Bacteriology of Secondary Peritonitis and Relationship to Surgical Site Infection in a Tertiary Health Establishment in Southern Nigeria
Bibliographic record
Abstract
Background: Peritonitis secondary to gastrointestinal perforation is associated with high morbidity and mortality rates. The outcome is dependent on multiple factors, but significantly on early diagnosis and prompt intervention. The principles of management are based on fluid resuscitation, initiation of appropriate antibiotic therapy, surgical intervention, and management of associated co-morbid conditions. Aim and Objectives: To determine the bacterial flora of the peritoneal fluid culture in secondary peritonitis resulting from gastrointestinal perforation and relate the findings to the bacterial flora of surgical site infections/morbidity in patients presenting to Irrua Specialist Teaching Hospital. Study Design: This is a prospective study of 64 consecutive patients with secondary peritonitis due to gastrointestinal perforation. Methodology: All patients who were laparotomised for secondary peritonitis had their intraperitoneal fluid sent for microscopy, aerobic culture, and sensitivity. Intravenous ceftriaxone and metronidazole were administered to all the patients pre-operatively. Postoperatively, the wounds were assessed on days 3, 5, 7, 14, and 30 for surgical site infection (SSI). The concordance rate of the microorganism-isolated from peritoneal and wound culture was calculated using the formula: Concordance Rate = Number of Concordant Pairs Number of Concordant Pairs+Number of Discordant Pairs X 100 Results: Sixty-four patients who met the inclusion criteria were selected for the study. The mean age was 43.9 ± 16.3 years (range: 18-74 years). There were 43 (67.2%) males and 21 (32.8%) females, with a male to female ratio of 2:1. The mean duration of hospitalization was 12.4 days (range: 6-30 days) with predominant site of perforation being gastroduodenal (n=27, i.e., 42.2%), followed by ruptured appendicitis (n=24, i.e., 37.5%). Of the 64 peritoneal fluid specimens sent for microscopy, culture, and antibiotic sensitivity, 55 (85.9%) yielded bacterial growth. The bacteria most frequently isolated from peritoneal fluid were Escherichia coli (20; 31.3%) and Klebsiella (14; 21.9%). There was no growth in 9 (14.1%). Escherichia coli was sensitive to ceftriaxone in 70.3%, piperacillin-tazobactam in 74.0%, and meropenem in 95.4% of cases. Klebsiella pneumoniae was sensitive to ciprofloxacin in 70.0%, ceftriaxone in 70.2%, piperacillin-tazobactam in 67.0%, and meropenem in 79.1% of cases. The overall surgical site infection (SSI) rate was 16 in 64 patients (25.0%), with 14 cases (21.9%) being superficial SSIs and 1 case (1.6%) each of deep SSI and organ space infection. Conclusion: Escherichia coli was the most commonly isolated microorganism in cases of peritonitis secondary to gastrointestinal perforation and the subsequent SSI, followed by Klebsiella, Staphylococcus aureus, mixed growth of Staphylococcus aureus and Escherichia coli, Pseudomonas aeruginosa, and Candida.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".