We describe a single-posture method for deriving the proportionality constant (K) between rib cage (RC) and abdominal (AB) amplifiers of the respiratory inductive plethysmograph (RIP). Qualitative diagnostic calibration (QDC) is based on equations of the isovolume maneuver calibration (ISOCAL) and is carried out during a 5-min period of natural breathing without using mouthpiece or mask. In this situation, K approximates the ratio of standard deviations (SD) of the uncalibrated changes of AB-to-RC volume deflections. Validity of calibration was evaluated by 1) analyzing RIP waveforms during an isovolume maneuver and 2) comparing changes of tidal volume (VT) amplitude and functional residual capacity (FRC) level measured by spirometry (SP) with RIP values. Comparisons of VT(RIP) to VT(SP) were also obtained in a variety of postures during natural (uninstructed) preferential RC and AB breathing and with voluntary changes of VT amplitude and FRC level. VT(RIP)-to-VT(SP) comparisons were equal to or closer than published reports for single posture, ISOCAL, multiple- and linear-regression procedures. QDC of RIP in supine posture with comparisons to SP in that posture and others showed better accuracy in horizontal than upright postures.

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OBJECTIVE To determine effects of fentanyl, lidocaine, and a fentanyl-lidocaine combination on the minimum alveolar concentration of sevoflurane preventing motor movement (MAC) in dogs. ANIMALS 6 adult Beagles. PROCEDURES Dogs were anesthetized with sevoflurane in oxygen 3 times (1-week intervals). Baseline MAC (MAC) was determined starting 45 minutes after induction of anesthesia. Dogs then received 1 of 3 treatments IV: fentanyl (loading dose, 15 μg/kg; constant rate infusion [CRI], 6 μg/kg/h), lidocaine (loading dose, 2 mg/kg; CRI, 6 mg/kg/h), and the fentanyl-lidocaine combination at the same doses. Determination of treatment MAC (MAC) was initiated 90 minutes after start of the CRI. Venous blood samples were collected at the time of each treatment MAC measurement for determination of plasma concentrations of fentanyl and lidocaine. RESULTS Mean ± SEM overall MAC for the 3 treatments was 2.70 ± 0.27 vol%. The MAC decreased from MAC to MAC by 39%, 21%, and 55% for fentanyl, lidocaine, and the fentanyl-lidocaine combination, respectively. This decrease differed significantly among treatments. Plasma fentanyl concentration was 3.25 and 2.94 ng/mL for fentanyl and the fentanyl-lidocaine combination, respectively. Plasma lidocaine concentration was 2,570 and 2,417 ng/mL for lidocaine and the fentanyl-lidocaine combination, respectively. Plasma fentanyl and lidocaine concentrations did not differ significantly between fentanyl and the fentanyl-lidocaine combination or between lidocaine and the fentanyl-lidocaine combination. CONCLUSIONS AND CLINICAL RELEVANCE CRIs of fentanyl, lidocaine, and the fentanyl-lidocaine combination at the doses used were associated with clinically important and significant decreases in the MAC of sevoflurane in dogs.

Prediction and early detection of kidney damage induced by nonsteroidal anti-inflammatories (NSAIDs) would provide the best chances of maximizing the anti-inflammatory effects while minimizing the risk of kidney damage. Unfortunately, biomarkers for detecting NSAIDinduced kidney damage in cats remain to be discovered. To identify potential urinary biomarkers for monitoring NSAID-based treatments, we applied an untargeted metabolomics approach to urine collected from cats treated repeatedly with meloxicam or saline for up to 17 days. Applying multivariate analysis, this study identified a panel of seven metabolites that discriminate meloxicam treated from saline treated cats. Combining artificial intelligence machine learning algorithms and an independent testing urinary metabolome data set from cats with meloxicam-induced kidney damage, a panel of metabolites was identified and validated. The panel of metabolites including tryptophan, tyrosine, taurine, threonic acid, pseudouridine, xylitol and lyxitol, successfully distinguish meloxicam-treated and saline-treated cats with up to 75-100% sensitivity and specificity. This panel of urinary metabolites may prove a useful and non-invasive diagnostic tool for monitoring potential NSAID induced kidney injury in feline patients and may act as the framework for identifying urine biomarkers of NSAID induced injury in other species.