cross-sectional survey (electronic P

5 things the story did carry across
  • Cross-sectional observational design comparing POTS, PASC/long COVID, and healthy controls, with active stand testing and Holter monitoring.
  • A majority of PASC participants met formal POTS criteria: 62.5%.
  • Orthostatic heart-rate response differed by group, with the largest rise in POTS, an intermediate rise in PASC, and a smaller rise in controls.
  • Patient-reported outcomes showed greater fatigue, orthostatic intolerance, autonomic symptom burden, and reduced health-related quality of life in POTS and PASC groups versus controls.
  • Cross-sectional design precludes temporal or causal inference about SARS-CoV-2 infection, PASC, and development of POTS.
Then read the study layer

Study layer

Study at a glance

Scan the study first. Expand only the parts you want to inspect.

Pieces of work

5

Evidence read

study summary

Lead result

human in vivo

1Lead resulthuman in vivoCompare autonomic phenotype and objective cardiovascular measures (active stand testing; Holter monitoring) across POTS, PASC, and healthy controls, including estimating the proportion of PASC participants meeting formal POTS criteria.cross-sectional observational group comparisonExpand

In plain English

Cross-sectional comparison of autonomic/cardiovascular phenotype in people with POTS (n=24), PASC (n=24), and healthy controls (n=19) using 10-minute active stand testing and 24-hour Holter monitoring, reporting group differences in orthostatic heart rate response and the proportion of PASC participants meeting formal POTS criteria.

Key findings

  • Participants with POTS demonstrated significantly greater orthostatic tachycardia compared with controls and participants with PASC.Mean supine-to-standing HR change: POTS 46.3 ± 14.0 bpm; PASC 34.6 ± 13.7 bpm; controls 12.7 ± 6.6 bpm (overall P < 0.001; POTS vs PASC P = 0.005).
  • A majority of participants classified as PASC met formal POTS diagnostic criteria.62.5% of PASC participants met formal POTS criteria.
“In this cross-sectional study (August 2021 to December 2022), we recruited patients with POTS (n=24) or PASC (n=24) and healthy controls (n=19).”
What this piece can’t prove
  • Cross-sectional design precludes inference about temporal or causal relationships between SARS-CoV-2 infection, PASC, and POTS development.

3 further details could not be confirmed from the summary.

2ex vivo humanCompare circulating immune markers (serum cytokines) across groups and in relation to POTS phenotype (including within PASC by POTS-status).cross-sectional cytokine profilingExpand

In plain English

Cross-sectional serum cytokine profiling in 67 participants (POTS n=24, PASC n=24, controls n=19) found lower IL-2 and higher IL-8 in POTS versus controls, and higher tumor necrosis factor-α (TNF-α) in participants with POTS compared with those without POTS; cytokine and autoantibody measures did not provide predictive utility for POTS in multivariate models.

Key findings

  • Serum interleukin-2 (IL-2) was lower in participants with POTS compared with healthy controls.
  • Serum interleukin-8 (IL-8) was higher in participants with POTS compared with healthy controls.
“Participants underwent ... serum cytokine”
What this piece can’t prove
  • Cross-sectional design precludes inference of causality or temporal relationships between cytokine alterations and POTS onset.
  • Modest sample size (total n=67; POTS n=24, PASC n=24, controls n=19) limits precision and statistical power.
  • Abstract lacks detailed assay methods (platform, limits of detection, batch handling) and exact cytokine concentration or effect-size reporting.
  • Serum cytokine measurements may not reflect compartmentalized (tissue-level) immune activity relevant to POTS pathophysiology.
  • Multivariate model details and external validation are not reported, limiting assessment of the negative predictive finding.
3human in vivoCompare functional impact and symptom burden using patient-reported outcome measures across groups.cross-sectional survey (electronic PROs)Expand

In plain English

In a cross-sectional sample (n=67), electronic patient-reported outcome measures indicated greater fatigue, orthostatic intolerance, and autonomic symptom burden and reduced health-related quality of life in participants with POTS and PASC compared with healthy controls.

Key findings

  • Electronic patient-reported outcome measures showed greater fatigue, orthostatic intolerance, autonomic symptom burden, and reduced health-related quality of life in participants with POTS and PASC compared with healthy controls.
“Patient-reported outcome measures were collected via secure electronic link.”
What this piece can’t prove
  • Abstract does not specify which validated PRO instruments were used or provide questionnaire scoring details.
  • Cross-sectional study design prevents assessment of temporal changes or causal relationships.
  • Modest sample size (n=67) and relatively small group sizes constrain generalizability.
  • PROs are self-reported and collected electronically, potentially subject to reporting or selection bias.
4ex vivo humanAssess adrenergic autoantibody functional activity (cell-based activation assays) across groups and evaluate whether immune biomarkers (cytokines/autoantibodies) can predict POTS diagnosis (multivariable models).Cross-sectional ex-vivo cell-based autoantibody activation assayExpand

In plain English

In a cross-sectional sample (n=67; POTS 24, PASC 24, controls 19), adrenergic autoantibody functional activity was measured using cell-based activation assays. Autoantibody activation measures did not differ significantly among POTS, PASC, and control groups. Multivariable biomarker models that included cytokine and autoantibody measures did not demonstrate predictive utility for diagnosing POTS.

Key findings

  • Adrenergic autoantibody functional activation, measured by cell-based assays, showed no significant differences between POTS, PASC, and healthy control groups.
  • Multivariable biomarker models that included cytokine and autoantibody measures lacked predictive utility for diagnosing POTS in this cohort.
“Participants underwent ... adrenergic autoantibody assays (cell-based activation).”
What this piece can’t prove
  • Modest overall sample size (n=67) and group sizes (POTS n=24, PASC n=24, controls n=19) may limit power to detect differences or to develop/validate predictive models.
  • Cross-sectional design precludes assessment of temporal relationships or changes in autoantibody activity over time.
  • Abstract lacks technical details of the cell-based activation assay (e.g., antigen constructs, readout, positivity thresholds) and of the multivariable modeling approach.
  • Possible type II error (false-negative) cannot be excluded given limited sample and absence of reported effect estimates.
5secondary dataAssess adrenergic autoantibody functional activity (cell-based activation assays) across groups and evaluate whether immune biomarkers (cytokines/autoantibodies) can predict POTS diagnosis (multivariable models).Predictive multivariable modeling (secondary analysis)Expand

In plain English

In a cross-sectional cohort (n=67; POTS n=24, PASC n=24, controls n=19), the authors performed secondary multivariable predictive modeling using circulating cytokine measures and cell-based adrenergic autoantibody activation assays as candidate predictors. The abstract reports that autoantibody activation measures did not differ significantly among groups and that multivariate biomarker models lacked predictive utility for diagnosing POTS; model type, validation approach, and performance metrics are not reported in the abstract.

Key findings

  • Cell-based adrenergic autoantibody activation measures did not differ significantly among POTS, PASC, and healthy control groups.
  • Multivariate biomarker models incorporating cytokine and autoantibody measures lacked predictive utility for diagnosing POTS.
“multivariate biomarker models lacked predictive utility for POTS diagnosis.”
What this piece can’t prove
  • Modest sample size and small group sizes (POTS 24, PASC 24, controls 19) reduce statistical power for both group comparisons and predictive modeling and increase risk of overfitting.
  • Cross-sectional study design prevents assessment of temporal or prognostic predictive value.
  • Biomarker measurements confined to circulating serum; potential compartmentalized immune signals may not be detected.

2 further details could not be confirmed from the summary.

Finally, the search trail

Method layer

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NewsLink checks the story. Tessa is where you inspect the paper, authors, evidence, and research context.

Open the paper in Tessa

Comparative Analysis of Circulating Cytokines and Adrenergic Autoantibodies in Postural Orthostatic Tachycardia Syndrome, Postacute Sequelae of SARS-CoV-2, and Healthy Controls.

Journal of the American Heart Association · 2026

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Why this one

Near certain

NewsLink found the paper. Tessa is where you inspect it deeply.

Papers considered

The selected paper, plus nearby candidates.

PubMed, Crossref, Europe PMC · 39 candidate papers

Selected

Comparative Analysis of Circulating Cytokines and Adrenergic Autoantibodies in Postural Orthostatic Tachycardia Syndrome, Postacute Sequelae of SARS-CoV-2, and Healthy Controls.

Journal of the American Heart Association · 2026 · PubMed, Crossref

Tessa (opens in a new tab)Source (opens in a new tab)
Candidate

Delta Heart Rate and Autonomic Symptom Burden Association in Postural Orthostatic Tachycardia Syndrome

Heart, Lung and Circulation · 2026 · Crossref

Source (opens in a new tab)

And 33 more candidates considered.