Search

This prospective quasi-experimental study from the NASAM (National Approach to Standardize and Improve Mechanical Ventilation) collaborative assessed the impact of evidence-based practices including subglottic suctioning, daily assessment for spontaneous awakening trial (SAT), spontaneous breathing trial (SBT), head of bed elevation, and avoidance of neuromuscular blockers unless otherwise indicated. The study outcomes included VAE (primary) and intensive care unit (ICU) mortality. Changes in daily care process measures and outcomes were evaluated using repeated measures mixed modeling. The results were reported as incident rate ratio (IRR) for each additional month with 95% confidence interval (CI). A comprehensive program that included education on evidence-based practices for optimal care of mechanically ventilated patients with real-time benchmarking of daily care process measures to drive improvement in forty-two ICUs from 26 hospitals in Saudi Arabia (>27,000 days of observation). Compliance with subglottic suctioning, SAT and SBT increased monthly during the project by 3.5%, 2.1% and 1.9%, respectively (IRR 1.035, 95%CI 1.007-1.064, p = 0.0148; 1.021, 95% CI 1.010-1.032, p = 0.0003; and 1.019, 95%CI 1.009-1.029, p = 0.0001, respectively). The use of neuromuscular blockers decreased monthly by 2.5% (IRR 0.975, 95%CI 0.953-0.998, p = 0.0341). The compliance with head of bed elevation was high at baseline and did not change over time. Based on data for 83153 ventilator days, VAE rate was 15.2/1000 ventilator day (95%CI 12.6-18.1) at baseline and did not change during the project (IRR 1.019, 95%CI 0.985-1.053, p = 0.2812). Based on data for 8523 patients; the mortality was 30.4% (95%CI 27.4-33.6) at baseline, and decreased monthly during the project by 1.6% (IRR 0.984, 95%CI 0.973-0.996, p = 0.0067). A national quality improvement collaborative was associated with improvements in daily care processes. These changes were associated with a reduction in mortality but not VAEs. Registration The study is registered in clinicaltrials.gov (NCT03790150).

The relative effects of climate warming with grazing on medicinally important plants are not fully understood in Hindukush-Himalaya (HKH) region. Therefore, we combined the indigenous knowledge about culturally important therapeutic plants and climate change with experimental warming (open-top chambers) and manual clipping (simulated grazing effect) and compared the relative difference on aboveground biomass and percent cover of plant species at five alpine meadow sites on an elevation gradient (4696 m-3346 m) from 2016-2018. Experimental warming increased biomass and percent cover throughout the experiment. However, the interactive treatment effect (warming x clipping) was significant on biomass but not on percent cover. These responses were taxa specific. Warming induced an increase of 1 ± 0.6% in Bistorta officinalis percent cover while for Poa alpina it was 18.7 ± 4.9%. Contrastingly, clipping had a marginally significant effect in reducing the biomass and cover of all plant species. Clipping treatment reduced vegetation cover & biomass by 2.3% and 6.26%, respectively, but that was not significant due to the high variability among taxa response at different sites. It was found that clipping decreased the effects of warming in interactive plots. Thus, warming may increase the availability of therapeutic plants for indigenous people while overgrazing would have deteriorating effects locally. The findings of this research illustrate that vegetation sensitivity to warming and overgrazing is likely to affect man-environment relationships, and traditional knowledge on a regional scale.

Climate change is expected to impact a large number of organisms in many ecosystems, including several threatened mammals. A better understanding of climate impacts on species can make conservation efforts more effective. The Himalayan ibex (Capra ibex sibirica) and blue sheep (Pseudois nayaur) are economically important wild ungulates in northern Pakistan because they are sought-after hunting trophies. However, both species are threatened due to several human-induced factors, and these factors are expected to aggravate under changing climate in the High Himalayas. In this study, we investigated populations of ibex and blue sheep in the Pamir-Karakoram mountains in order to (i) update and validate their geographical distributions through empirical data; (ii) understand range shifts under climate change scenarios; and (iii) predict future habitats to aid long-term conservation planning. Presence records of target species were collected through camera trapping and sightings in the field. We constructed Maximum Entropy (MaxEnt) model on presence record and six key climatic variables to predict the current and future distributions of ibex and blue sheep. Two representative concentration pathways (4.5 and 8.5) and two-time projections (2050 and 2070) were used for future range predictions. Our results indicated that ca. 37% and 9% of the total study area (Gilgit-Baltistan) was suitable under current climatic conditions for Himalayan ibex and blue sheep, respectively. Annual mean precipitation was a key determinant of suitable habitat for both ungulate species. Under changing climate scenarios, both species will lose a significant part of their habitats, particularly in the Himalayan and Hindu Kush ranges. The Pamir-Karakoram ranges will serve as climate refugia for both species. This area shall remain focus of future conservation efforts to protect Pakistan’s mountain ungulates.

Pakistan's total estimated snow leopard habitat is about 80,000 km2 of which about half is considered prime habitat. However, this preliminary demarcation was not always in close agreement with the actual distribution-the discrepancy may be huge at the local and regional level. Recent technological developments like camera trapping and molecular genetics allow for collecting reliable presence records that could be used to construct realistic species distribution based on empirical data and advanced mathematical approaches like MaxEnt. The current study followed this approach to construct an accurate distribution of the species in Pakistan. Moreover, movement corridors, among different landscapes, were also identified through circuit theory. The probability of habitat suitability, generated from 98 presence points and 11 environmental variables, scored the snow leopard's assumed range in Pakistan, from 0 to 0.97. A large portion of the known range represented low-quality habitat, including areas in lower Chitral, Swat, Astore, and Kashmir. Conversely, Khunjerab, Misgar, Chapursan, Qurumber, Broghil, and Central Karakoram represented high-quality habitats. Variables with higher contributions in the MaxEnt model were precipitation during the driest month (34%), annual mean temperature (19.5%), mean diurnal range of temperature (9.8%), annual precipitation (9.4%), and river density (9.2). The model was validated through receiver operating characteristic (ROC) plots and defined thresholds. The average test AUC in Maxent for the replicate runs was 0.933 while the value of AUC by ROC curve calculated at 0.15 threshold was 1.00. These validation tests suggested a good model fit and strong predictive power. The connectivity analysis revealed that the population in the Hindukush landscape appears to be more connected with the population in Afghanistan as compared to other populations in Pakistan. Similarly, the Pamir-Karakoram population is better connected with China and Tajikistan, while the Himalayan population was connected with the population in India. Based on our findings we propose three model landscapes to be considered under the Global Snow Leopard Ecosystem Protection Program (GSLEP) agenda as regional priority areas, to safeguard the future of the snow leopard in Pakistan and the region. These landscapes fall within mountain ranges of the Himalaya, Hindu Kush and Karakoram-Pamir, respectively. We also identified gaps in the existing protected areas network and suggest new protected areas in Chitral and Gilgit-Baltistan to protect critical habitats of snow leopard in Pakistan.

Habitat suitability models are useful to understand species distribution and to guide management and conservation strategies. The grey wolf (Canis lupus) has been extirpated from most of its historic range in Pakistan primarily due to its impact on livestock and livelihoods. We used non-invasive survey data from camera traps and genetic sampling to develop a habitat suitability model for C. lupus in northern Pakistan and to explore the extent of connectivity among populations. We detected suitable habitat of grey wolf using a maximum entropy approach (Maxent ver. 3.4.0) and identified suitable movement corridors using the Circuitscape 4.0 tool. Our model showed high levels of predictive performances, as seen from the values of area under curve (0.971±0.002) and true skill statistics (0.886±0.021). The main predictors for habitat suitability for C. lupus were distances to road, mean temperature of the wettest quarter and distance to river. The model predicted ca. 23,129 km2 of suitable areas for wolf in Pakistan, with much of suitable habitat in remote and inaccessible areas that appeared to be well connected through vulnerable movement corridors. These movement corridors suggest that potentially the wolf range can expand in Pakistan's Northern Areas. However, managing protected areas with stringent restrictions is challenging in northern Pakistan, in part due to heavy dependence of people on natural resources. The habitat suitability map provided by this study can inform future management strategies by helping authorities to identify key conservation areas.

Autosomal recessive hypotrichosis is a rare genetic irreversible hair loss disorder characterized by sparse scalp hair, sparse to absent eyebrows and eyelashes, and sparse axillary and body hair. The study, presented here, established genetic linkage in four families showing similar phenotypes to lysophosphatidic acid receptor 6 (LPAR6) gene on chromosome 13q14.11-q21.32. Subsequently, sequence analysis of the gene revealed two previously reported missense mutations including p.D63V in affected members of one and p.I188F in three other families. Molecular modeling and docking analysis was performed to investigate binding of a ligand oleoyl-L-alpha-lysophosphatidic acid (LPA) to modeled protein structures of normal and mutated (D63V, G146R, I188F, N248Y, S3T, L277P) LPAR6 receptors. The mutant receptors showed a complete shift in orientation of LPA at the binding site. In addition, hydropathy analysis revealed a significant change in the membrane spanning topology of LPAR6 helical segments. The present study further substantiated involvement of LPAR6-LPA signaling in the pathogenesis of hypotrichosis/woolly hair and provided additional insight into the molecular mechanism of hair development.

This prospective quasi-experimental study from the NASAM (National Approach to Standardize and Improve Mechanical Ventilation) collaborative assessed the impact of evidence-based practices including subglottic suctioning, daily assessment for spontaneous awakening trial (SAT), spontaneous breathing trial (SBT), head of bed elevation, and avoidance of neuromuscular blockers unless otherwise indicated. The study outcomes included VAE (primary) and intensive care unit (ICU) mortality. Changes in daily care process measures and outcomes were evaluated using repeated measures mixed modeling. The results were reported as incident rate ratio (IRR) for each additional month with 95% confidence interval (CI). A comprehensive program that included education on evidence-based practices for optimal care of mechanically ventilated patients with real-time benchmarking of daily care process measures to drive improvement in forty-two ICUs from 26 hospitals in Saudi Arabia (>27,000 days of observation). Compliance with subglottic suctioning, SAT and SBT increased monthly during the project by 3.5%, 2.1% and 1.9%, respectively (IRR 1.035, 95%CI 1.007-1.064, p = 0.0148; 1.021, 95% CI 1.010-1.032, p = 0.0003; and 1.019, 95%CI 1.009-1.029, p = 0.0001, respectively). The use of neuromuscular blockers decreased monthly by 2.5% (IRR 0.975, 95%CI 0.953-0.998, p = 0.0341). The compliance with head of bed elevation was high at baseline and did not change over time. Based on data for 83153 ventilator days, VAE rate was 15.2/1000 ventilator day (95%CI 12.6-18.1) at baseline and did not change during the project (IRR 1.019, 95%CI 0.985-1.053, p = 0.2812). Based on data for 8523 patients; the mortality was 30.4% (95%CI 27.4-33.6) at baseline, and decreased monthly during the project by 1.6% (IRR 0.984, 95%CI 0.973-0.996, p = 0.0067). A national quality improvement collaborative was associated with improvements in daily care processes. These changes were associated with a reduction in mortality but not VAEs. Registration The study is registered in clinicaltrials.gov (NCT03790150)., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Arabi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Adverse drug reactions (ADRs) represent a major burden on the healthcare system. Chronic kidney disease (CKD) patients are particularly vulnerable to ADRs because they are usually on multiple drug regimens, have multiple comorbidities, and because of alteration in their pharmacokinetics and pharmacodynamic parameters. Therefore, one step towards reducing this burden is to identify patients who are at increased risk of an ADR., Objective: To develop a method of identifying CKD patients who are at increased risk for experiencing ADRs during hospitalisation., Materials and Methods: Factors associated with ADRs were identified by using demographic, clinical and laboratory variables of patients with CKD stages 3 to 5 (estimated glomerular filtration rate, 10-59 ml/min/1.73 m2) who were admitted between January 1, 2012, and December 31, 2012, to the renal unit of Dubai Hospital. An ADR risk score was developed by constructing a series of logistic regression models. The overall model performance for sequential models was evaluated using Akaike Information Criterion for goodness of fit. Odd ratios of the variables retained in the best model were used to compute the risk scores., Results: Of 512 patients (mean [SD] age, 60 [16] years), 62 (12.1%) experienced an ADR during their hospitalisation. An ADR risk score included age 65 years or more, female sex, conservatively managed end-stage renal disease, vascular disease, serum level of C-reactive protein more than 10 mg/L, serum level of albumin less than 3.5 g/dL, and the use of 8 medications or more during hospitalization. The C statistic, which assesses the ability of the risk score to predict ADRs, was 0.838; 95% CI, 0.784-0.892)., Conclusion: A score using routinely available patient data can be used to identify CKD patients who are at increased risk of ADRs.