Analysis of Influencing Factors for Incisional Surgical Site Infection after Laparoscopic Colorectal Cancer Surgery and Construction of a Prediction Model Article Swipe
Bin Liu
,
Jiacheng Zou
,
Wei Wang
,
Jun Ren
,
Liuhua Wang
,
Daorong Wang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-8008648/v1
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-8008648/v1
Colorectal cancer (CRC) is a common malignant tumor worldwide. Laparoscopic surgery has become the preferred treatment due to its minimally invasive advantages, but postoperative incisional surgical site infection (I-SSI) still significantly affects patient prognosis. This study aimed to analyze the risk factors for incisional infection after laparoscopic colorectal cancer surgery and construct a risk prediction model to provide a basis for precise clinical prevention. Clinical data of 919 patients who underwent laparoscopic radical resection of colorectal cancer at Northern Jiangsu People's Hospital from February 2018 to February 2022 were retrospectively collected. Univariate and multivariate Logistic regression were used to screen infection-related risk factors. A nomogram prediction model was constructed using R software, and the model performance was evaluated by ROC curve and calibration curve. Results showed that the incidence of incisional infection among 919 patients was 6.0%. Multivariate analysis indicated that diabetes mellitus (OR = 2.05), hypoproteinemia (OR = 3.52), high BMI (OR = 1.10), emergency surgery (OR = 0.35), and longitudinal incision (OR = 2.32) were independent risk factors, while preoperative prophylactic use of antibiotics (OR = 0.44) and incision length greater than the shortest tumor diameter (especially with a difference of 1–2 cm, OR = 0.35) were protective factors. The constructed nomogram model had an AUC of 0.76 (95% CI = 0.70–0.82), with a sensitivity of 0.70 and specificity of 0.83, and good calibration effect. This study identifies key influencing factors for incisional infection after laparoscopic colorectal cancer surgery, and the established nomogram model has moderate predictive performance (AUC = 0.76), providing a scientific basis for personalized surgical planning and infection prevention.
Related Topics
Concepts
Medicine
Nomogram
Logistic regression
Colorectal cancer
Laparoscopic surgery
Surgery
Univariate analysis
Colorectal surgery
Multivariate analysis
Surgical incision
Incidence (geometry)
Surgical site infection
Laparoscopy
Complication
Retrospective cohort study
Abdominal surgery
Stage (stratigraphy)
Cancer
Randomized controlled trial
Risk factor
Incisional hernia
Univariate
Clinical trial
Surgical wound
General surgery
Radical surgery
Colectomy
Metadata
- Type
- article
- Landing Page
- https://doi.org/10.21203/rs.3.rs-8008648/v1
- https://www.researchsquare.com/article/rs-8008648/latest.pdf
- OA Status
- gold
- References
- 13
- OpenAlex ID
- https://openalex.org/W7106684317
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7106684317Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-8008648/v1Digital Object Identifier
- Title
-
Analysis of Influencing Factors for Incisional Surgical Site Infection after Laparoscopic Colorectal Cancer Surgery and Construction of a Prediction ModelWork title
- Type
-
articleOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-11-26Full publication date if available
- Authors
-
Bin Liu, Jiacheng Zou, Wei Wang, Jun Ren, Liuhua Wang, Daorong WangList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-8008648/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-8008648/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://www.researchsquare.com/article/rs-8008648/latest.pdfDirect OA link when available
- Concepts
-
Medicine, Nomogram, Logistic regression, Colorectal cancer, Laparoscopic surgery, Surgery, Univariate analysis, Colorectal surgery, Multivariate analysis, Surgical incision, Incidence (geometry), Surgical site infection, Laparoscopy, Complication, Retrospective cohort study, Abdominal surgery, Stage (stratigraphy), Cancer, Randomized controlled trial, Risk factor, Incisional hernia, Univariate, Clinical trial, Surgical wound, General surgery, Radical surgery, ColectomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
13Number of works referenced by this work
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| abstract_inverted_index.at | 78 |
| abstract_inverted_index.by | 119 |
| abstract_inverted_index.is | 4 |
| abstract_inverted_index.of | 67, 75, 130, 175, 193, 209, 218, 222 |
| abstract_inverted_index.to | 18, 38, 57, 86, 99 |
| abstract_inverted_index.(OR | 144, 148, 153, 158, 164, 177 |
| abstract_inverted_index.919 | 68, 134 |
| abstract_inverted_index.AUC | 208 |
| abstract_inverted_index.BMI | 152 |
| abstract_inverted_index.ROC | 120 |
| abstract_inverted_index.The | 202 |
| abstract_inverted_index.and | 51, 93, 113, 122, 161, 180, 220, 224, 242, 262 |
| abstract_inverted_index.but | 23 |
| abstract_inverted_index.cm, | 195 |
| abstract_inverted_index.due | 17 |
| abstract_inverted_index.for | 43, 61, 234, 258 |
| abstract_inverted_index.had | 206 |
| abstract_inverted_index.has | 12, 247 |
| abstract_inverted_index.its | 19 |
| abstract_inverted_index.key | 231 |
| abstract_inverted_index.the | 14, 40, 114, 128, 185, 243 |
| abstract_inverted_index.use | 174 |
| abstract_inverted_index.was | 108, 117, 136 |
| abstract_inverted_index.who | 70 |
| abstract_inverted_index.(95% | 211 |
| abstract_inverted_index.(AUC | 251 |
| abstract_inverted_index.0.70 | 219 |
| abstract_inverted_index.0.76 | 210 |
| abstract_inverted_index.2018 | 85 |
| abstract_inverted_index.2022 | 88 |
| abstract_inverted_index.This | 35, 228 |
| abstract_inverted_index.data | 66 |
| abstract_inverted_index.from | 83 |
| abstract_inverted_index.good | 225 |
| abstract_inverted_index.high | 151 |
| abstract_inverted_index.risk | 41, 54, 102, 169 |
| abstract_inverted_index.site | 27 |
| abstract_inverted_index.than | 184 |
| abstract_inverted_index.that | 127, 141 |
| abstract_inverted_index.used | 98 |
| abstract_inverted_index.were | 89, 97, 167, 199 |
| abstract_inverted_index.with | 190, 215 |
| abstract_inverted_index.(CRC) | 3 |
| abstract_inverted_index.0.35) | 198 |
| abstract_inverted_index.0.44) | 179 |
| abstract_inverted_index.0.83, | 223 |
| abstract_inverted_index.1–2 | 194 |
| abstract_inverted_index.2.32) | 166 |
| abstract_inverted_index.6.0%. | 137 |
| abstract_inverted_index.after | 46, 237 |
| abstract_inverted_index.aimed | 37 |
| abstract_inverted_index.among | 133 |
| abstract_inverted_index.basis | 60, 257 |
| abstract_inverted_index.curve | 121 |
| abstract_inverted_index.model | 56, 107, 115, 205, 246 |
| abstract_inverted_index.still | 30 |
| abstract_inverted_index.study | 36, 229 |
| abstract_inverted_index.tumor | 8, 187 |
| abstract_inverted_index.using | 110 |
| abstract_inverted_index.while | 171 |
| abstract_inverted_index.0.35), | 160 |
| abstract_inverted_index.0.76), | 253 |
| abstract_inverted_index.1.10), | 155 |
| abstract_inverted_index.2.05), | 146 |
| abstract_inverted_index.3.52), | 150 |
| abstract_inverted_index.become | 13 |
| abstract_inverted_index.cancer | 2, 49, 77, 240 |
| abstract_inverted_index.common | 6 |
| abstract_inverted_index.curve. | 124 |
| abstract_inverted_index.length | 182 |
| abstract_inverted_index.screen | 100 |
| abstract_inverted_index.showed | 126 |
| abstract_inverted_index.(I-SSI) | 29 |
| abstract_inverted_index.Jiangsu | 80 |
| abstract_inverted_index.Results | 125 |
| abstract_inverted_index.affects | 32 |
| abstract_inverted_index.analyze | 39 |
| abstract_inverted_index.effect. | 227 |
| abstract_inverted_index.factors | 42, 233 |
| abstract_inverted_index.greater | 183 |
| abstract_inverted_index.patient | 33 |
| abstract_inverted_index.precise | 62 |
| abstract_inverted_index.provide | 58 |
| abstract_inverted_index.radical | 73 |
| abstract_inverted_index.surgery | 11, 50, 157 |
| abstract_inverted_index.Clinical | 65 |
| abstract_inverted_index.February | 84, 87 |
| abstract_inverted_index.Hospital | 82 |
| abstract_inverted_index.Logistic | 95 |
| abstract_inverted_index.Northern | 79 |
| abstract_inverted_index.People's | 81 |
| abstract_inverted_index.analysis | 139 |
| abstract_inverted_index.clinical | 63 |
| abstract_inverted_index.diabetes | 142 |
| abstract_inverted_index.diameter | 188 |
| abstract_inverted_index.factors, | 170 |
| abstract_inverted_index.factors. | 103, 201 |
| abstract_inverted_index.incision | 163, 181 |
| abstract_inverted_index.invasive | 21 |
| abstract_inverted_index.mellitus | 143 |
| abstract_inverted_index.moderate | 248 |
| abstract_inverted_index.nomogram | 105, 204, 245 |
| abstract_inverted_index.patients | 69, 135 |
| abstract_inverted_index.planning | 261 |
| abstract_inverted_index.shortest | 186 |
| abstract_inverted_index.surgery, | 241 |
| abstract_inverted_index.surgical | 26, 260 |
| abstract_inverted_index.construct | 52 |
| abstract_inverted_index.emergency | 156 |
| abstract_inverted_index.evaluated | 118 |
| abstract_inverted_index.incidence | 129 |
| abstract_inverted_index.indicated | 140 |
| abstract_inverted_index.infection | 28, 45, 132, 236, 263 |
| abstract_inverted_index.malignant | 7 |
| abstract_inverted_index.minimally | 20 |
| abstract_inverted_index.preferred | 15 |
| abstract_inverted_index.providing | 254 |
| abstract_inverted_index.resection | 74 |
| abstract_inverted_index.software, | 112 |
| abstract_inverted_index.treatment | 16 |
| abstract_inverted_index.underwent | 71 |
| abstract_inverted_index.Colorectal | 1 |
| abstract_inverted_index.Univariate | 92 |
| abstract_inverted_index.collected. | 91 |
| abstract_inverted_index.colorectal | 48, 76, 239 |
| abstract_inverted_index.difference | 192 |
| abstract_inverted_index.identifies | 230 |
| abstract_inverted_index.incisional | 25, 44, 131, 235 |
| abstract_inverted_index.prediction | 55, 106 |
| abstract_inverted_index.predictive | 249 |
| abstract_inverted_index.prognosis. | 34 |
| abstract_inverted_index.protective | 200 |
| abstract_inverted_index.regression | 96 |
| abstract_inverted_index.scientific | 256 |
| abstract_inverted_index.worldwide. | 9 |
| abstract_inverted_index.(especially | 189 |
| abstract_inverted_index.advantages, | 22 |
| abstract_inverted_index.antibiotics | 176 |
| abstract_inverted_index.calibration | 123, 226 |
| abstract_inverted_index.constructed | 109, 203 |
| abstract_inverted_index.established | 244 |
| abstract_inverted_index.independent | 168 |
| abstract_inverted_index.influencing | 232 |
| abstract_inverted_index.performance | 116, 250 |
| abstract_inverted_index.prevention. | 64, 264 |
| abstract_inverted_index.sensitivity | 217 |
| abstract_inverted_index.specificity | 221 |
| abstract_inverted_index.Laparoscopic | 10 |
| abstract_inverted_index.Multivariate | 138 |
| abstract_inverted_index.laparoscopic | 47, 72, 238 |
| abstract_inverted_index.longitudinal | 162 |
| abstract_inverted_index.multivariate | 94 |
| abstract_inverted_index.personalized | 259 |
| abstract_inverted_index.preoperative | 172 |
| abstract_inverted_index.prophylactic | 173 |
| abstract_inverted_index.0.70–0.82), | 214 |
| abstract_inverted_index.postoperative | 24 |
| abstract_inverted_index.significantly | 31 |
| abstract_inverted_index.hypoproteinemia | 147 |
| abstract_inverted_index.retrospectively | 90 |
| abstract_inverted_index.infection-related | 101 |
| abstract_inverted_index.<title>Abstract</title> | 0 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |