Incidence and predictors of surgical site infection following cesarean section in North-west Ethiopia: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Following delivery by caesarean section, surgical site infection is the most common infectious complication. Despite a large number of caesarean sections performed at Debre Markos Referral Hospital, there was no study documenting the incidence of surgical site infection after caesarean section. Therefore, this study aimed to estimate the incidence of surgical site infection following caesarean section at Debre-Markos Referral Hospital in Amhara region, North-west Ethiopia. METHODS: A prospective cohort study was conducted among 520 pregnant women who had a caesarean section between March 28, 2019 and August 31, 2019. Preoperative, intraoperative, and postoperative data were collected using a standardized questionnaire. Data was entered using EpiData™ Entry Version 4.1 software and analyzed using R Version 3.6.1 software. A descriptive analysis was conducted using tables, interquartile ranges and median. The time to development of surgical site infection was estimated using Kaplan-Meier method. The Cox regression model for bivariable and multivariable analyses was done. Adjusted Hazard Ratio (AHR) with 95% Confidence Interval (CI) was reported to show the strength of association. RESULT: The mean age of the study cohort was 27.4 ± 4.8 years. The overall cumulative incidence of surgical site infection was 25.4% with an incidence of 11.7 (95% CI:9.8,13.9) per 1000 person/days. Not able to read and write (AHR = 1.30,95% CI:1.19,2.11), no antenatal care (AHR = 2.16, 95%CI:1.05,4.53), previous history of CS (AHR = 1.21, 95% CI:1.11,2.31), HIV positive (AHR = 1.39, 95% CI:1.21,2.57), emergency procedure (AHR = 1.13, 95% CI:1.11,2.43), vertical type of incision (AHR = 2.60, 95% CI:1.05,6.44), rupture of membrane (AHR = 1.50, 95% CI:1.31,1.64), multiple vaginal examination (AHR = 1.88, 95% CI: 1.71, 3.20) were significant predictors of surgical site infection in this study. CONCLUSION: This study concluded that the incidence of surgical site infection following caesarean section was relatively high compared to previous studies. Not able to read and write, have no ante natal care, previous history of caesarean section, HIV, emergency surgery, vertical type of incision, rupture of membranes before caesarean section, and multiple vaginal examinations were significant predictors of surgical site infection in this study. Therefore, intervention programs should focus on and address the identified factors to minimize and prevent the infection rate after caesarean section.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".