Length of preoperative hospital stay is the dominating risk factor for surgical site infection in neurosurgery: A cohort data-driven analysis

Construction and validation of nomogram to predict surgical site infection after hysterectomy: a retrospective study

This study aimed to develop a predictive tool for surgical site infections (SSI) following hysterectomy and propose strategies for their prevention and control. We conducted a retrospective analysis at a tertiary maternity and child specialist hospital in Zhejiang Province, focusing on patients who underwent hysterectomy between January 2018 and December 2023 for gynecological malignancies or benign reproductive system diseases resistant to medical treatment. Risk factors associated with surgical site infections (SSI) following hysterectomy were identified using LASSO regression analysis on data from 2018 to 2022 as the training set. Independent risk factors were then used to develop a nomogram. The model was validated using data from 2023 as the validation set. Model performance was assessed using the area under the receiver operating characteristic curve (ROC), while calibration curves were employed to gauge model accuracy. Furthermore, clinical utility was evaluated through clinical decision curve analysis (DCA) and clinical impact curve analysis (CIC), providing insights into the practical application of the nomogram. Multivariate analysis identified six independent risk factors associated with SSI development after hysterectomy: BMI ≥ 24 kg/m2 (OR: 2.58; 95% CI 1.14-6.19; P < 0.05), hypoproteinaemia diagnosis (OR: 4.99; 95% CI 1.95-13.02; P < 0.05), postoperative antibiotic use for ≥ 3 days (OR: 49.53; 95% CI 9.73-91.01; P < 0.05), history of previous abdominal surgery (OR: 7.46; 95% CI 2.93-20.01; P < 0.05), hospital stay ≥ 10 days (OR: 9.67; 95% CI 2.06-76.46; P < 0.05), and malignant pathological type (OR: 4.62; 95% CI 1.78-12.76; P < 0.05). A nomogram model was constructed using these variables. ROC and calibration curves demonstrated good model calibration and discrimination in both training and validation sets. Analysis with DCA and CIC confirmed the clinical utility of the nomogram. Personalized nomogram mapping for SSI after hysterectomy enables early identification of high-risk patients, facilitating timely interventions to reduce SSI incidence post-surgery.

An update on a persisting challenge: A systematic review and meta-analysis of the risk factors for surgical site infection post craniotomy

BACKGROUND

Surgical site infections (SSIs) postcraniotomy continue to impose a significant burden on health care systems and patient outcomes. It is, therefore, important to understand their risk factors in order to promote effective preventative measures. This meta-analysis aims to provide a comprehensive, up-to-date analysis of the risk factors associated with SSIs in neurosurgical procedures.

METHODS

A systematic review was conducted as per preferred reporting items for systematic reviews and meta-analysis guidelines to explore existing primary evidence on the risk factors for SSIs postcraniotomy. A comprehensive search of MEDLINE, EMBASE, and Pubmed was performed from database inception up to June 2023. 43 studies were included in the meta-analysis, encompassing a total of 68,881 patients.

RESULTS

The strongest predictor for SSIs was found to be cerebrospinal fluid (CSF) leak (OR: 8.91, CI: 4.30-18.44). Other significant factors included infratentorial surgery (OR: 0.43, CI: 0.31-0.61), emergency surgery (OR: 1.41, CI: 1.05-1.91), reintervention (OR: 3.19, CI: 1.77-5.75), prolonged operative time (mean difference: 33.25; CI: 18.83-47.67), hospital length of stay (mean difference: 0.60; CI: 0.23-0.98) and intracranial pressure monitor (ICPM) insertion (OR: 1.81; CI: 1.06-3.11). Contrarily, sex, body mass index (BMI), diabetes, antibiotic prophylaxis, immunosuppressive agents, trauma, use of artificial implants did not demonstrate statistical significance.

CONCLUSIONS

This meta-analysis provides an up-to-date and comprehensive evaluation of risk factors for SSIs postcraniotomy. It emphasizes the need for preventive strategies, particularly against CSF leaks, and calls for further research to elucidate the intricate relationships between these factors.

A meta-analysis of the risk factors for neurosurgical surgical site infection following craniotomy

The purpose of the meta-analysis was to evaluate and compare the risk factors for neurosurgical surgical site infection (SSI) after craniotomy. Using dichotomous or contentious random or fixed effect models, the odds ratio (OR) and mean difference (MD) with 95% confidence intervals (CIs) were computed based on the examination of the meta-analysis results. Eighteen analyses, covering 11 068 craniotomies between 2001 and 2023, were included in the current meta-analysis. Subjects with SSIs had a significantly younger age (MD, -2.49; 95% CI, -2.95 to -2.04, p < 0.001), longer operation duration (MD, 10.21; 95% CI, 6.49-13.94, p < 0.001) and longer length of postoperative hospital stay (MD, 1.52; 95% CI, 0.45-2.60, p = 0.006) compared to subjects with no SSI with craniotomy. However, no significant difference was found between craniotomy subjects with SSIs and with no SSI in gender (OR, 0.90; 95% CI, 0.76-1.07, p = 0.23), and combination with other infection (OR, 3.93; 95% CI, 0.28-56.01, p = 0.31). The data that were looked at showed that younger age, longer operation duration and longer length of postoperative hospital stay can be considered as risk factors of SSI in subjects with craniotomy; however, gender and combination with other infections are not. Nonetheless, consideration should be given to their values because several studies only involved a small number of patients, and there are not many studies available for some comparisons.

Perioperative quality indicators among neurosurgery patients: A retrospective cohort study of 1142 cases at a tertiary center

OBJECTIVE

The purpose of this study was to present the first comprehensive analysis of perioperative quality indicators; length of hospital stay; readmission; reoperation; pre-, intra, and postoperative events; and mortality in a diverse neurosurgical patient cohort in Europe.

METHODS

Electronic medical records of all patients who were admitted to our institution between January 1 and December 31 of 2020, and underwent an index neurosurgical operation (n = 1142) were retrospectively reviewed.

RESULTS

The median length of hospital stay at the index admission and readmission was 8 days (range: 1-242 days) and 5 days (range: 0-94 days), respectively. Of the 1142 patients, 22.9% (n = 262) had an extended length of hospital stay of ≥14 days. The all-cause 7-, 15-, 30-, 60-, and 90-day readmission rates were 3.9% (n = 44), 5.7% (n = 65), 8.8% (n = 100), 12.3% (n = 141), and 16.5% (n = 188), respectively. The main reason for unplanned readmission was deterioration of medical and/or neurological condition. The all-cause 7-, 15-, 30-, 60-, and 90-day reoperation rates were 11.1% (n = 127), 13.8% (n = 158), 16.5% (n = 189), 18.7% (n = 213), and 19.4% (n = 221), respectively. Unplanned reoperations were due primarily to hydrocephalus. The rate of preoperative events was 1.1% (n = 13), one-third of which were associated with infection. The rate of intraoperative events was 11.0% (n = 126), of which 98 (64.47%) were surgical, 37 (24.34%) were anesthesiologic, and 17 (11.18%) were associated with technical equipment. The rate of postoperative events was 9.5% (n = 109). The most common postoperative event was malfunction, disconnection, or dislocation of an implanted device (n = 24, 17.91%). The mortality rates within 7, 15, 30, 60, and 90 days after the index operation were 0.9% (n = 10), 1.8% (n = 21), 2.5% (n = 29), 3.4% (n = 39), and 4.7% (n = 54), respectively. Several patient characteristics and perioperative factors were significantly associated with outcome parameters.

CONCLUSIONS

This study provides an in-depth analysis of quality indicators in neurosurgery, highlighting a variety of inherent and modifiable factors influencing patient outcomes.

Effect of preoperative hospital stay on surgical site infection in Chinese cranial neurosurgery

OBJECTIVE

Surgical site infection(SSI)after neurosurgical procedure can be devastating. Delayed hospital stay has been identified as a potentially modifiable driver of SSI in general surgery patients. However, the relationship between preoperative length of stay and SSI has not been quantified previously in neurosurgery. This study aimed to clarify the association.

DESIGN

A Cohort study based on STROBE checklist.

METHOD

This observational study focused on cranial neurosurgery patients at a tertiary referral centers in China. Data collection from hospital information system conducted between 1 January 2016 and 31 December 2016 was used to examine the results of interest (n = 600). Logistic regression analysis explored association between preoperative length of stay and SSI, adjusting for potential confounders.

RESULTS

Overall SSI prevalence was 10.8% and was significantly higher in the longer preoperative length of stay group. Besides preoperative length of stay, American Society of Anesthesiologists score, type of surgery, gross blood loss also significantly associated with SSI prevalence. Compared with 1 to 2 days, longer preoperative length of stay was associated with increased SSI prevalence after adjustment for confounders (3 to 4 days: odds ratio[OR], 0.975[95%CI, 0.417 to 2.281]; 5 to 6 days: OR, 2.830[95%CI, 1.092 to 7.332]; 7 or more days: OR, 4.039[95%CI, 1.164 to 14.015]; P for trend < 0.001). On the other hand, we found a positive association between preoperative length of stay to deep/space-organ SSI (OR = 1.404; 95% CI: 1.148 to 1.717; P for trend < 0.001), which was higher than superficial SSI (OR = 1.242; 95% CI: 0.835 to1.848; P for trend= 0.062).

CONCLUSIONS

In a cohort of patients from a single center retrospective surgical registry, a longer preoperative length of stay was associated with a higher incidence of cranial neurosurgical SSI. There is room for improvement in preoperative length of stay. This can be used for hospital management and to stratify patients with regard to SSI risk.