ArticleIndian journal of thoracic and cardiovascular surgery2025
Descriptive statistics for cardiothoracic surgeons: part 2 - the foundation of data interpretation.
Article in Indian journal of thoracic and cardiovascular surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Basic Microbiome Analysis: Analytical Steps from Sampling to Sequencing.Microorganisms · 2026Review
- A robust pressure drop prediction model in vertical multiphase flow: a machine learning approach.Scientific reports · 2025Article
- Regression analysis for cardiothoracic surgeons: part 5-predicting risks and outcomes in surgery.Indian journal of thoracic and cardiovascular surgery · 2025Article
- Correlation and causation for cardiothoracic surgeons: part 4-distinguishing relationships in data.Indian journal of thoracic and cardiovascular surgery · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Descriptive statistics are essential for summarizing and interpreting clinical data in cardiothoracic surgery. Understanding measures of central tendency and dispersion, such as mean, median, range, variance, and standard deviation, provides insights into patient outcomes and surgical effectiveness. Confidence intervals offer a range for population parameters, enhancing decision-making precision. Data visualization tools like histograms, box plots, and scatter plots illustrate distributions and relationships. Interpreting tables and figures accurately, recognizing biases, and evaluating statistical validity are crucial for applying research findings to clinical practice. These statistical tools ultimately support evidence-based practice and ensure informed decision-making by clinicians.
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Registered trials
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.