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. 2024 Dec 27;19(12):e0315253. doi: 10.1371/journal.pone.0315253

Table 5. Diagnostic performance of current and identified optimal MUAC cutoffs and evaluated alternative case definitions for severe wasting.

Categories Severe Wasting
Cutoff (cm) AUROC (LB-UB) Sensitivity Specificity PPV NPV
All children Current (<11.5cm) 0.558 (0.539–0.576) 12.62% 98.92% 10.66% 99.10%
  <13.6 0.690 (0.662–0.717) 61.81% 76.09% 2.58% 99.49%
  <13.4 or WAZ <-3 0.752 (0.727–0.777) 72.17% 78.26% 3.28% 99.64%
  <11.6 or WAZ <-2 0.801 (0.779–0.823) 80.58% 79.62% 3.89% 99.75%
Age (months) 
6–23 m <11.5cm 0.598 (0.562–0.633) 22.22% 97.29% 11.19% 98.79%
  <13.0 0.650 (0.607–0.692) 55.56% 74.40% 3.23% 99.09%
24–59 <11.5cm 0.524 (0.507–0.540) 5.17% 99.58% 9.18% 99.23%
  <14.5 0.698 (0.667–0.729) 78.16% 61.47% 1.62% 99.71%
Sex 
Male <11.5cm 0.567 (0.541–0.592) 14.13% 99.17% 16.77% 98.99%
  <13.7 0.704 (0.669–0.738) 65.22% 75.49% 3.04% 99.46%
Female <11.5cm 0.545 (0.518–0.572) 10.40% 98.64% 6.16% 99.23%
  <13.4 0.683 (0.641–0.726) 63.20% 73.48% 2.00% 99.57%
Weight-for-age z-score (underweight status)
≤ -3SD (Severe) <11.5cm 0.562 (0.528–0.596) 20.95% 91.43% 28.18% 87.81%
  <12.0 0.588 (0.547–0.628) 35.14% 82.43% 24.30% 88.79%
-2SD < z ≤ -3SD (Moderate) <11.5cm 0.525 (0.499–0.550) 7.00% 97.93% 6.25% 98.16%
  <13.6 0.564 (0.516–0.613) 60.00% 52.87% 2.45% 98.53%
2SD < z ≤ -2SD (Normal) <11.5cm 0.505 (0.489–0.521) 1.64% 99.40% 0.70% 99.75%
  <14.2 0.611 (0.548–0.673) 55.74% 66.37% 0.42% 99.83%
Height-for-age z-score (stunting status)
≤ -3SD (Severe) <11.5cm 0.665 (0.595–0.734) 36.17% 96.82% 16.67% 98.85%
  <12.7 0.797 (0.738–0.857) 78.72% 80.70% 6.69% 99.54%
-2SD < z ≤ -3SD (Moderate) <11.5cm 0.561 (0.510–0.612) 13.64% 98.57% 5.61% 99.46%
  <13.4 0.707 (0.637–0.777) 68.18% 73.21% 1.56% 99.73%
2SD < z ≤ -2SD (Normal <11.5cm 0.533 (0.516–0.551) 7.34% 99.31% 10.19% 99.02%
  <14.5 0.683 (0.655–0.711) 77.52% 59.05% 1.98% 99.60%

Note: AUROC = Area Under the Receiver-Operator Characteristic Curve; LB = Lower bound; UB = Upper bound; PPV = Positive predictive value; NPV = Negative predictive value