Evidence map›Paper›PMID 36191941›Full record

ArticleCMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne2022

Predicting major complications in patients undergoing laparoscopic and open hysterectomy for benign indications.

Krupa Madhvani, Silvia Fernandez Garcia, Borja M Fernandez-Felix, Javier Zamora, Tyrone Carpenter, Khalid S Khan

Abstract read
In one paragraph

Article in CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Krupa MadhvaniBarts and the London School of Medicine and Dentistry (Madhvani), Queen Mary University of London, London, UK; University Hospitals Dorset (Carpenter), NHS Foundation Trust, UK; Clinical Biostatistics Unit, Hospital Ramón y Cajal (IRYCIS) (Fernandez Garcia, Fernandez-Felix, Zamora); CIBER Epidemiology and Public Health (Fernandez-Felix, Zamora, Khan), Madrid, Spain; WHO Collaborating Centre for Global Women's Health (Zamora), Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK; Department of Preventative Medicine and Public Health (Khan), Faculty of Medicine, University of Granada, Spain krupa.madhvani@nhs.net.
Silvia Fernandez GarciaBarts and the London School of Medicine and Dentistry (Madhvani), Queen Mary University of London, London, UK; University Hospitals Dorset (Carpenter), NHS Foundation Trust, UK; Clinical Biostatistics Unit, Hospital Ramón y Cajal (IRYCIS) (Fernandez Garcia, Fernandez-Felix, Zamora); CIBER Epidemiology and Public Health (Fernandez-Felix, Zamora, Khan), Madrid, Spain; WHO Collaborating Centre for Global Women's Health (Zamora), Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK; Department of Preventative Medicine and Public Health (Khan), Faculty of Medicine, University of Granada, Spain.
Borja M Fernandez-FelixBarts and the London School of Medicine and Dentistry (Madhvani), Queen Mary University of London, London, UK; University Hospitals Dorset (Carpenter), NHS Foundation Trust, UK; Clinical Biostatistics Unit, Hospital Ramón y Cajal (IRYCIS) (Fernandez Garcia, Fernandez-Felix, Zamora); CIBER Epidemiology and Public Health (Fernandez-Felix, Zamora, Khan), Madrid, Spain; WHO Collaborating Centre for Global Women's Health (Zamora), Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK; Department of Preventative Medicine and Public Health (Khan), Faculty of Medicine, University of Granada, Spain.
Javier ZamoraBarts and the London School of Medicine and Dentistry (Madhvani), Queen Mary University of London, London, UK; University Hospitals Dorset (Carpenter), NHS Foundation Trust, UK; Clinical Biostatistics Unit, Hospital Ramón y Cajal (IRYCIS) (Fernandez Garcia, Fernandez-Felix, Zamora); CIBER Epidemiology and Public Health (Fernandez-Felix, Zamora, Khan), Madrid, Spain; WHO Collaborating Centre for Global Women's Health (Zamora), Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK; Department of Preventative Medicine and Public Health (Khan), Faculty of Medicine, University of Granada, Spain.
Tyrone CarpenterBarts and the London School of Medicine and Dentistry (Madhvani), Queen Mary University of London, London, UK; University Hospitals Dorset (Carpenter), NHS Foundation Trust, UK; Clinical Biostatistics Unit, Hospital Ramón y Cajal (IRYCIS) (Fernandez Garcia, Fernandez-Felix, Zamora); CIBER Epidemiology and Public Health (Fernandez-Felix, Zamora, Khan), Madrid, Spain; WHO Collaborating Centre for Global Women's Health (Zamora), Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK; Department of Preventative Medicine and Public Health (Khan), Faculty of Medicine, University of Granada, Spain.
Khalid S KhanBarts and the London School of Medicine and Dentistry (Madhvani), Queen Mary University of London, London, UK; University Hospitals Dorset (Carpenter), NHS Foundation Trust, UK; Clinical Biostatistics Unit, Hospital Ramón y Cajal (IRYCIS) (Fernandez Garcia, Fernandez-Felix, Zamora); CIBER Epidemiology and Public Health (Fernandez-Felix, Zamora, Khan), Madrid, Spain; WHO Collaborating Centre for Global Women's Health (Zamora), Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK; Department of Preventative Medicine and Public Health (Khan), Faculty of Medicine, University of Granada, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHysterectomy, the most common gynecological operation, requires surgeons to counsel women about their operative risks. We aimed to develop and validate multivariable logistic regression models to predict major complications of laparoscopic or abdominal hysterectomy for benign conditions.

methodsWe obtained routinely collected health administrative data from the English National Health Service (NHS) from 2011 to 2018. We defined major complications based on core outcomes for postoperative complications including ureteric, gastrointestinal and vascular injury, and wound complications. We specified 11 predictors a priori. We used internal-external cross-validation to evaluate discrimination and calibration across 7 NHS regions in the development cohort. We validated the final models using data from an additional NHS region.

resultsWe found that major complications occurred in 4.4% (3037/68 599) of laparoscopic and 4.9% (6201/125 971) of abdominal hysterectomies. Our models showed consistent discrimination in the development cohort (laparoscopic, C-statistic 0.61, 95% confidence interval [CI] 0.60 to 0.62; abdominal, C-statistic 0.67, 95% CI 0.64 to 0.70) and similar or better discrimination in the validation cohort (laparoscopic, C-statistic 0.67, 95% CI 0.65 to 0.69; abdominal, C-statistic 0.67, 95% CI 0.65 to 0.69). Adhesions were most predictive of complications in both models (laparoscopic, odds ratio [OR] 1.92, 95% CI 1.73 to 2.13; abdominal, OR 2.46, 95% CI 2.27 to 2.66). Other factors predictive of complications included adenomyosis in the laparoscopic model, and Asian ethnicity and diabetes in the abdominal model. Protective factors included age and diagnoses of menstrual disorders or benign adnexal mass in both models and diagnosis of fibroids in the abdominal model.

interpretationPersonalized risk estimates from these models, which showed moderate discrimination, can inform clinical decision-making for people with benign conditions who may require hysterectomy.

Indexed as

LaparoscopyState MedicineFemaleHumansHysterectomyPostoperative ComplicationsRetrospective Studies

Identifiers

PMID36191941
PMCPMC9529570

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.