Improving the Measurement of Surgical Site Infection Risk Stratification/Outcome Detection

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Appendix F. Algorithm

Figure 1. Final CABG Algorithm

Figure 1. Final CABG Algorithm. Graphic illustrating classification tree branching for the final CABG algorithm as described in the final report narrative.

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Figure 2. Correlation and Cross-validation error for CABG Algorithm

Figure 2. Correlation and Cross-validation error for CABG Algorithm. Correlation and cross-validation error graphs for CABG, depicting R-square and X-relative error values (y-axis) by number of splits (x-axis).

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Figure 3. Final Algorithm for Herniorrhaphy

Figure 3. Final Algorithm for Herniorrhaphy. Graphic illustrating classification tree branching for the final herniorrhaphy algorithm as described in the final report narrative.

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Figure 4. Correlation and Cross Validation Error for Herniorrhaphy

Figure 4. Correlation and Cross Validation Error for Herniorrhaphy. Correlation and cross-validation error graphs for herniorrhaphy, depicting R-square and X-relative error values (y-axis) by number of splits (x-axis).

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Figure 5. Unpruned Algorithm for TKA

Figure 5. Unpruned Algorithm for TKA. Graphic illustrating classification tree branching for the unpruned TKA algorithm as described in the final report narrative.

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Figure 6. Correlation and Cross Validation Error for TKA

Figure 6. Correlation and Cross Validation Error for TKA. Correlation and cross-validation error graphs for TKA, depicting R-square and X-relative error values (y-axis) by number of splits (x-axis).

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Figure 7. Final Algorithm for TKA

Figure 7. Final Algorithm for TKA. Graphic illustrating classification tree branching for the final TKA algorithm as described in the final report narrative.

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Figure 8. Final Algorithm for THA

Figure 8. Final Algorithm for THA. Graphic illustrating classification tree branching for the final THA algorithm as described in the final report narrative.

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Figure 9. Correlation and Cross Validation Error for THA

Figure 9. Correlation and Cross Validation Error for THA. Correlation and cross-validation error graphs for THA, depicting R-square and X-relative error values (y-axis) by number of splits (x-axis).

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Algorithms That Include sSSI

Rules using similar protocols as that above that included superficial SSI for training did not perform as well.

Table 1. Preliminary Performance on Training Set (includes sSSI)

	CABG	HIP	KNEE	HERNIA
Total	4525	19692	7467	3867
Algorithm Positive	747	2238	1980	311
True Positive	116	220	103	78
False Negative	28	19	6	17
Algorithm Sensitivity	80.6	92.1	94.4	82.1
% Excluded	83.5	88.6	73.5	91.2
NNR Algorithm	6.4	10.2	19.2	4
NNR sans Algorithm	39	89.5	72.5	49.6

CABG - Coronary Artery Bypass Grafting, HERNIA - herniorraphy, KNEE - Total Knee Arthroplasty, HIP - Total Hip Arthroplasty, NNR - number needed to read

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Figure 10. Algorithm for CABG (includes sSSI)

Figure 10. Algorithm for CABG (includes sSSI). Graphic illustrating classification tree branching for the CABG algorithm including sSSI, as described in the final report narrative.

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Figure 11. Algorithm for Herniorrhaphy (Includes sSSI)

Figure 11. Algorithm for Herniorrhaphy (Includes sSSI). Graphic illustrating classification tree branching for the herniorraphy algorithm including sSSI, as described in the final report narrative.

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Figure 12. Algorithm for TKA (Includes sSSI)

Figure 12. Algorithm for TKA (Includes sSSI). Graphic illustrating classification tree branching for the TKA algorithm including sSSI, as described in the final report narrative.

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Figure 13. Algorithm for THA (Includes sSSI)

Figure 13. Algorithm for THA (Includes sSSI). Graphic illustrating classification tree branching for the THA algorithm including sSSI, as described in the final report narrative.

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