Evidence map›Paper›PMID 40999342›Full record

ArticleBMC nephrology2025

Factors influencing the symptom-to-contact time in patients with peritoneal dialysis-associated peritonitis: a multi-center retrospective study.

Huimin Huang, Yan Luo, Meirong Lv, Qing Liao, Juanjuan Ou, Cuirong Hu

Abstract readMulticenter Study
In one paragraph

Article in BMC nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Huimin HuangDepartment of Nursing, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China.
Yan LuoDepartment of Nursing, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China. luoyan5158745@163.com.
Meirong LvThe Xiamen Traditional Chinese Medicine Hospital, Xiamen, China.
Qing LiaoThe Second Hospital Affiliated to Xiamen Medical University, Xiamen, China.
Juanjuan OuNephrology Ward, Zhongshan Hospital Affiliated to Xiamen University, 201-209 Hubinnan Road, Xiamen, 361004, China.
Cuirong HuNephrology Ward, Zhongshan Hospital Affiliated to Xiamen University, 201-209 Hubinnan Road, Xiamen, 361004, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDelays in seeking medical attention cause delays in the initiation of antibiotic therapy, prolonging the duration of illness in patients with peritoneal dialysis-associated peritonitis (PDAP). However, there is limited information on the factors that cause delays in seeking initial medical attention after the onset of symptoms. This study aims to investigate the situation and factors influencing delayed consultation in PDAP patients.

methodsRetrospective review of clinical and epidemiological data of all adult patients with peritoneal dialysis-associated peritonitis in three hospitals in Xiamen, China, who developed peritonitis between January 2022 and November 2024. Data were analysed with descriptive and inferential statistics (i.e. correlation and multiple logistic regression) using the Statistical Package for the Social Sciences version 27.

resultsA total of 134 patients were included in the current study, of whom 77 (57.5%) had symptom-to-contact time (SC time) ≦ 24 h. Cloudy effluent was the most common presenting symptom (73.9%), while 67.9% had abdominal pain and 53% had both. Univariate analysis showed that there was a statistically significant difference between groups in residence (χ2 = 10.059, P = 0.002), PD modality (χ2 = 7.151, P = 0.007), fever (χ2 = 10.631, P = 0.001), abdominal pain (χ2 = 13.206, P < 0.001), cloudy effluent (χ2 = 8.002, P = 0.005), and diarrhea (χ2 = 4.953, P = 0.026). Univariate logistic regression analysis demonstrated that Residence(OR = 2.54, 95% CI:1.09-5.94, p = 0.032)、PD modality(OR = 0.06, 95% CI:0.01-0.87, p = 0.039)、Abdominal pain(OR = 4.60, 95% CI:1.87-11.32, p = 0.001)、Fever(OR = 4.34, 95% CI:1.24-15.17, p = 0.022)、Diarrhea(OR = 0.26, 95% CI:0.07-0.94, p = 0.040)are factors affecting the SC time in patients with peritoneal dialysis-associated peritonitis.

conclusionA substantial proportion of PDAP patients experienced delayed consultation. Specifically, residence, PD modality, abdominal pain, fever, and diarrhea were the influencing factors for delayed consultation in PDAP patients. Targeted interventions in managing PDAP patients are therefore important to promote timely consultations, particularly in rural areas, by improving patient awareness and education. They should also enhance the accessibility of healthcare services and provide clear guidance on when to seek medical attention.

trial registrationNot applicable.

Indexed as

Peritoneal DialysisPeritonitisTime-to-TreatmentAbdominal PainAdultAgedChinaFemaleHumansMaleMiddle AgedRetrospective StudiesTime FactorsInfluencing factorsPeritoneal dialysis-associated peritonitisSymptom-to-contact time

Identifiers

PMID40999342
PMCPMC12465788

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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.