Systematic Review Overview

What a systematic review is in Paperguide

A systematic review answers a research question by following a protocol you define in advance: what makes a study eligible, what data you pull from it, and how you decide. The method has to be transparent enough that someone else could repeat it and reach the same result.

Paperguide runs that method as AI-led with human verification:

• Paperguide AI does the work. It evaluates your research question, drafts your eligibility criteria and extraction fields, searches for papers, screens abstracts and full texts against your criteria, extracts your defined data, and synthesizes the report.
• A person verifies every stage. AI decisions are proposals, not conclusions. An assigned member reviews each one alongside the evidence AI cited, overrides anything they disagree with, and confirms the stage before the next one unlocks.
• Everything is recorded. Every screening decision keeps both what AI decided and what a human changed, and every extracted value links to the statement in the source it came from.

That last point is what makes the output defensible. A systematic review is only as good as its audit trail.

How the workflow runs

A systematic review moves through six stages in order. Each one unlocks when the stage before it is confirmed.

Creating a systematic review

Creating a review takes two steps. Setting up your team comes straight after.

Step 1: Enter your research question

Your research question is the single entry point. Everything downstream is built from it, including the criteria and extraction fields Paperguide AI later suggests for your protocol, so it is worth getting right before you move on.

Enter it as free text. For example:

In adults with type 2 diabetes, do GLP-1 receptor agonists reduce major adverse cardiovascular events compared with standard care?

Paperguide AI evaluates your question as you enter it. There is no button to press. AI reads the question, identifies what is missing, and surfaces enhancement options based on the gaps it finds. A question with no defined population or no stated comparator will come back with suggestions for both.

Apply the ones that fit and ignore the ones that do not. You know your field better than the model does.

Step 2: Choose which screening stages to run

Two customization options decide the shape of your review. Each one turns a screening stage on or off.

Most reviews should keep both enabled. Two screening passes is the standard method, and skipping one weakens what you can claim about how papers were selected.

Skipping is worth considering in narrow cases. If you are starting from a small, already-curated set of papers, abstract screening may add little. If your criteria can be settled from abstracts alone, full text screening may not earn its cost.

Once these are set, the systematic review is created and the stages become available.

Step 3: Set up your team

Add the people working on the review and give each of them a role. You do this from the Members and Settings tabs of the systematic review. Learn more

• Members tab. Add people and set their access: Full Access, Review, or View.
• Settings tab. Assign verifiers to the stages each person is responsible for.

You can do this at any point, including later in the review. Do it before screening starts if you can, so responsibilities are clear from the first stage.

You can also run a systematic review alone. If you do, you verify each stage yourself.

What happens next

The review now exists, and the first stage, Protocol, is open. From here the work happens inside the stages themselves, each on its own page:

Protocol → Papers → Title & Abstract Screening → Full Text Screening → Data Extraction → Report

The report

Once data extraction is confirmed, Paperguide generates the systematic review report. This is the final output of the review and the document you take forward.

The report contains:

• The synthesized findings. Paperguide AI analyses the data extracted across all included papers and writes up what it shows, rather than listing each study in turn.
• The methodology. A record of how the review was conducted: your research question, eligibility criteria, extraction fields, and the counts at every stage.
• The PRISMA diagram. Explained below.

Synthesis draws only on data that survived screening and was confirmed during extraction. Nothing enters the report that a person has not verified.

Read the report as a draft to work from, not a finished manuscript. It documents what your review found and how it got there. Interpretation, discussion, and the argument you build on top of the evidence are still yours to write.

The PRISMA diagram

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is the reporting standard for systematic reviews. Its flow diagram shows how many records you started with and how many survived each stage, so a reader can see exactly where papers were lost and why.

Paperguide builds the diagram automatically from your review. Every number in it comes from work you already did:

Because the diagram is generated from your actual screening decisions, it stays accurate as those decisions change. If a verifier overrides an exclusion, the counts move with it.

Audit trail and logs

Every action in a systematic review is logged. This is what lets you show not just what your review concluded, but how it got there and who was responsible at each point.

Per-paper history. Every paper carries a record of everything that happened to it: when it was added and from which source, its abstract screening decision and the evidence behind it, its full text screening decision, and the data extracted from it. If a reviewer questions why a specific study was excluded, the answer is on the paper itself.

Review audit log. The systematic review as a whole keeps a log of every action taken across it, covering all stages and all members.

Together these are what makes the review reproducible. Anyone reviewing your work can trace a single paper from collection to final decision, or follow the review as a whole from start to finish.

Exports

You can export from every stage of the systematic review, not only at the end.

Exporting at each stage is useful for two things: sharing progress with collaborators who are not in Paperguide, and keeping a copy of your screening record alongside your submission.

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Before you start

A few things worth knowing before you commit to a review.

Set up your protocol first. Criteria and extraction fields should be settled before screening begins. Editing the protocol mid-review overrides existing data and forces you to restart each stage in order. It is possible, but it is not something you want to discover halfway through.

Papers need PDFs for full text screening. Any paper without an attached PDF is marked ineligible at that stage. You can add PDFs later, or use the Paperguide browser extension to fetch them, including through your institution's proxy.

Order your criteria deliberately. When a paper fails screening, the first criterion it fails, in the order you listed them, becomes its exclusion reason. Put your broadest, most decisive criteria first.

Write instructions, not labels. AI screens and extracts based on what your criteria and fields tell it to look for. "Study design" is a label. "Identify the study design and include only randomized controlled trials with a parallel-group design" is an instruction.

Assign your verifiers before each stage starts. Verification is what advances the review. A stage with no assigned verifier will sit and wait once the AI run finishes.

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AI credits

Every AI task in a systematic review draws on your AI credit allowance: question enhancement aside, that covers protocol generation, search, abstract screening, full text screening, data extraction, and report synthesis. There is no separate systematic review allowance.

Research question enhancement is the one exception. It does not consume credits, so you can refine your question as many times as you need before creating the review.