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		<title>Living Systematic Reviews: Evidence That Stays Current</title>
		<link>https://zorost.com/living-systematic-reviews-evidence-current/</link>
		
		<dc:creator><![CDATA[Zorost Intelligence]]></dc:creator>
		<pubDate>Tue, 16 Dec 2025 09:00:00 +0000</pubDate>
				<category><![CDATA[Pharmaceutical Research]]></category>
		<category><![CDATA[Benchmarking]]></category>
		<category><![CDATA[Evaluation]]></category>
		<category><![CDATA[EvidAI]]></category>
		<category><![CDATA[PRISMA 2020]]></category>
		<category><![CDATA[RAG]]></category>
		<guid isPermaLink="false">https://zorost.com/living-systematic-reviews-evidence-current/</guid>

					<description><![CDATA[<p>A traditional systematic review is a snapshot, frozen at the search date. A living review is a stream, refreshed as new evidence appears. Here is the architecture that makes living reviews operationally feasible.</p>
<p>The post <a href="https://zorost.com/living-systematic-reviews-evidence-current/">Living Systematic Reviews: Evidence That Stays Current</a> appeared first on <a href="https://zorost.com">Zorost Intelligence | AI, Cloud &amp; Data Experts</a>.</p>
]]></description>
										<content:encoded><![CDATA[<blockquote>
<p><strong>Pull-quote:</strong> &#8220;A review that is six months out of date is not a review. It is a historical artifact.&#8221;</p>
</blockquote>
<h4>Why this matters</h4>
<p>The fundamental flaw of the traditional systematic review is that it is a <strong>snapshot</strong>. A team works on it for six months, freezes the literature search at a date, and publishes a result that becomes outdated the moment the next paper appears. In rapidly evolving fields — oncology, infectious disease, AI/ML methodology, certain rare-disease indications — that lag is unacceptable.</p>
<p>The fix is a <strong>living systematic review</strong> — a review that is continuously refreshed as new evidence appears.</p>
<h4>What &#8220;living&#8221; actually requires</h4>
<p>Living reviews are not just &#8220;running the search again every quarter.&#8221; They require:</p>
<ol>
<li><strong>Protocol stability</strong> — the inclusion / exclusion criteria do not change between updates</li>
<li><strong>Federated search at scheduled cadence</strong> across the full database set</li>
<li><strong>Delta detection</strong> — what&#8217;s new since the last update</li>
<li><strong>Consistent screening</strong> — the same multi-agent consensus applied to new papers</li>
<li><strong>Risk-of-bias and GRADE re-assessment</strong> — if a new high-quality study changes the certainty of evidence, that needs to surface</li>
<li><strong>Versioned reporting</strong> — each refresh produces a versioned report with a clear changelog</li>
<li><strong>Subscriber notification</strong> — stakeholders are alerted when something material changes</li>
</ol>
<p>This is not a research methodology improvement. It is an engineering problem: how to do high-rigor evidence synthesis on a recurring schedule, with reproducibility and auditability preserved.</p>
<h4>Architecture</h4>
<p>EvidAI&#8217;s living review architecture:</p>
<pre><code>Protocol (versioned) ──► Federated search (11 databases, scheduled)
                                          │
                                          ▼
                              Delta detection
                                          │
                          New papers since last refresh
                                          │
                                          ▼
                       Multi-agent consensus screening
                                          │
                          Included papers (new)
                                          │
                                          ▼
                  Risk-of-bias (RoB 2 / ROBINS-I / NOS)
                                          │
                                          ▼
                  GRADE re-assessment per outcome
                                          │
                                          ▼
                  Living report (versioned, with changelog)
                                          │
                                          ▼
                  Subscriber notifications</code></pre>
<h4>What changes for the team</h4>
<p>The team&#8217;s role shifts from &#8220;run a six-month review every two years&#8221; to &#8220;monitor a continuously updated review and adjudicate the small fraction of decisions the AI escalated.&#8221; That is a fundamentally different work pattern, and it scales.</p>
<h4>Closing</h4>
<p>A review that is six months out of date is not a review. Living reviews are an engineering solution to a research methodology problem — and they are now operationally feasible.</p>
<hr>
<p>The post <a href="https://zorost.com/living-systematic-reviews-evidence-current/">Living Systematic Reviews: Evidence That Stays Current</a> appeared first on <a href="https://zorost.com">Zorost Intelligence | AI, Cloud &amp; Data Experts</a>.</p>
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