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Diagnosis of acute cystitis in primary care: symptom-based versus urinalysis-based diagnosis

Published online by Cambridge University Press:  17 November 2022

Rian Lelie- van der Zande*
Affiliation:
Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands
Ellen S. Koster
Affiliation:
Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands
Marion Grol
Affiliation:
General Practice Vreeswijk, Nieuwegein, the Netherlands
Kurt G. Naber
Affiliation:
Department of Urology, Technical University of Munich, Munich, Germany
Jakhongir F. Alidjanov
Affiliation:
Department of Urology, Pediatric Urology and Andrology, Justus-Liebig University of Giessen, Giessen, Germany
Martina Teichert
Affiliation:
Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, the Netherlands
Marcel L. Bouvy
Affiliation:
Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands
*
Author for correspondence: Rian Lelie- van der Zande, Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, David de Wiedgebouw, Universiteitsweg 99, 3584 CG Utrecht, the Netherlands. E-mail: a.c.a.lelie-vanderzande@uu.nl
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Abstract

Aim:

This study aimed to provide insight into the congruity of acute cystitis (AC) diagnosis in women, measured both by the Acute Cystitis Symptom Score (ACSS) questionnaire and urine test(s).

Background:

The ACSS questionnaire was developed as a self-administering tool for assessing urinary symptoms, quality of life (QoL) and treatment outcomes in healthy, nonpregnant female patients.

Methods:

This prospective observational cohort study compared AC diagnosis based on the questionnaire with a GP diagnosis based on dipstick/dipslide test(s). ACSS questionnaire form A (typical and differential symptoms, QoL and relevant conditions) was filled in by the patient group, women suspected for AC visiting a GP practice with a urine sample, and the reference group, women visiting a community pharmacy for any medication. Analyses were performed assuming that the GP diagnosis based on urine test(s) was correct. Divergent result(s) of urine test(s) and ACSS questionnaire were analysed for scores of all individual questionnaire domains. Statistical analyses included descriptive statistics and the positive predictive value (PPV) and the negative predictive value (NPV) of the ACSS questionnaire and the urine test(s).

Findings:

In the patient group, 59 women were included, 38 of whom a GP positively diagnosed for AC. The reference group included 70 women. The PPV of the ACSS questionnaire was 77.3%, and the NPV was 73.3%. Analysis of patient data for divergent results showed that differential symptoms, QoL and relevant conditions explained false-positive and false-negative results. Revised results (most probable diagnosis) based on this analysis showed a PPV and NPV of 88.6% and 73.3% for the ACSS questionnaire and 100% and 76.2% for the urine test(s). For use in primary care, a reduction in false-positive and false-negative results can be achieved by including scores for differential symptoms, QoL and relevant conditions, alongside a total typical symptoms score of 6 or higher.

Information

Type
Research
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1. Study flowchart

Figure 1

Table 1. Participants’ characteristics. AC diagnosis according to GP guideline

Figure 2

Table 2. Reliability analysis per domain for all included patients and controls

Figure 3

Table 3. Comparison of typical symptom scores, differential symptom scores, QoL item scores and domain scores between a) AC-positive patients (n = 38) versus AC-negative patients (N = 21); B) AC-positive patients (n = 38) versus reference group (n = 70); C) AC-negative patients (n = 21) versus reference group (n = 70). AC diagnosis according to GP guideline; differences statistically significant if P < 0.05

Figure 4

Figure 2. (A) Boxplot with typical symptom scores (median, IQR) for AC-positive patients (n = 38), AC-negative patients (n = 21) and reference group (n = 70), based on GP guideline diagnosis. (B) Boxplot with ACSS domain scores (median, IQR), both for AC-positive patients (n = 38), AC-negative patients (n = 21) and reference group (n = 70), based on GP guideline diagnosis

Figure 5

Figure 3. Percentages of AC-positive patients (n = 38), AC-negative patients (n = 21) and reference group (n = 70) for typical symptoms with score ≥1 (mild, moderate or severe symptoms). based on GP guideline diagnosis

Figure 6

Table 4. Patients with negative ACSS questionnaire result and positive urinary test(s) result but most probable diagnosis AC-positive (false-negative ACSS)

Figure 7

Table 5. Patients with positive ACSS questionnaire result and negative urinary test(s) result but most probable diagnosis AC-negative (false-positive ACSS)

Figure 8

Table 6. Patients with positive ACSS questionnaire result and negative urinary test(s) result but most probable diagnosis AC-positive (false-negative result for GP)

Figure 9

Figure 4. (A) Boxplot with typical symptom scores (median, IQR) for AC-positive patients (n = 43), AC-negative patients (n = 16) and reference group (n = 70), based on most probable diagnosis, after evaluation of divergent results of ACSS questionnaire and urine test(s). (B) Boxplot with ACSS domain scores (median, IQR), both for AC-positive patients (n = 43), AC-negative patients (n = 16) and reference group (n = 70), based on most probable diagnosis, after evaluation of divergent results of ACSS questionnaire and urine test(s)

Figure 10

Figure 5. Boxplot with total typical symptom scores (median, IQR) for AC-positive patients n = 38), AC-negative patients (n = 21) and reference group (n = 70), (a) based on GP guideline diagnosis, (b) based on most probable diagnosis after evaluation of divergent results of ACSS questionnaire and urine test(s), and (c) based on ACSS diagnosis (summary score ≥6)

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