{"doi":"10.1161/circulationaha.124.072156","title":"Evidence-Based Application of Natriuretic Peptides in the Evaluation of Chronic Heart Failure With Preserved Ejection Fraction in the Ambulatory Outpatient Setting","abstract":"BACKGROUND: Plasma NT-proBNP (N-terminal pro-B-type natriuretic peptide) is commonly used to diagnose heart failure with preserved ejection fraction (HFpEF), but its diagnostic performance in the ambulatory/outpatient setting is unknown because previous studies lacked objective reference standards. METHODS: Among patients with chronic dyspnea, diagnosis of HFpEF or noncardiac dyspnea was determined conclusively by exercise catheterization in a derivation cohort (n=414), multicenter validation cohort 1 (n=560), validation cohort 2 (n=207), and a nonobese Japanese validation cohort 3 (n=77). Optimal NT-proBNP cut points for HFpEF rule out (optimizing sensitivity) and rule in (optimizing specificity) were derived and tested, stratified by obesity and atrial fibrillation. Derived cut points were tested in 3 additional validation cohorts (cohorts 4–6) in whom HFpEF was diagnosed by resting catheterization only (n=260), previous hospitalization for heart failure (n=447), or exercise echocardiography (n=517), respectively. RESULTS: Current recommended rule-out NT-proBNP threshold <125 pg/mL had 82% sensitivity (95% CI, 77%–88%) with a body mass index (BMI) <35 kg/m 2 , decreasing to 67% (95% CI, 58%–77%) with a BMI ≥35 kg/m 2 . A lower rule-out NT-proBNP threshold <50 pg/mL displayed good sensitivity with a BMI <35 kg/m 2 (97% [95% CI, 95%–99%]), with a modest decline in sensitivity with a BMI ≥35 kg/m 2 (86% [95% CI, 79%–93%]); diagnostic thresholds were confirmed in validation cohorts 1 and 2 (91% [95% CI, 88%–95%] and 86% [95% CI, 80%–93%] with a BMI <35 kg/m 2 ; 80% [95% CI, 74%–87%] and 84% [95% CI, 74%–93%] with a BMI ≥35 kg/m 2 ). Current consensus age- and BMI-stratified rule-in thresholds demonstrated only 65% specificity (95% CI, 57%–72%). Rule-in NT-proBNP threshold ≥500 pg/mL had 85% specificity (95% CI, 78%–91%) with a BMI <35 kg/m 2 (87% [95% CI, 80%–94%] and 90% [95% CI, 81%–99%] in validation cohorts), with 100% specificity at a BMI ≥35 kg/m 2 (93% [95% CI, 81%–100%] and 100% in validation cohorts). With a BMI ≥35 kg/m 2 , lower rule-in thresholds (≥220 pg/mL) provided good specificity (88% [95% CI, 73%–100%]; 93% [95% CI, 81%–100%] and 100% in validation cohorts). Findings were consistent in validation cohorts 3 through 6 (sensitivity of <50 pg/mL, 93%–98%; specificity of ≥500 pg/mL, 82%–89%). NT-proBNP provided no incremental discrimination among patients with history of AF; ≥98% of patients with AF and dyspnea were found to have HFpEF in our cohorts. CONCLUSIONS: In patients with chronic unexplained dyspnea, current rule-in and rule-out NT-proBNP diagnostic thresholds lead to unacceptably high error rates, with important interactions by obesity and AF status. In our study, NT-proBNP provided little value in those with AF and dyspnea because the presence of AF is by itself a robust biomarker of HFpEF. Use of separate rule-in and rule-out diagnostic thresholds stratified by BMI reduces miscategorization and can guide more appropriate use of exercise testing for possible HFpEF.","journal":"Circulation","year":2025,"id":509000,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":54,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9501,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1072687,"name":"Atsushi Tada","orcid":"0009-0000-7998-1881","position":1,"is_corresponding":false},{"id":230311,"name":"Masaru Obokata","orcid":"0000-0002-5473-0688","position":2,"is_corresponding":false},{"id":288520,"name":"Rickey E. Carter","orcid":"0000-0002-0818-273X","position":3,"is_corresponding":false},{"id":937971,"name":"David M. Kaye","orcid":"0000-0003-4058-0372","position":4,"is_corresponding":false},{"id":863316,"name":"M. Louis Handoko","orcid":"0000-0002-8942-7865","position":5,"is_corresponding":false},{"id":1201619,"name":"Mads J. Andersen","orcid":"0000-0002-9320-8227","position":6,"is_corresponding":false},{"id":235997,"name":"Kavita Sharma","orcid":"0000-0002-3012-1765","position":7,"is_corresponding":false},{"id":235992,"name":"Ryan J. Tedford","orcid":"0000-0001-9045-7722","position":8,"is_corresponding":false},{"id":288521,"name":"Margaret M. Redfield","orcid":"0000-0002-0946-7518","position":9,"is_corresponding":false},{"id":230314,"name":"Barry A. Borlaug","orcid":"0000-0001-9375-0596","position":10,"is_corresponding":false},{"id":230310,"name":"Yogesh N.V. Reddy","orcid":"0000-0001-5322-0902","position":0,"is_corresponding":true}],"reference_count":49,"raw_metadata":null,"created_at":"2026-07-19T02:47:00.188082Z","pmid":"39840432","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}