Clinical data analysis for publication — GistiQ

Who it's for

Physician — preparing an article for a journal

Postgraduate — working on a dissertation

Researcher — conducting a clinical study

Department head — analyzing treatment outcomes

The data is there — Excel with hundreds of patients. To turn it into a publication, you need R/SPSS/Stata, the ability to choose the right test, build charts to journal standards, format tables. ChatGPT can explain how to calculate — but cannot actually run calculations on your data, build a real chart, and deliver a ready file.

What you can upload

+Excel/CSV with patient data — any volume+Study protocol — to understand design and endpoints+Journal formatting requirements (link or PDF)+Already written article sections — for results integration

Confidentiality: GistiQ is deployed on your own or rented server — patient data never leaves your perimeter. No data is shared with third parties.

What it can do

Statistical analysis

Descriptive statistics: medians, quartiles, frequencies — Table 1 per CONSORT/STROBE standard. Group comparison: t-test, Mann-Whitney, chi-square, Fisher — with automatic test selection based on distribution. Survival analysis: Kaplan-Meier curves, log-rank test, Cox regression — hazard ratio with confidence intervals. Logistic regression, multivariate analysis, odds ratio. Processing hundreds and thousands of records — not 10 rows in a chat context.

Publication-ready charts

Kaplan-Meier curves with "at risk" table, p-value, median survival
Forest plots for meta-analyses and subgroup analyses
ROC curves with AUC
Box plots, violin plots for group comparison
All charts in journal-accepted quality — PNG 300 dpi, SVG, PDF

Tables

Table 1 (baseline characteristics) — automatically, with p-value between groups
Results tables with OR/HR, 95% CI, p-value
LaTeX formatting — ready to copy into an article
Export to Word/Excel for further work

Verification and supplementation

GistiQ checks ClinicalTrials.gov — whether a similar study is registered. Conducts deep research and finds articles with similar design — for the Discussion section. Suggests: which test is correct, whether the sample size is sufficient, whether there is bias.

Example

A cardiologist conducted a retrospective study: 340 patients with CHF, two groups — standard therapy vs. standard + dapagliflozin. Uploads Excel: age, sex, LVEF, NT-proBNP, creatinine, events (death, hospitalization), dates.
GistiQ builds Table 1 per CONSORT — groups are balanced, p-value for each parameter. Draws Kaplan-Meier curves for the composite endpoint (death + hospitalization) — HR 0.74 (95% CI 0.58–0.95), p=0.017. Forest plot by subgroups: age ≥65 / <65, EF ≤30% / >30%, DM yes/no. Multivariate Cox regression — dapagliflozin remains significant after adjustment. GistiQ checks ClinicalTrials.gov, finds 12 similar studies for Discussion.
Result: complete statistical report in PDF, all charts — 300 dpi PNG + SVG, tables — LaTeX + Excel. Everything in the cloud, organized by sections.