Evidence map›Paper›PMID 22458739›Full record

ArticleJournal of clinical hypertension (Greenwich, Conn.)2012

A simplified mechanistic algorithm for treating resistant hypertension: efficacy in a retrospective study.

Samuel J Mann, Neal S Parikh

Open access · bronzeAbstract read
In one paragraph

Article in Journal of clinical hypertension (Greenwich, Conn.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 19 citations in OpenAlex.

  1. Neurogenic hypertension: pathophysiology, diagnosis and management.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2018
    Review
  2. Article
  3. Article
  4. Review
  5. Exploring issues in difficult-to-treat hypertension.Journal of clinical hypertension (Greenwich, Conn.) · 2013
    Review
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Samuel J MannDivision of Nephrology and Hypertension, Department of Medicine, Weill/Cornell Medical Center, New York Presbyterian Hospital, New York, NY 10021, USA. sjmann@med.cornell.edu
Neal S Parikh
Cornell University · USNewYork–Presbyterian Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This retrospective study assessed the efficacy of a recently described, mechanism-based algorithm for treating resistant hypertension. Charts of consecutive patients seen for resistant hypertension were reviewed. Algorithm-based intervention was limited to either or both of just 2 options: (1) strengthening of the diuretic regimen, usually with addition of spironolactone; and (2) treatment with the combination of an α- + nonmetabolized β-blocker. Of 27 patients, 24 (89%) achieved control, including 13 (54%) in whom the diuretic regimen was strengthened, 6 (25%) in whom α-/β-blockade was instituted, and 5 (21%) who received both interventions. The most frequent medication adjustments were addition of a potassium-sparing diuretic in 16 (67%), doxazosin in 9 (37.5%), and replacing a metabolized with a nonmetabolized β-blocker in 6 (25%). The authors conclude that treatment based on this algorithm can both simplify and improve the management of resistant hypertension and merits further evaluation in prospective studies.

Indexed as

AlgorithmsAdrenergic beta-AntagonistsAntihypertensive AgentsDiureticsFemaleHumansHypertensionMaleMiddle AgedRenin-Angiotensin SystemRetrospective StudiesTreatment FailureAdrenergic beta-AntagonistsAntihypertensive AgentsDiuretics

Identifiers

PMID22458739
PMCPMC8108948
OpenAlexW1485129821

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.