| Literature DB >> 31550246 |
Aline Benjamin1, Solange Cesar Cavalcante1, Leda Fátima Jamal2, Denise Arakaki-Sanchez3, Josué Nazareno de Lima3, Jose Henrique Pilotto4,5, Francisco Ivanildo de Oliveira Junior6, Tâmara Newman Lobato Souza6, Maria Cristina Lourenço7, Maeve Brito de Mello8, Pedro Emmanuel Alvarenga Americano do Brasil9, Draurio Barreira10, Valeria Rolla1.
Abstract
BACKGROUND: Determine TB-LAM Ag (LAM) is a point of care test developed to diagnose tuberculosis (TB). The aim of this study was to evaluate the diagnostic performance of LAM in people living with HIV using Brazilian public health network algorithm for TB diagnosis. METHODS ANDEntities:
Mesh:
Year: 2019 PMID: 31550246 PMCID: PMC6759169 DOI: 10.1371/journal.pone.0221038
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Absolute and relative frequencies of clinical characteristics at TB investigation by LAM result (relative frequencies are in parenthesis, except as otherwise indicated).
| LAM | LAM | Total | Statistic Test | P Value | |
|---|---|---|---|---|---|
| 162 | 37 | 199 | |||
| Male | 100 (61.73) | 27 (72.97) | 127 (63.82) | Chisq. (1 df) = 1.198 | 0.274 |
| Female | 62 (38.27) | 10 (27.03) | 72 (36.18) | ||
| Mean (SD) | 39.76 (10.01) | 36.00 (9.16) | 39.06 (9.95) | t-test (198 df) = 2.090 | 0.038 |
| 51 (22.3,90.8) | 25 (15,39) | 42 (19,82) | Rannksum test | < 0.001 | |
| [0,50] | 81 (50.00) | 31 (83.78) | 112 (56.28) | Chi-square (2df) = 14.603 | < 0.001 |
| (50,100] | 47 (29.01) | 5 (13.51) | 52 (26.13) | ||
| (100,200] | 34 (20.99) | 1 (2.70) | 35 (17.59) | ||
| No | 66 (43.42) | 12 (34.29) | 78 (41.71) | Chi-square (2df) = 2.961 | 0.228 |
| Yes | 68 (44.74) | 21 (60.00) | 89 (47.59) | ||
| Inespecific abnormalities | 18 (11.84) | 2 (5.71) | 20 (10.70) | ||
| No | 66 (40.74) | 10 (27.03) | 76 (38.19) | Fisher's exact test | 0.137 |
| Yes | 96 (59.26) | 27 (72.97) | 123 (61.81) | ||
| No | 46 (28.40) | 10 (27.03) | 56 (28.14) | Fisher's exact test | 1 |
| Yes | 116 (71.60) | 27 (72.97) | 143 (71.86) | ||
| No | 9 (5.56) | 4 (10.81) | 13 (6.53) | Fisher's exact | 0.268 |
| Yes | 153 (94.44) | 33 (89.19) | 186 (93.47) | ||
| No | 134 (82.72) | 33 (89.19) | 167 (83.92) | Fisher's exact | 0.745 |
| Yes | 24 (14.81) | 4 (10.81) | 28 (14.07) | ||
| Don´t know | 4 (2.47) | 0 (0.00) | 4 (2.01) | ||
| No | 68 (41.98) | 17 (45.95) | 85 (42.71) | Fisher's exact | 0.768 |
| Yes | 93 (57.41) | 20 (54.05) | 113 (56.78) | ||
| Don´t know | 1 (0.62) | 0 (0.00) | 1 (0.50) | ||
| No | 121 (74.69) | 30 (81.08) | 151 (75.88) | Fisher's exact | 0.779 |
| Yes | 39 (24.07) | 7 (18.92) | 46 (23.12) | ||
| Don´t know | 2 (1.23) | 0 (0.00) | 2 (1.01) | ||
| Pulmonary | 18 (11.11) | 16 (43.24) | 34 (17.09) | Fisher's exact | 0.590 |
| Pleuropulmonary | 2 (1.23) | 0 (0.00) | 2 (1.01) | ||
| Disseminated | 6 (3.70) | 7 (18.92) | 13 (6.53) | ||
| Extrapulmonary | 0 (0.00) | 0 (0.00) | 0 (0.00) |
Fig 1Forest plot with sensitivity and specificity for different combination of tests in overall population.
Fig 2Forest plot with sensitivity and specificity for different combination of tests in different strata of CD4.