Comparison of kinemyography and electromyography during spontaneous recovery from non-depolarising neuromuscular blockade

This study compared two commercially available quantitative neuromuscular function monitoring techniques, kinemyography (KMG) and electromyography (EMG), to assess whether KMG could be used interchangeably with EMG to exclude residual neuromuscular blockade (RNMB). Train-of-four (TOF) ratios were recorded every 20 seconds using KMG at the adductor pollicis and EMG at the first dorsal interosseous of the same hand during spontaneous recovery from shallow neuromuscular blockade. TOF ratios were compared using Bland-Altman analysis for repeated measurements. The precision of each device was assessed by the repeatability coefficient. Agreement between devices was assessed by the bias and limits of agreement. Clinically acceptable agreement was defined as a bias <0.025 within limits of agreement ±0.05. We recorded 629 sets of TOF ratios from 23 patients. The repeatability coefficient for KMG was 0.05 (95% confidence interval [CI] 0.05 to 0.06) and for EMG 0.10 (95% CI 0.10 to 0.11). Overall, the bias of KMG TOF ratios against EMG TOF ratios was 0.11 (95% CI 0.10 to 0.12), with limits of agreement -0.11 to 0.32. In the 0.80 to 0.99 TOF range, the bias was 0.08 (95% CI 0.06 to 0.09) and the limits of agreement were -0.12 to 0.27. Overall, TOF ratios measured by KMG were on average 0.11 higher than EMG. In the 0.80 to 0.99 TOF range, KMG TOF ratios were 0.08 higher. EMG and KMG are not interchangeable because the bias is large and the limits of agreement are wide. Thus a maximum TOF ratio of 1.0 on KMG may not exclude RNMB

Epidemiology of Peripheral Lymph Node Tuberculosis and Genotyping of <i>M</i>. <i>tuberculosis</i> Strains: A Case-Control Study

<div><p>Background</p><p>This study examined potential risk factors of lymph node tuberculosis (LNTB), including phylogenetic lineages of <i>Mycobacterium tuberculosis</i> (MTB), in comparison to pulmonary tuberculosis (PTB) in a setting with an ethnically diverse population.</p><p>Methods</p><p>We conducted a case-control study at a major tuberculosis clinic in Sydney, Australia, which included all patients with peripheral LNTB seen at the clinic between 2000 and 2012. Controls were randomly selected patients with PTB seen at the same clinic during the study period. Epidemiological data were extracted from the hospital electronic database and medical records. Associations between LNTB and age, sex, ethnicity, comorbidities and phylogenetic lineages of MTB in comparison to PTB were examined using logistic regression in univariate and multivariate analyses.</p><p>Results</p><p>There were 212 cases with LNTB and 424 randomly selected controls with PTB. Among patients with LNTB, 74% were female and the mean age (standard deviation, SD) was 42 (16) years. Among patients with PTB, 43% were female and the mean age was 44 (22) years. Females, 45 to 64-year-olds and Southern Asians had an increased risk for LNTB (OR 3.13, 95% CI 2.10-4.67; OR 2.50, 95% CI 1.29-4.84; OR 3.95, 95% CI 1.54-10.12 respectively). Patients with diabetes were at a higher risk of PTB (OR 0.40, 95% CI 0.19 – 0.83 for LNTB). A subset analysis showed that patients infected with the East African Indian strain of MTB were more likely to develop LNTB (OR 10.07, 95% CI 2.37-42.77).</p><p>Conclusions</p><p>An increased risk for LNTB (but still lower rates than for PTB) was found among females, people aged 45 to 64 years and people born in Southern Asia. An increased risk for PTB was found among patients with diabetes. The East African Indian strain of MTB was significantly associated with a higher likelihood of LNTB compared to other MTB strains.</p></div

Patient characteristics and associations with LNTB in multivariate analysis.

<p>Patient characteristics and associations with LNTB in multivariate analysis.</p

Ratio of females to males in LNTB cohorts of published studies.

<p>Ratio of females to males in LNTB cohorts of published studies.</p

Subset multivariate analysis including cases with MTB genotyping, associations with LNTB in multivariate analysis.

<p>Subset multivariate analysis including cases with MTB genotyping, associations with LNTB in multivariate analysis.</p

Patient characteristics and associations with LNTB in multivariate analysis.

<p>Patient characteristics and associations with LNTB in multivariate analysis.</p