Evidence map›Paper›PMID 39269520›Full record

ArticleHernia : the journal of hernias and abdominal wall surgery2024

The impact of diabetes and presurgical glycemic control on wound morbidity following open complex abdominal wall reconstruction: a single-center experience.

Nir Messer, Benjamin T Miller, Lucas R A Beffa, Clayton C Petro, David M Krpata, Serrgio Mazzola Poli de Figueiredo, Aldo Fafaj, Li-Ching Huang, Ryan C Ellis, Sara M Maskal and 2 more

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Article in Hernia : the journal of hernias and abdominal wall surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Nir MesserCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA. masrinir@gmail.com.ORCID 0000-0002-4686-9583
Benjamin T MillerCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
Lucas R A BeffaCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
Clayton C PetroCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
David M KrpataCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
Serrgio Mazzola Poli de FigueiredoCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
Aldo FafajCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
Li-Ching HuangThe Abdominal Core Health Quality Collaborative, Centennial, USA.
Ryan C EllisCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
Sara M MaskalCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
Ajita S PrabhuCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.
Michael J RosenCleveland Clinic Center for Abdominal Core Health, Department of General Surgery, Cleveland Clinic Foundation, Cleveland, OH, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNumerous studies have identified diabetes mellites (DM) as a significant risk factor for postoperative wound morbidity, with suboptimal preoperative glycemic control (GC) posing an even greater risk. However, this data largely excludes ventral hernia patients. Our study examined the association between diabetes and preoperative GC and postoperative outcomes following open complex abdominal wall reconstruction (AWR).

methodsWe identified diabetic patients who had undergone open, elective, clean VHR with transversus abdominis release (TAR) and permanent synthetic mesh at the Cleveland Clinic Foundation between January 2014 and December 2023. Their 30-day outcomes were compared to non-diabetic patients undergoing the same procedure. Subsequently, diabetic patients were categorized based on GC. status: "Optimal GC" (HbA1c < 7%), "Sub-optimal GC" (HbA1c 7-8.4%), and "Poor GC" (HbA1c ≥ 8.5%) and their outcomes were compared.

results514 patients with DM who underwent clean elective TAR were identified, of which 431 met the inclusion criteria. GC was deemed optimal in 255 patients, sub-optimal in 128, and poor in 48 patients. Demographics were similar, except for anticoagulation treatment (p = 0.014). The entire study population exhibited significantly higher rates of wound morbidities and overall complications compared to non-diabetic patients. However, rates of surgical site infection (SSI), surgical site occurrence (SSO), SSO requiring procedural intervention (SSOPI), and reoperation did not differ significantly among the three cohorts of presurgical glycemic control (p = 0.82, p = 0.46, p = 0.51, p = 0.78), respectively. No occurrence of mesh removal was documented.

conclusionIn general, diabetes is a marker for increased wound morbidity and complications following complex abdominal wall reconstruction. However, we could not establish a hard cutoff to justify withholding surgery in symptomatic patients based on an arbitrary HbA1C level. We believe this data is important for shared decision-making when considering AWR for symptomatic ventral hernias in diabetic patients.

Indexed as

Glycemic ControlAbdominal WallAgedDiabetes MellitusFemaleGlycated HemoglobinHernia, VentralHerniorrhaphyHumansMaleMiddle AgedPostoperative ComplicationsRetrospective StudiesRisk FactorsSurgical MeshSurgical Wound InfectionGlycated HemoglobinDiabetes MellitusGlycemic controlHbA1cSurgical site infectionSurgical site occurrenceVentral herniaWound morbidity

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.