Background: Even though there are continually upgraded recommendations for managing sepsis, such as "Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock", mortality is still high. Si-Ni-Tang, a remedy documented in Shanghan Lun, a medical collection from ancient China, is used for treating patients with sepsis and septic shock. Using a well-designed clinical trial, we are eager to survey the effectiveness of the concurrent use of this remedy in restoring these patients' hemodynamic status, or "Yang Qi". Methods/Design: Patients admitted to our medical intensive care units with the diagnosis of septic shock, defined as persistent hypotension induced by sepsis despite adequate fluid resuscitation, are eligible for participation. The inclusion criteria include: age from 20 to 85 years, conditions meeting the definition of septic shock, use of vasopressors within 24 hours of entering the study, and use of a nasogastric tube for feeding. The enrolled patients are randomly allocated either to the Si-Ni-Tang group or the placebo group. The prescription of the trial drugs (Si-Ni-Tang/placebo) is 2.25 grams 4 times a day for 7 days or till shock reversal (if shock reversal occurs in less than 7 days). Data, including duration of vasopressor infusion, gender, age, co-morbidities, APACHE II score, predicted mortality, ICU mortality, ICU length of stay, hospital mortality, hospital length of stay, source of sepsis, and culture results, are collected for the following analysis. Discussion: Si-Ni-Tang is composed of processed Zingiber officinale, Glycyrrhiza uralensis, and Aconitum carmichaeli. Zingiber officinale and Glycyrrhiza uralensis are found to have the ability to reduce pro-inflammatory cytokine production, to inhibit lipopolisaccharide-induced macrophage activation and function, and to lessen the bacterial load and suppress acute and chronic inflammation. Aconitum carmichaeli is known to have vasopressor activity, and positive chronotropic and inotropic effects. As this remedy has a potential benefit in treating septic shock patients, we designed a double-blind, prospective, randomized controlled trial and would like to publish the results and conclusions later. Trial Registration: ClinicalTrials.gov: NCT01223430

Diabetes mellitus (DM) and tuberculosis (TB) are major public health and economic burdens. DM increases Mycobacterium tuberculosis (M.tb) infection rates and treatment durations. This study evaluated the relationship between five classes of oral DM medications and TB infection risk in DM patients. We used longitudinal records from the Taiwan Longitudinal Health Insurance Research Database. DM patients were identified using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD‐9‐CM) code 250 and A code A181. TB patients were identified using ICD‐9‐CM code 010.x‐017.x. Oral DM medications were divided into five classes: sulfonylureas, biguanides, meglitinides, α‐glucosidase inhibitors (AGIs), and thiazolidinediones. Users were classified as nonusers, low‐concentration users, and high‐concentration users. The incidence rate ratio (IRR) was derived using multivariate Poisson regression to calculate the relative risk of TB infection. DM patients using low‐ and high‐concentration AGIs had significantly lower TB infection risks compared with nonusers. The IRRs of the sulfonylureas and AGI users were [CI] 0.693–0.948) and (95% CI 0.651–0.995), respectively. The other four classes of medications exhibited no significant effect on TB infection risk in DM patients. Furthermore, DM patients using high‐concentration AGIs had a significantly lower TB infection risk compared with those using low‐concentration AGIs (IRR 0.918, 95% CI: 0.854–0.987). We noted a dose‐response relationship in the effects of DM medications on TB risk. Accordingly, we suggest that DM patients use AGIs to benefit from their protective effect on TB infection risk.

Gattinoni’s equation, $${\text{MP}}_{{{\text{rs}}}} \, = \,0.098\, \times \,{\text{RR}}\, \times \,\left[ {{\text{V}}_{T} ^{2} \left( {\frac{1}{2}{\text{E}}_{{{\text{rs}}}} \, + \,{\text{RR}}\, \times \,\frac{{1\, + \,I:E}}{{60\, \times \,I:E}}\, \times \,{\text{R}}_{{{\text{aw}}}} } \right)\, + \,{\text{V}}_{{\text{T}}} \, \times \,{\text{PEEP}}} \right]$$MP rs = 0.098 × RR × V T 2 1 2 E rs + RR × 1 + I : E 60 × I : E × R aw + V T × PEEP , now commonly used to calculate the mechanical power (MP) of ventilation. However, it calculates only inspiratory MP. In addition, the inclusion of PEEP in Gattinoni’s equation raises debate because PEEP does not produce net displacement or contribute to MP. Measuring the area within the pressure–volume loop accurately reflects the MP received in a whole ventilation cycle and the MP thus obtained is not influenced by PEEP. The MP of 25 invasively ventilated patients were calculated by Gattinoni’s equation and measured by integration of the areas within the pressure–volume loops of the ventilation cycles. The MP obtained from both methods were compared. The effects of PEEPs on MP were also evaluated. We found that the MP obtained from both methods were correlated by R² = 0.75 and 0.66 at PEEP 5 and 10 cmH₂O, respectively. The biases of the two methods were 3.13 (2.03 to 4.23) J/min (P < 0.0001) and − 1.23 (− 2.22 to − 0.24) J/min (P = 0.02) at PEEP 5 and 10 cmH₂O, respectively. These P values suggested that both methods were significantly incongruent. When the tidal volume used was 6 ml/Kg, the MP by Gattinoni’s equation at PEEP 5 and 10 cmH₂O were significantly different (4.51 vs 7.21 J/min, P < 0.001), but the MP by PV loop area was not influenced by PEEPs (6.46 vs 6.47 J/min, P = 0.331). Similar results were observed across all tidal volumes. We conclude that the Gattinoni’s equation is not accurate in calculating the MP of a whole ventilatory cycle and is significantly influenced by PEEP, which theoretically does not contribute to MP.

This study investigated the usefulness of ventilator parameters in the prediction of development and outcome of acute respiratory distress syndrome (ARDS) in postoperative patients with esophageal or lung cancer on admission to the surgical intensive care unit (SICU). A total of 32 post-operative patients with lung or esophageal cancer from SICU in a tertiary medical center were retrospectively analyzed. The study patients were divided into an ARDS group (n = 21) and a non-ARDS group (n = 11). The ARDS group contained the postoperative patients who developed ARDS after lung or esophageal cancer surgery. The ventilator variables were analyzed in this study. Principal component analysis (PCA) was performed to reduce the correlated ventilator variables to a small set of variables. The top three ventilator variables with large coefficients, as determined by PCA, were considered as sensitive variables and included in the analysis model based on the rule of 10 events per variable. Firth logistic regression with selective stepwise elimination procedure was performed to identify the most important predictors of morbidity and mortality in patients with ARDS. Ventilator parameters, including rapid shallow breath index during mechanical ventilation (RSBIv), rate pressure product of ventilation (RPPv), rate pressure volume index (RPVI), mechanical work (MW), and inspiration to expiration time ratio (IER), were analyzed in this study. It was found that the ARDS patients had significantly greater respiratory rate (RR), airway resistance (Raw), RSBIv, RPPv, RPVI, positive end-expiratory pressure (PEEP), and IER and significantly lower respiratory interval (RI), expiration time (Te), flow rate ($\dot{\mathrm{V}}$), tidal volume (V_T), dynamic compliance (Cdyn), mechanical work of ventilation (MW), and MW/IER ratio than the non-ARDS patients. The non-survivors of ARDS had significantly greater peak inspiratory pressure above PEEP (PIP), RSBIv, RPPv, and RPVI than the survivors of ARDS. By using PCA, the MW/IER was found to be the most important predictor of the development of ARDS, and both RPPv and RPVI were significant predictors of mortality in patients with ARDS. In conclusion, some ventilator parameters, such as RPPv, RPVI, and MW/IER defined in this study, can be derived from ventilator readings and used to predict the development and outcome of ARDS in mechanically ventilated patients on admission to the SICU.