Phytolith-occluded carbon in leaves of Dendrocalamus Ronganensis influenced by drought during growing season.

Being an important carbon (C) sink, phytolith-occluded carbon (PhytOC) has been investigated in various soil-plant systems. However, the effects of environmental factors (i.e., drought) on phytoliths, including altered deposition in plant tissues, morphological variation, and amounts of carbon occluded within phytoliths, are less studied. In this study, we analyzed the monthly variations of phytolith production and PhytOC in the leaves of Dendrocalamus ronganensis grown on a karst mountain in southwestern China during a drought year. This study thus sought to understand the effects of drought on phytolith formation, morphological variations and carbon sequestration within phytoliths in plants. Our results showed that the phytolith assemblages and PhytOC between new and old leaves differed significantly and varied with plant growth stages. The average PhytOC values of old leaves and tip leaves were 3.2% and 2.2%, respectively. In particular, both PhytOC and proportions of ELONGATE, BULLIFORM FLABELLATE, and STOMA phytoliths in tip leaves significantly decreased from September to January the following year because of drought effects. This study suggests that PhytOC in plants varies between phytolith morphotypes and is significantly affected by plant growth stage and hydrologic conditions. This indicates that we can improve the efficiency of phytolith carbon sequestration in plants by improving the soil water conditions required for plant growth.

Electron probe microanalysis of the elemental composition of phytoliths from woody bamboo species.

Electron probe microanalysis (EPMA) is promising for accurately determining elemental components in micro-areas of individual phytolith particles, interpreting compositional features and formation mechanisms of phytoliths in plants, identifying archeological and sedimental phytolith. However, the EPMA method of analyzing mounted slide phytoliths has not well been defined. In this study, we attempted different EPMA methods to determine the elemental compositions of phytoliths in mounted slides. Direct analysis of carbon (DAC) with other elements in phytolith could obtain abnormally high total values and carbon values. The method of carbon excluded in measuring elements (non-carbon analysis (NCA)) was feasible to obtain elemental compositions in phytolith. The NCA method was conducive to obtain the factual elemental compositions of an individual phytolith (morphotype) when the carbon content of phytolith was relatively low. The EPMA results of phytoliths from 20 bamboo species (three genera) showed that phytolith was dominantly composed of SiO2 but also included low contents of diverse other elements. The EPMA of phytoliths can provide the elemental composition of micro-areas of an individual phytolith particle. The elemental compositions of phytolith varied with their morphotypes, the genera and ecotype of bamboos. The EPMA of elemental compositions in phytoliths is a potential tool to study the formation mechanism of phytoliths, plant taxonomical identification, archaeological and paleoenvironmental reconstruction.

Incidence, characteristics, and outcomes of delirium in patients with noninvasive ventilation: a prospective observational study.

BACKGROUND: Factors that may increase the risk for delirium and the firm knowledge around mechanism for delirium in noninvasive ventilation (NIV) patients is lacking. We investigated the incidence, characteristics, and outcomes of delirium in NIV patients. METHODS: A prospective observational study was performed in an intensive care unit (ICU) of a teaching hospital. Patients in whom NIV was used as a first-line intervention were enrolled. During NIV intervention, delirium was screened using the Confusion Assessment Method for the ICU each day. The association between delirium and poor outcomes (e.g., NIV failure, ICU and hospital mortality) was investigated using forward stepwise multivariate logistic regression analyses. RESULTS: We enrolled 1083 patients. Of these, 196 patients (18.1%) experienced delirium during NIV intervention. Patients with delirium had higher NIV failure rates (37.8% vs. 21.0%, p < 0.01), higher ICU mortality (33.2% vs. 14.3%, p < 0.01), and higher hospital mortality (37.2% vs. 17.0%, p < 0.01) than subjects without delirium. They also had a longer duration of NIV (median 6.3 vs. 3.7 days, p < 0.01), and stayed longer in the ICU (median 9.0 vs. 6.0 days, p < 0.01) and the hospital (median 14.5 vs. 11.0 days, p < 0.01). These results were confirmed in COPD and non-COPD cohorts. According to subtype, compared to hyperactive delirium patients, hypoactive and mixed delirium patients spent more days and many more days on NIV (median 3.4 vs. 6.5 vs. 10.1 days, p < 0.01). Similar outcomes were found for length of stay in the ICU and hospital. However, NIV failure, ICU mortality, and hospital mortality did not differ among the three subtypes. CONCLUSIONS: Delirium is associated with increases in poor outcomes (NIV failure, ICU mortality, and hospital mortality) and the use of medical resources (duration of NIV, and lengths of stay in the ICU and hospital). Regarding subtype, hypoactive and mixed delirium are associated with higher, and much higher, consumption of medical resources, respectively, compared to hyperactive delirium.

Noninvasive ventilation failure in patients with hypoxemic respiratory failure: the role of sepsis and septic shock.

BACKGROUND: Sepsis and septic shock are common in noninvasive ventilation (NIV) patients. However, studies on the association between sepsis and NIV failure are lacking. METHODS: A prospective multi-center observational study was performed in 16 Chinese intensive care units (ICUs). Patients who used NIV due to hypoxemic respiratory failure were enrolled. Sepsis and septic shock were diagnosed according to the guideline of sepsis-3. RESULTS: A total of 519 patients were enrolled. Sepsis developed in 365 patients (70%) and septic shock developed in 79 patients (15%). However, 75 patients (14%) had no sepsis. NIV failure was 23%, 38%, and 61% in patients, with no sepsis, sepsis, and septic shock, respectively. Multivariate analysis found that sepsis [odds ratio (OR) = 1.95, 95% confidence interval (CI): 1.06-3.61] and septic shock (OR = 2.47, 95% CI: 1.12-5.45) were independently associated with NIV failure. In sepsis and septic shock population, the NIV failure was 13%, 31%, 37%, 53%, and 67% in patients with sequential organ failure assessment (SOFA) scores of ⩽2, 3-4, 5-6, 7-8, and ⩾9, respectively. Patients with nonpulmonary induced sepsis had similar NIV failure rate compared with those with pulmonary induced sepsis, but had higher proportion of septic shock (37% versus 10%, p ⩽ 0.01) and lower ICU mortality (10% versus 22%, p ⩽ 0.01). CONCLUSIONS: Sepsis was associated with NIV failure in patients with hypoxemic respiratory failure, and the association was stronger in septic shock patients. NIV failure increased with the increase of organ dysfunction caused by sepsis. The reviews of this paper are available via the supplemental material section.

Early prediction of noninvasive ventilation failure in COPD patients: derivation, internal validation, and external validation of a simple risk score.

BACKGROUND: Early identification of noninvasive ventilation (NIV) failure is a promising strategy for reducing mortality in chronic obstructive pulmonary disease (COPD) patients. However, a risk-scoring system is lacking. METHODS: To develop a scale to predict NIV failure, 500 COPD patients were enrolled in a derivation cohort. Heart rate, acidosis (assessed by pH), consciousness (assessed by Glasgow coma score), oxygenation, and respiratory rate (HACOR) were entered into the scoring system. Another two groups of 323 and 395 patients were enrolled to internally and externally validate the scale, respectively. NIV failure was defined as intubation or death during NIV. RESULTS: Using HACOR score collected at 1-2 h of NIV to predict NIV failure, the area under the receiver operating characteristic curves (AUC) was 0.90, 0.89, and 0.71 for the derivation, internal-validation, and external-validation cohorts, respectively. For the prediction of early NIV failure in these three cohorts, the AUC was 0.91, 0.96, and 0.83, respectively. In all patients with HACOR score > 5, the NIV failure rate was 50.2%. In these patients, early intubation (< 48 h) was associated with decreased hospital mortality (unadjusted odds ratio = 0.15, 95% confidence interval 0.05-0.39, p < 0.01). CONCLUSIONS: HACOR scores exhibited good predictive power for NIV failure in COPD patients, particularly for the prediction of early NIV failure (< 48 h). In high-risk patients, early intubation was associated with decreased hospital mortality.

Decreasing re-intubation using prophylactic noninvasive ventilation in elderly patients: A propensity-matched study.

PURPOSE: Prophylactic noninvasive ventilation (NIV) reduces re-intubation in high-risk patients. However, its effects in elderly patients remain unclear. Here, we investigated the efficacy of prophylactic NIV in elderly patients after a planned extubation. MATERIALS AND METHODS: From January 2011 to December 2017, patients aged ≥65 years old were enrolled after completing an SBT. After extubation, patients who immediately received NIV were classified as the prophylactic NIV group, and those who did not were classified as the control group. Re-intubation was recorded at postextubation 72 h. RESULTS: We enrolled 171 and 120 patients in the NIV and control groups, respectively. Patients in the NIV group had a lower re-intubation rate (6.4% vs. 23.3%, p < 0.01) and lower hospital mortality (22.2% vs. 35.8%, p = 0.01) than controls. In addition, prophylactic NIV was an independent protective factor for re-intubation (OR = 0.15, 95% CI: 0.07-0.34, p < 0.01 for all patients; OR = 0.16, 95% CI: 0.05-0.52, p < 0.01 for AECOPD patients, and OR = 0.17, 95% CI: 0.05-0.62, p < 0.01 for pneumonia/ARDS patients). After completing propensity-matched analyses, prophylactic NIV also reduced re-intubation and hospital mortality. CONCLUSIONS: Elderly patients received benefits from prophylactic NIV after a planned extubation.

Resource use, characteristics and outcomes of prolonged non-invasive ventilation: a single-centre observational study in China.

OBJECTIVE: To report the resource use, characteristics and outcomes of patients with prolonged non-invasive ventilation (NIV). DESIGN: A single-centre observational study. SETTING: An intensive care unit of a teaching hospital. PARTICIPANTS: Patients who only received NIV because of acute respiratory failure were enrolled. Prolonged NIV was defined as subjects who received NIV ≥14 days. A total of 1539 subjects were enrolled in this study; 69 (4.5%) underwent prolonged NIV. MAIN OUTCOME MEASURES: Predictors of prolonged NIV and hospital mortality. RESULTS: The rate of do-not-intubate (DNI) orders was 9.1% (140/1539). At the beginning of NIV, a DNI order (OR 3.95, 95% CI 2.25 to 6.95) and pH ≥7.35 (2.20, 1.27 to 3.82) were independently associated with prolonged NIV. At days 1 and 7 of NIV, heart rate (1.01 (1.00 to 1.03) and 1.02 (1.00 to 1.03], respectively) and PaO2/FiO2<150 (2.19 (1.25 to 3.85) and 2.05 (1.04 to 4.04], respectively) were other independent risk factors for prolonged NIV. When patients who died after starting NIV but prior to 14 days were excluded, the association was strengthened. Regarding resource use, 77.1% of subjects received NIV<7 days and only accounted for 47.0% of NIV-days. However, 18.4% of subjects received NIV 7-13.9 days and accounted for 33.4% of NIV-days, 2.9% of subjects received NIV 14-20.9 days and accounted for 9.5% of NIV-days, and 1.6% of subjects received NIV≥21 days and accounted for 10.1% of NIV-days. CONCLUSIONS: Our results indicate the resource use, characteristics and outcomes of a prolonged NIV population with a relatively high proportion of DNI orders. Subjects with prolonged NIV make up a high proportion of NIV-days and are at high risk for in-hospital mortality.

Assessment of heart rate, acidosis, consciousness, oxygenation, and respiratory rate to predict noninvasive ventilation failure in hypoxemic patients.

PURPOSE: To develop and validate a scale using variables easily obtained at the bedside for prediction of failure of noninvasive ventilation (NIV) in hypoxemic patients. METHODS: The test cohort comprised 449 patients with hypoxemia who were receiving NIV. This cohort was used to develop a scale that considers heart rate, acidosis, consciousness, oxygenation, and respiratory rate (referred to as the HACOR scale) to predict NIV failure, defined as need for intubation after NIV intervention. The highest possible score was 25 points. To validate the scale, a separate group of 358 hypoxemic patients were enrolled in the validation cohort. RESULTS: The failure rate of NIV was 47.8 and 39.4% in the test and validation cohorts, respectively. In the test cohort, patients with NIV failure had higher HACOR scores at initiation and after 1, 12, 24, and 48 h of NIV than those with successful NIV. At 1 h of NIV the area under the receiver operating characteristic curve was 0.88, showing good predictive power for NIV failure. Using 5 points as the cutoff value, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for NIV failure were 72.6, 90.2, 87.2, 78.1, and 81.8%, respectively. These results were confirmed in the validation cohort. Moreover, the diagnostic accuracy for NIV failure exceeded 80% in subgroups classified by diagnosis, age, or disease severity and also at 1, 12, 24, and 48 h of NIV. Among patients with NIV failure with a HACOR score of >5 at 1 h of NIV, hospital mortality was lower in those who received intubation at ≤12 h of NIV than in those intubated later [58/88 (66%) vs. 138/175 (79%); p = 0.03). CONCLUSIONS: The HACOR scale variables are easily obtained at the bedside. The scale appears to be an effective way of predicting NIV failure in hypoxemic patients. Early intubation in high-risk patients may reduce hospital mortality.

Noninvasive Ventilation Intolerance: Characteristics, Predictors, and Outcomes.

BACKGROUND: Noninvasive ventilation (NIV) intolerance is one reason for NIV failure. However, the characteristics, predictors, and outcomes of NIV intolerance are unclear. METHODS: A prospective observational study was performed in the respiratory intensive care unit of a teaching hospital. Subjects with acute respiratory failure who used NIV were enrolled. Initially, continuous use of NIV was encouraged. However, if the subject could not tolerate NIV, it was used intermittently. NIV intolerance was defined as termination of NIV due to subject refusal to receive it because of discomfort, even after intermittent use was attempted. RESULTS: A total of 961 subjects were enrolled in the study. Of these, 50 subjects (5.2%) experienced NIV intolerance after a median 2.4 h of NIV support. Age (OR = 0.98, 95% CI 0.963-0.996) and heart rate (OR = 1.02, 95% CI 1.006-1.030) measured before NIV were 2 independent risk factors of NIV intolerance. After 1-2 h of NIV, independent risk factors of NIV intolerance were heart rate (OR = 1.03, 95% CI 1.016-1.044) and breathing frequency (OR = 1.06, 95% CI 1.027-1.099). Intolerant subjects had no improvement in mean arterial pressure, heart rate, or breathing frequency after the NIV intervention. Moreover, intolerant subjects had a higher intubation rate (44.0% vs 25.8%, P = .008) and higher mortality (34.0% vs 22.4%, P = .08). The three most common complaints were that NIV worsened subjects' distress (46%), that NIV resulted in dyspnea (26%), and that the flow or pressure of NIV was too strong to bear (16%). CONCLUSIONS: NIV intolerance worsened subjects' outcomes. Younger subjects with a high heart rate and breathing frequency may be more likely to experience NIV intolerance.

Semiquantitative cough strength score for predicting reintubation after planned extubation.

BACKGROUND: Semiquantitative cough strength score (SCSS, graded 0-5) and cough peak flow (CPF) have been used to predict extubation outcome in patients in whom extubation is planned; however, the correlation of the 2 assessments is unclear. METHODS: In the intensive care unit of a university-affiliated hospital, 186 patients who were ready for extubation after a successful spontaneous breathing trial were enrolled in the study. Both SCSS and CPF were assessed before extubation. Reintubation was recorded 72 hours after extubation. RESULTS: Reintubation rate was 15.1% within 72 hours after planned extubation. Patients in whom extubation was successful had higher SCSSs than did reintubated patients (mean [SD], 3.2 [1.6] vs 2.2 [1.6], P = .002) and CPF (74.3 [40.0] vs 51.7 [29.4] L/min, P = .005). The SCSS showed a positive correlation with CPF (r = 0.69, P < .001). Mean CPFs were 38.36 L/min, 39.51 L/min, 44.67 L/min, 57.54 L/min, 78.96 L/min, and 113.69 L/min in patients with SCSSs of 0, 1, 2, 3, 4, and 5, respectively. The discriminatory power for reintubation, evidenced by area under the receiver operating characteristic curve, was similar: 0.677 for SCSS and 0.678 for CPF (P = .97). As SCSS increased (from 0 to 1 to 2 to 3 to 4 to 5), the reintubation rate decreased (from 29.4% to 25.0% to 19.4% to 16.1% to 13.2% to 4.1%). CONCLUSIONS: SCSS was convenient to measure at the bedside. It was positively correlated with CPF and had the same accuracy for predicting reintubation after planned extubation.

Semiquantitative cough strength score and associated outcomes in noninvasive positive pressure ventilation patients with acute exacerbation of chronic obstructive pulmonary disease.

BACKGROUND: Weak cough may result in the failure of noninvasive positive pressure ventilation (NPPV) in patients with AECOPD. However, no detailed descriptions have yet been published for the measurement of cough strength and associated outcomes in AECOPD patients. METHODS: This study prospectively enrolled 261 AECOPD patients who received NPPV. Semiquantitative cough strength score (SCSS, ranging from 0 = weak to 5 = strong) was recorded before NPPV. Patients who required intubation were defined as NPPV failures. RESULTS: NPPV failed in 55 patients (21.1%). Weak cough (SCSS ≤3, OR = 8.1), high disease severity (APACHE II score >19, OR = 3.8), and malnutrition (total proteins ≤58 g/L, OR = 2.8) were independent risk factors for NPPV failure. Patients with 1, 2, and 3 risk factors were 4.7, 13.6, and 21.6 times more likely, respectively, to experience NPPV failure compared with patients with no risk factors. The NPPV failure rates were 80%, 40%, and 10.2% in patients with SCSS of 0­1, 2­3, and 4­5, respectively (p < 0.001). Compared with NPPV success patients, NPPV failure patients stayed longer in ICU (10.1 ± 7.9 days vs. 6.5 ± 4.6 days, p < 0.001), and they had higher ICU costs (€2986 ± 1906 vs. €5680 ± 3,604, p < 0.001), higher hospital costs (€ 6714 ± 7025 vs. €10,399 ± 9,509, p = 0.009), and higher hospital mortality (72.7% vs. 4.4%, p < 0.001). Moderate accuracy to distinguish NPPV failure by APACHE II score, SCSS, and total proteins was evidenced by ROC curves, with areas under the curve of 0.71, 0.78, and 0.67, respectively. A combination of all three factors reached good accuracy, with an area under the curve of 0.86. CONCLUSION: AECOPD patients with weak cough had a high risk of NPPV failure. SCSS, APACHE II scores, and total proteins were predictors of NPPV failure. Combined, these factors increased the power to predict NPPV failure.

Voluntary is better than involuntary cough peak flow for predicting re-intubation after scheduled extubation in cooperative subjects.

BACKGROUND: In this study, we compared the predictive accuracy of voluntary cough peak flow (V-CPF) and involuntary cough peak flow (IV-CPF) for re-intubation in mechanically ventilated subjects. METHODS: Endotracheally intubated patients who passed a spontaneous breathing trial and assessment of readiness for extubation were enrolled. Before extubation, V-CPF and IV-CPF were measured. Re-intubation was recorded at 72 h after extubation. RESULTS: A total of 115 extubations in 106 cooperative subjects (including 9 subjects with second extubation) and 5 extubations in 5 uncooperative subjects were recorded. At 72 h, 20 (17.4%) and 1 (25%) instances of re-intubation occurred in cooperative and uncooperative subjects, respectively. In cooperative subjects, those who had been successfully extubated had higher V-CPF than re-intubated subjects (81.3 ± 41.4 vs 51.3 ± 31.7, P = .003). However, rates were not significantly different with IV-CPF (70.9 ± 39.8 vs 55.7 ± 37.9, P = .121). Areas under the curve of the receiver operating characteristic in V-CPF and IV-CPF were 0.743 ± 0.057 and 0.632 ± 0.069 (P < .001 and P = .058, respectively, compared with area under the curve = 0.5). V-CPF had higher predictive accuracy for re-intubation than IV-CPF (P = .034). In subjects with a lower quartile and third quartile V-CPF (≤ 43.2 L/min and 43.2-68.4 L/min, respectively), V-CPF was similar to IV-CPF. However, in second quartile and upper quartile V-CPF (68.4-99.0 L/min and > 99.0 L/min, respectively), V-CPF was higher than IV-CPF (82.1 ± 9.6 vs 66.6 ± 19.5 L/min, P < .001; 135.5 ± 29.8 vs 116.2 ± 38.2 L/min, P = .006, respectively). Overall, V-CPF was higher than IV-CPF (76.0 ± 41.4 vs 68.2 ± 39.7, P = .003). In uncooperative subjects, the IV-CPF was higher than V-CPF (40.2 ± 10.2 vs 79.2 ± 29.0, P = .042). CONCLUSIONS: V-CPF is noninvasive. It is much more accurate than IV-CPF as a predictor of re-intubation in cooperative patients because the IV-CPF may underestimate cough strength in patients with high V-CPF. However, it is unclear which is optimal for use in uncooperative patients.