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Table 1 Characteristics of study participants for nMI, UM, and SM (n = 2,207)

From: Machine learning approaches classify clinical malaria outcomes based on haematological parameters

Characteristic Non-malaria infections (nMI) Uncomplicated malaria (UM) Severe malaria (SM)  
N = 2,207 N = 978 (44.3%) N = 703 (31.8%) N = 526 (23.8%) P value
Patient age
 Mean (SD) 4.23 (3.57) 4.95 (3.57) 1.66 (0.93) < 0.001a
 Median (range) 3.0 (2–6) 4.0 (2–7) 1.0 (1–2)  
Body temperature
 Mean (SD) 37.4 (1.18) 38.1 (1.23) 38.4 (1.15) < 0.001a
 Median (range) 37.2 (36.5–38.4) 38.1 (37–39) 38.3 (37.5–39.2)  
Parasite density
 Geometric mean (SD) 0 0 27,467.59 8.44 16,674.41 8.61 0.592c
 Median (range) 0 0 29,426 3,144–105,351 25,160 3,560–86,560  
Location
 Accra (n, %) 657 (67.2%) 200 (28.4%) 0 (0.0%) < 0.001b
 Kintampo (n, %) 321 (32.8%) 405 (57.6%) 0 (0.0%)  
 Navrongo (n, %) 0.0 (0.0%) 98 (13.9%) 526 (100.0%)  
Sex
 Female (n, %) 477 (48.8%) 317 (45.1%) 236 (44.9%) 0.209 b
 Male (n, %) 501 (51.2%) 386 (54.9%) 290 (55.1%)  
Fever symptom
 No (n, %) 395 (40.4%) 97 (13.8%) 4 (0.8%) < 0.001 b
 Yes (n, %) 581 (59.4%) 601 (85.5%) 522 (99.2%)  
 Missing (n, %) 2 (0.2%) 5 (0.7%) 0 (0%)  
  1. Patient age, body temperature, and parasite density were analysed using the Kruskal-Wallis test while recruitment location, sex, and fever were analysed using the chi-square test at 95% CI. All the participant characteristics were significantly different between the nMI, UM, and SM except median parasite density and patient sex
  2. aKruskal-Wallis test
  3. bChi-square test
  4. cDunn (1964) Kruskal-Wallis multiple comparison—UM vs SM only