European Journal of Cardiovascular Medicine

Post-operative complications after GI surgery remain common and costly. Traditional risk models incorporate age, comorbidity, nutritional status, and operative factors but variably predict outcomes. The gut microbiome modulates mucosal immunity, metabolite production (e.g., short-chain fatty acids), and pathogen resistance—pathways central to wound healing, motility, and barrier integrity. We hypothesised that pre-operative microbiome composition independently associates with early post-operative outcomes.

Objectives:

1. Determine associations between pre-operative microbiome diversity/composition and 30-day major complications;
2. Identify taxa linked to specific complications (SSI, ileus, leak);
3. Evaluate incremental predictive value of microbiome features beyond clinical factors.

Study Design and Population

Prospective cohort across three tertiary centres (January–December). Adults (≥18 years) undergoing elective GI surgery were eligible. Exclusions: emergency surgery, ostomy reversal only, antibiotic use >48 h in the 14 days prior (except single-dose prophylaxis allowed), inflammatory bowel disease flare requiring steroids >10 mg/day, bowel prep with non-standard antibiotics. All participants provided written informed consent; protocol approved by local IRBs.

Peri-operative Care

Enhanced Recovery After Surgery (ERAS) pathways were standard. Prophylactic antibiotics followed guideline-concordant regimens.

Microbiome Sampling and Profiling

Participants provided stool within 7 days pre-op (stabilised at collection, −80 °C storage). DNA extraction used bead-beating protocols. V3–V4 16S rRNA amplicons were sequenced (Illumina), DADA2 denoised to amplicon sequence variants (ASVs), SILVA taxonomy assigned. Alpha diversity (Shannon), beta diversity (Bray–Curtis), and enterotype clustering (partitioning around medoids) were computed. A prespecified dysbiosis score summed z-scores of decreased SCFA producers (Faecalibacterium, Roseburia, Blautia) and increased potential pathobionts (Enterococcus, Escherichia/Shigella, Klebsiella).

Outcomes

Primary: Composite 30-day major complications (Clavien–Dindo ≥ II).

Secondary: SSI (CDC criteria), anastomotic leak (clinical/radiologic), prolonged ileus (no flatus/bowel movement by post-op day 4 or NG reinsertion), LOS, and 30-day readmission.

Covariates

Age, sex, BMI, smoking, diabetes, malignancy, ASA class, neoadjuvant therapy, serum albumin, operative approach (open vs minimally invasive), procedure type, operative time, and blood loss.

Statistical Analysis

Continuous variables summarised as mean±SD or median[IQR]; categorical as n(%). Group comparisons used t/χ²/Mann–Whitney tests as appropriate. Multivariable logistic regression estimated adjusted odds ratios (aORs). LOS modelled with negative binomial regression. Microbiome features entered as quartiles/tertiles or z-scores; false discovery rate (FDR) controlled at 10% for taxa analyses. Discrimination assessed via AUC with and without microbiome features (DeLong test). Sensitivity analyses: excluding pre-op antibiotics entirely, stratifying by ERAS adherence, and centre-level random effects. Two-sided p<0.05 signified significance

Cohort

Of 487 screened, 420 enrolled and completed follow-up. Mean age 61±12; 52% male; 58% colorectal resections, 21% upper GI, 21% HPB or small-bowel procedures. Major complications occurred in 118 (28.1%).

Primary Associations

Lower alpha diversity associated with higher complication risk (linear trend across quartiles p = 0.002). In adjusted models, lowest vs highest diversity quartile: aOR 2.10 (95% CI 1.28–3.43). Each SD increase in dysbiosis score: aOR 1.38 (95% CI 1.12–1.72). Adding microbiome features improved primary model AUC from 0.72 to 0.78 (ΔAUC +0.06; p = 0.01).

Taxa and Secondary Outcomes

Top-tertile Enterococcus abundance associated with SSI (aOR 2.44; 95% CI 1.29–4.62). Bottom-tertile Faecalibacterium associated with prolonged ileus (aOR 1.91; 95% CI 1.08–3.37). Anastomotic leak showed a non-significant trend with low Akkermansia (aOR 1.74; 95% CI 0.93–3.28; p = 0.082). Dysbiosis correlated with longer LOS (+1.4 days per SD; 95% CI 0.6–2.2).

Inference

Across multiple models and sensitivity checks, pre-operative microbiome signatures independently and consistently predicted early post-operative morbidity, with effect sizes comparable to established clinical risk factors (e.g., ASA class, operative time). The direction of effects (low diversity, higher pathobionts, fewer SCFA producers) aligns biologic plausibility and supports potential causal pathways worth testing in interventional trials.

Table 1. Baseline Characteristics by 30-day Major Complications

Table 2. Pre-operative Microbiome Metrics by Complication Status

Table 3. Multivariable Logistic Regression for Primary Outcome (Major Complications)

AUC clinical model alone: 0.72; +microbiome features: 0.78; ΔAUC +0.06, p = 0.01.

Table 4. Microbiome Associations with Key Secondary Outcomes (Adjusted Models)

Table 5. Sensitivity Analyses

In this prospective cohort, pre-operative gut microbiome features were strongly and independently associated with early post-operative morbidity after GI surgery. Low alpha diversity and a composite dysbiosis index—reflecting loss of SCFA-producing commensals and expansion of pathobionts—were robust predictors of the composite major complication endpoint and longer LOS. Taxon-level signals were biologically coherent: Enterococcus enrichment associated with SSI (reflecting potential for biofilm formation and antimicrobial resistance), while reduced Faecalibacterium—a canonical butyrate producer supporting epithelial energy and motility—associated with prolonged ileus. A trend toward higher leak risk with depleted Akkermansia (mucin degrader linked to barrier integrity) merits larger samples.

Importantly, microbiome features improved discrimination beyond established clinical variables (ΔAUC +0.06). While modest, this improvement could meaningfully inform peri-operative risk stratification, targeted monitoring, or resource allocation.

Our review underscores that while hormone therapy remains the most effective intervention for vasomotor symptoms, its use is limited by safety concerns and patient acceptability【1–3】. Non-hormonal pharmacotherapies, including SSRIs, SNRIs, and gabapentin, consistently demonstrate significant reductions in hot flash frequency and severity, providing validated alternatives for women unable to pursue hormone therapy【4–7】. Clonidine shows modest benefits but is often poorly tolerated due to side effects such as hypotension and dry mouth【8】. Herbal and complementary therapies, including phytoestrogens, black cohosh, and red clover, remain popular; however, evidence from RCTs and meta-analyses suggests their effects are inconsistent and often indistinguishable from placebo【9–11】. More recently, behavioral interventions such as cognitive-behavioral therapy (CBT), yoga, and mindfulness have gained traction, with several trials confirming improvements in symptom perception, sleep quality, and quality of life【12–14】. Importantly, recent network meta-analyses position combination approaches—leveraging both pharmacological and non-pharmacological strategies—as the most promising pathway for individualized, patient-centered menopause care【15】.

Clinical Implications

• Risk Stratification: Pre-operative stool profiling could identify high-risk patients for enhanced surveillance or prehabilitation.
• Modulation Opportunities: Trials should test microbiome-targeted strategies (dietary fibre/prebiotics, SCFA-focused synbiotics, selective decontamination alternatives, or peri-operative antibiotic stewardship) with mechanistic endpoints (barrier function, metabolomics).
• Antibiotic Stewardship: Associations persisted after excluding recent antibiotics, but prophylactic regimens and timing remain critical covariates for future research.

Strengths and Limitations

Strengths include prospective design, prespecified microbiome and clinical covariates, and multicentre recruitment.

Limitations: 16S profiling limits strain-level resolution and functional inference; residual confounding is possible; single pre-operative sample may not capture temporal dynamics; and external validation is required. Interventional causality cannot be inferred from observational data.

Pre-operative gut microbiome composition—particularly low diversity, higher dysbiosis, Enterococcus enrichment, and depletion of SCFA producers—predicts adverse early outcomes after GI surgery. Incorporating microbiome profiling into peri-operative pathways and testing microbiome-modulating interventions are logical next steps.

Acknowledgments

We thank participating patients and peri-operative teams across all centres.

Funding

None.

Conflicts of Interest

The authors declare no competing interests.

Data Availability

De-identified data and analysis code can be made available upon reasonable request and ethics approval.

Author Contributions

Conceptualization: A.B., V.C.; Methodology: A.B., R.S.; Investigation: Site investigators; Formal analysis: R.S.; Writing—original draft: A.B., R.S.; Writing—review & editing: all authors; Supervision: V.C. (edit initials)

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