diff --git a/src/core/pagerankGraph.js b/src/core/pagerankGraph.js
index 5cd0ae8..e4afcba 100644
--- a/src/core/pagerankGraph.js
+++ b/src/core/pagerankGraph.js
@@ -26,7 +26,6 @@ import {
   findStationaryDistribution,
   type PagerankParams,
   type PagerankOptions as CorePagerankOptions,
-  uniformDistribution,
 } from "../core/attribution/markovChain";
 import * as NullUtil from "../util/null";
 
@@ -456,9 +455,13 @@ export class PagerankGraph {
    * individual delta in a node's score between the present and previous
    * iteration is less than or equal to `options.convergenceThreshold`.
    *
-   * TODO(#1020): Make `runPagerank` use the current nodes' scores as a
-   * starting point for computation, rather than re-generating from
-   * scratch every time `runPagerank` is called.
+   * Note that if runPagerank is called multiple times on the same
+   * PagerankGraph, it will re-use the last stationary distribution as the
+   * starting point for running PageRank again. In general, this will result in
+   * improved performance, and it will not usually affect the outcome from
+   * PageRank. However, in certain circumstances, it could result in different
+   * outputs. For example, if there are isolated nodes and no seed vector, then
+   * the initial distribution may matter.
    */
   async runPagerank(
     options?: PagerankOptions
@@ -476,11 +479,15 @@ export class PagerankGraph {
       this._syntheticLoopWeight
     );
     const osmc = createOrderedSparseMarkovChain(connections);
+    const pi0 = new Float64Array(osmc.chain.length);
+    osmc.nodeOrder.forEach(
+      (n: NodeAddressT, i) => (pi0[i] = NullUtil.get(this.node(n)).score)
+    );
     const params: PagerankParams = {
       chain: osmc.chain,
       alpha: fullOptions.alpha,
       seed: weightedDistribution(osmc.nodeOrder, fullOptions.seed),
-      pi0: uniformDistribution(osmc.chain.length),
+      pi0,
     };
     const coreOptions: CorePagerankOptions = {
       verbose: false,
diff --git a/src/core/pagerankGraph.test.js b/src/core/pagerankGraph.test.js
index 5158f38..44579c9 100644
--- a/src/core/pagerankGraph.test.js
+++ b/src/core/pagerankGraph.test.js
@@ -609,6 +609,22 @@ describe("core/pagerankGraph", () => {
       expect(results.convergenceDelta).toBeLessThan(convergenceThreshold);
       checkProbabilityDistribution(pg);
     });
+    it("re-uses existing scores as a starting point", async () => {
+      const pg = examplePagerankGraph();
+      const convergenceThreshold = 0.001;
+      const results1 = await pg.runPagerank({
+        maxIterations: 170,
+        convergenceThreshold,
+      });
+      expect(results1.convergenceDelta).toBeLessThan(convergenceThreshold);
+      // It should still converge without any iterations, because it uses the
+      // final distribution as a starting point
+      const results2 = await pg.runPagerank({
+        maxIterations: 0,
+        convergenceThreshold,
+      });
+      expect(results2.convergenceDelta).toEqual(results1.convergenceDelta);
+    });
   });
 
   describe("equals", () => {