PMID- 23388451
OWN - NLM
STAT- MEDLINE
DCOM- 20130913
LR  - 20161018
IS  - 1437-4331 (Electronic)
IS  - 1434-6621 (Linking)
VI  - 51
IP  - 4
DP  - 2013 Apr
TI  - A novel weighted cumulative delta-check method for highly sensitive detection of 
      specimen mix-up in the clinical laboratory.
PG  - 781-9
LID - 10.1515/cclm-2012-0752 [doi]
AB  - BACKGROUND: We sought to detect specimen mix-up by developing a new cumulative 
      delta-check method applicable to a mixture of test items with heterogeneous units 
      and distribution patterns. METHODS: The distributions of all test results were 
      successfully made Gaussian using power transformation. Values were then 
      standardized into z-score (zx) based on reference interval (RI) so that limits of 
      RI take zx=+/-1.96. To find a weight for summing absolute value of delta between 
      current and previous zx (Dz), we evaluated the distribution of Dz. Its central 
      portion was always regarded as Gaussian despite the presence of symmetrical long 
      tails. Thus, an adjusted SD (aSD) representing the center was estimated with an 
      iterative method. By setting 1/aSD2 as a weight factor, we computed a weighted 
      mean of Dz as an index for specimen mix-up (wCDI). RESULTS: The performance of 
      wCDI was evaluated, using a model laboratory database consisting of 32 basic test 
      items, by a simulation study generating artificial cases of mix-up. When wCDI was 
      computed from three commonly ordered test sets consisting of 6-9 items each, its 
      diagnostic efficiency in detecting the artificial cases was 0.937-0.967 expressed 
      as area under ROC curves (AUC). When the performance of wCDI was evaluated simply 
      by the number of test items (p) included in the computation, AUC gradually 
      increased from 0.944 (p=5) to 0.976 (p=8). However, when p>/=10, AUC stayed at 
      approximately 0.98. CONCLUSIONS: wCDI was proven to be highly effective in 
      uncovering cases of specimen mix-up. The diagnostic efficiency of wCDI depends 
      only on the number of test items included in the computation.
FAU - Yamashita, Teppei
AU  - Yamashita T
AD  - Graduate School of Health Care Science, Jikei Institute, Osaka, Japan.
FAU - Ichihara, Kiyoshi
AU  - Ichihara K
FAU - Miyamoto, Ayaho
AU  - Miyamoto A
LA  - eng
PT  - Journal Article
PL  - Germany
TA  - Clin Chem Lab Med
JT  - Clinical chemistry and laboratory medicine
JID - 9806306
SB  - IM
MH  - Area Under Curve
MH  - Clinical Laboratory Information Systems/standards
MH  - Data Mining
MH  - Humans
MH  - Laboratories, Hospital/*standards
MH  - Normal Distribution
MH  - Quality Control
MH  - ROC Curve
MH  - Reference Values
EDAT- 2013/02/08 06:00
MHDA- 2013/09/14 06:00
CRDT- 2013/02/08 06:00
PHST- 2012/11/04 00:00 [received]
PHST- 2013/01/08 00:00 [accepted]
PHST- 2013/02/08 06:00 [entrez]
PHST- 2013/02/08 06:00 [pubmed]
PHST- 2013/09/14 06:00 [medline]
AID - /j/cclm.ahead-of-print/cclm-2012-0752/cclm-2012-0752.xml [pii]
AID - 10.1515/cclm-2012-0752 [doi]
PST - ppublish
SO  - Clin Chem Lab Med. 2013 Apr;51(4):781-9. doi: 10.1515/cclm-2012-0752.