Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study
Background This study was performed to construct and validate an early risk warning model of urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD). Methods Eligible patients with NLUTD admitted to Shenzhen Longcheng hospital from January 2017 to June 2021 were r...
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PeerJ Inc.
2022-05-01
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| Online Access: | https://peerj.com/articles/13388.pdf |
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| author | Liqiong Zhou Surui Liang Qin Shuai Chunhua Fan Linghong Gao Wenzhi Cai |
| author_facet | Liqiong Zhou Surui Liang Qin Shuai Chunhua Fan Linghong Gao Wenzhi Cai |
| author_sort | Liqiong Zhou |
| collection | DOAJ |
| description | Background This study was performed to construct and validate an early risk warning model of urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD). Methods Eligible patients with NLUTD admitted to Shenzhen Longcheng hospital from January 2017 to June 2021 were recruited for model construction, internal validation and external validation. The first time point of data collection was within half a month of patients first diagnosed with NLUTD. The second time point was at the 6-month follow-up. The early warning model was constructed by logistic regression. The model prediction effects were validated using the area under the Receiver Operating Characteristic curve, the Boostrap experiment and the calibration plot of the combined data. The model was externally validated using sensitivity, specificity and accuracy. Results Six predictors were identified in the model, namely patients ≥65 years old (OR = 2.478, 95%CI [1.215– 5.050]), female (OR = 2.552, 95%CI [1.286–5.065]), diabetes (OR = 2.364, 95%CI) [1.182–4.731]), combined with urinary calculi (OR = 2.948, 95%CI [1.387–6.265]), indwelling catheterization (OR = 1.988, 95%CI [1.003 –3.940]) and bladder behavior training intervention time ≥2 weeks (OR = 2.489, 95%CI [1.233–5.022]); and the early warning model formula was Y = 0.907 × age+ 0.937 × sex + 0.860 × diabetes +1.081 × combined with urinary calculi+ 0.687 × indwelling catheterization+ 0.912 × bladder behavior training intervention time-2.570. The results show that the area under the ROC curve is 0.832, which is close to that of 1,000 Bootstrap internal validation (0.828). The calibration plot shows that the early warning model has good discrimination ability and consistency. The external validation shows the sensitivity is 62.5%, the specificity is 100%, and the accuracy is 90%. Conclusion The early warning model for urinary tract infection in patients with NLUTD is suitable for clinical practice, which can provide targeted guidance for the evaluation of urinary tract infection in patients with NLUTD. |
| first_indexed | 2024-03-09T06:51:13Z |
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| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T06:51:13Z |
| publishDate | 2022-05-01 |
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| spelling | doaj.art-778a57a1d587423c9c9fdc46912915dd2023-12-03T10:27:28ZengPeerJ Inc.PeerJ2167-83592022-05-0110e1338810.7717/peerj.13388Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective studyLiqiong Zhou0Surui Liang1Qin Shuai2Chunhua Fan3Linghong Gao4Wenzhi Cai5Nursing Department, Southern Medical University, Shenzhen Hospital, Shenzhen, Guangdong, ChinaNursing Department, Southern Medical University, Shenzhen Hospital, Shenzhen, Guangdong, ChinaNursing Department, Shenzhen Longcheng Hospital, Shenzhen, Guangdong, ChinaNursing Department, Shenzhen Longcheng Hospital, Shenzhen, Guangdong, ChinaNursing Department, Shenzhen Longcheng Hospital, Shenzhen, Guangdong, ChinaNursing Department, Southern Medical University, Shenzhen Hospital, Shenzhen, Guangdong, ChinaBackground This study was performed to construct and validate an early risk warning model of urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD). Methods Eligible patients with NLUTD admitted to Shenzhen Longcheng hospital from January 2017 to June 2021 were recruited for model construction, internal validation and external validation. The first time point of data collection was within half a month of patients first diagnosed with NLUTD. The second time point was at the 6-month follow-up. The early warning model was constructed by logistic regression. The model prediction effects were validated using the area under the Receiver Operating Characteristic curve, the Boostrap experiment and the calibration plot of the combined data. The model was externally validated using sensitivity, specificity and accuracy. Results Six predictors were identified in the model, namely patients ≥65 years old (OR = 2.478, 95%CI [1.215– 5.050]), female (OR = 2.552, 95%CI [1.286–5.065]), diabetes (OR = 2.364, 95%CI) [1.182–4.731]), combined with urinary calculi (OR = 2.948, 95%CI [1.387–6.265]), indwelling catheterization (OR = 1.988, 95%CI [1.003 –3.940]) and bladder behavior training intervention time ≥2 weeks (OR = 2.489, 95%CI [1.233–5.022]); and the early warning model formula was Y = 0.907 × age+ 0.937 × sex + 0.860 × diabetes +1.081 × combined with urinary calculi+ 0.687 × indwelling catheterization+ 0.912 × bladder behavior training intervention time-2.570. The results show that the area under the ROC curve is 0.832, which is close to that of 1,000 Bootstrap internal validation (0.828). The calibration plot shows that the early warning model has good discrimination ability and consistency. The external validation shows the sensitivity is 62.5%, the specificity is 100%, and the accuracy is 90%. Conclusion The early warning model for urinary tract infection in patients with NLUTD is suitable for clinical practice, which can provide targeted guidance for the evaluation of urinary tract infection in patients with NLUTD.https://peerj.com/articles/13388.pdfNeurogenic bladderUrinary tract infectionEarly waring modelRisk factorsNeurogenic lower urinary tract dysfunction |
| spellingShingle | Liqiong Zhou Surui Liang Qin Shuai Chunhua Fan Linghong Gao Wenzhi Cai Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study PeerJ Neurogenic bladder Urinary tract infection Early waring model Risk factors Neurogenic lower urinary tract dysfunction |
| title | Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study |
| title_full | Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study |
| title_fullStr | Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study |
| title_full_unstemmed | Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study |
| title_short | Early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction (NLUTD): a retrospective study |
| title_sort | early warning model construction and validation for urinary tract infection in patients with neurogenic lower urinary tract dysfunction nlutd a retrospective study |
| topic | Neurogenic bladder Urinary tract infection Early waring model Risk factors Neurogenic lower urinary tract dysfunction |
| url | https://peerj.com/articles/13388.pdf |
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