Chlorhexidine oral rinses for symptomatic COPD: a randomised, blind, placebo-controlled preliminary study

ObjectivesDetermine the effect of twice-daily chlorhexidine oral rinses on oral and lung microbiota biomass and respiratory symptoms.SettingSingle centre.ParticipantsParticipants were aged 40–85 with chronic obstructive pulmonary disease (COPD) and chronic productive cough or COPD exacerbation within the last year. Exclusions included antibiotics in the previous 2 months and/or those with less than four teeth. Forty-four participants were recruited and 40 completed the study.InterventionParticipants were randomised 1:1 to twice-daily 0.12% chlorhexidine oral rinses versus placebo for 2 months along with daily diaries. St. George’s Respiratory Questionnaire (SGRQ), blood tests, oral rinse and induced sputum were collected at randomisation and the final visit.Primary and secondary outcomesPrimary outcome was a change in oral and sputum microbiota biomass. Secondary outcomes included: sputum and oral microbiota Shannon and Simpson diversity and taxonomy; inflammatory markers; Breathlessness, Cough and Sputum Scale and SGRQ scores.ResultsNeither the oral microbiota nor the sputum microbiota biomass decreased significantly in those using chlorhexidine compared with placebo (oral microbiota mean log10 difference (SE)=−0.103 (0.23), 95% CI −0.59 to 0.38, p=0.665; sputum microbiota 0.80 (0.46), 95% CI −0.15 to 1.75, p=0.096). Chlorhexidine decreased both oral and sputum microbiota alpha (Shannon) diversity (linear regression estimate (SE) oral: −0.349 (0.091), p=0.001; sputum −0.622 (0.169), p=0.001). Chlorhexidine use did not decrease systemic inflammatory markers compared with placebo (C reactive protein (chlorhexidine 1.8±7.5 vs placebo 0.4±6.8, p=0.467), fibrinogen (22.5±77.8 vs 10.0±77.0, p=0.406) or leucocytes (0.2±1.8 vs 0.5±1.8, p=0.560)). Chlorhexidine use decreased SGRQ scores compared with placebo (chlorhexidine −4.7±8.0 vs placebo 1.7±8.9, p=0.032).ConclusionsWe did not detect a significant difference in microbiota biomass due to chlorhexidine use. Chlorhexidine decreased oral and sputum microbiota alpha diversity and improved respiratory health-related quality of life compared with placebo.Trial registrationNCT02252588.

Establishing a Reference Baseline for Midday Stem Water Potential in Olive and Its Use for Plant-Based Irrigation Management

Midday stem water potential (SWP) is rapidly becoming adopted as a standard tool for plant-based irrigation management in many woody perennial crops. A reference or “baseline” SWP has been used in some crops (almond, prune, grape, and walnut) to account for the climatic influence of air vapor pressure deficit (VPD) on SWP under non-limiting soil moisture conditions. The baseline can be determined empirically for field trees maintained under such non-limiting conditions, but such conditions are difficult to achieve for an entire season. We present the results of an alternative survey-based approach, using a large set of SWP and VPD data collected over multiple years, from irrigation experiments in olive orchards located in multiple countries [Spain, United States (California), Italy, and Argentina]. The relation of SWP to midday VPD across the entire data set was consistent with an upper limit SWP which declined with VPD, with the upper limit being similar to that found in Prunus. A best fit linear regression estimate for this upper limit (baseline) was found by selecting the maximum R2 and minimum probability for various upper fractions of the SWP/VPD relation. In addition to being surprisingly similar to the Prunus baseline, the olive baseline was also similar (within 0.1 MPa) to a recently published mechanistic olive soil-plant-atmosphere-continuum (SPAC) model for “super high density” orchard systems. Despite similarities in the baseline, the overall physiological range of SWP exhibited by olive extends to about −8 MPa, compared to about −4 MPa for economically producing almond. This may indicate that, despite species differences in physiological responses to low water availability (drought), there may be convergent adaptations/acclimations across species to high levels of water availability. Similar to its use in other crops, the olive baseline will enable more accurate and reproducible plant-based irrigation management for both full and deficit irrigation practices, and we present tentative SWP guidelines for this purpose.

Impact of Pneumococcal Urinary Antigen Testing in COVID-19 Patients: Outcomes from the San Matteo COVID-19 Registry (SMACORE)

Despite low rates of bacterial co-infections, most COVID-19 patients receive antibiotic therapy. We hypothesized that patients with positive pneumococcal urinary antigens (PUAs) would benefit from antibiotic therapy in terms of clinical outcomes (death, ICU admission, and length of stay). The San Matteo COVID-19 Registry (SMACORE) prospectively enrolls patients admitted for COVID-19 pneumonia at IRCCS Policlinico San Matteo, Pavia. We retrospectively extracted the data of patients tested for PUA from October to December 2020. Demographic, clinical, and laboratory data were recorded. Of 469 patients, 42 tested positive for PUA (8.95%), while 427 (91.05%) tested negative. A positive PUA result had no significant impact on death (HR 0.53 CI [0.22–1.28] p-value 0.16) or ICU admission (HR 0.8; CI [0.25–2.54] p-value 0.70) in the Cox regression model, nor on length of stay in linear regression (estimate 1.71; SE 2.37; p-value 0.47). After adjusting for age, we found no significant correlation between urinary antigen positivity and variations in the WHO ordinal scale and laboratory markers at admission and after 14 days. We found that a positive PUA result was not frequent and had no impact on clinical outcomes or clinical improvement. Our results did not support the routine use of PUA tests to select COVID-19 patients who will benefit from antibiotic therapy.

Using Robust Ridge Regression Diagnostic Method to Handle Multicollinearity Caused High Leverage Points

Statistics practitioners have been depending on the ordinary least squares (OLS) method in the linear regression model for generation because of its optimal properties and simplicity of calculation. However, the OLS estimators can be strongly affected by the existence of multicollinearity which is a near linear dependency between two or more independent variables in the regression model. Even though in the presence of multicollinearity the OLS estimate still remained unbiased, they will be inaccurate prediction about the dependent variable with the inflated standard errors of the estimated parameter coefficient of the regression model. It is now evident that the existence of high leverage points which are the outliers in x-direction are the prime factor of collinearity influential observations. In this paper, we proposed some alternative to regression methods for estimating the regression parameter coefficient in the presence of multiple high leverage points which cause the multicollinearity problem. This procedure utilized the ordinary least squares estimates of the parameter as the initial followed by an estimate of the ridge regression. We incorporated the Least Trimmed Squares (LTS) robust regression estimate to down weight the effects of multiple high leverage points which lead to the reduction of the effects of multicollinearity. The result seemed to suggest that the RLTS give a substantial improvement over the Ridge Regression.

Robust Estimation for a Generalised Ratio Model

It is known that data such as business sales and household income need data transformation prior to regression estimate as the data has a homoscedastic error. However, data transformations make the estimation of mean and total unstable. Therefore, the ratio model is often used for imputation in the field of official statistics to avoid the problem. Our study aims to robustify the estimator following the ratio model by means of M-estimation. Reformulation of the conventional ratio model with homoscedastic quasi-error term provides quasi-residuals which can be used as a measure of outlyingness as same as a linear regression model. A generalisation of the model, which accommodates varied error terms with different heteroscedasticity, is also proposed. Functions for robustified estimators of the generalised ratio model are implemented by the iterative re-weighted least squares algorithm in R environment and illustrated using random datasets. Monte Carlo simulation confirms accuracy of the proposed estimators, as well as their computational efficiency. A comparison of the scale parameters between the average absolute deviation (AAD) and median absolute deviation (MAD) is made regarding Tukey's biweight function. The results with Huber's weight function are also provided for reference. The proposed robust estimator of the generalised ratio model is used for imputation of major corporate accounting items of the 2016 Economic Census for Business Activity in Japan.

CALIBRATION OF A WEIGHING LYSIMETER FOR MEASURING COCOA EVAPOTRANSPIRATION

ABSTRACT Well-operated and calibrated weighing lysimeters reliably determine the water demand of agricultural crops, and the quality of the data is evaluated through the error analyses attributed to the instrument. The objective of this study was to determine performance parameters of a weighing lysimeter and to evaluate its adequacy for the direct determination of cocoa crop evapotranspiration. The lysimeter with 1.44 m2 surface, supported on four load cells installed in the experimental area of the Graduate Program in Agricultural Engineering of the Universidade Federal do Recôncavo da Bahia, was calibrated at 3:00 a.m., using known masses at intervals of 02 minutes in five cycles of addition and removal. Data were collected using a datalogger coupled to four load cells with an individual capacity of 1000 kg, programmed to perform readings every 01 second, storing the averages of 15 minutes. The lysimeter showed excellent accuracy, with r2greater than 0.99 in the correlation between the standard masses and the signal of the load cells and standard error of linear regression estimate of 0.03 mm. The combination of repeatability and hysteresis errors with an uncertainty of 0.19% showed that the load cells have accuracy of ±0.07 mm, with resolution of 0.00033 mV, and sensitivity to detect mass changes below 0.1 mm, the system is adequate for direct measurement of cocoa ETc at time intervals of less than one hour.

Rate of the Almost Sure Convergence of a Generalized Regression Estimate Based on Truncated and Functional Data

In this paper, a nonparametric estimation of a generalized regression function is proposed. The real response random variable (r.v.) is subject to left-truncation by another r.v. while the covariate takes its values in an infinite dimensional space. Under standard assumptions, the pointwise and the uniform almost sure convergences, of the proposed estimator, are established