Analysis of osteoarthritis in a mouse model of the progeroid human DNA repair syndrome trichothiodystrophy

The increasing average age in developed societies is paralleled by an increase in the prevalence of many age-related diseases such as osteoarthritis (OA), which is characterized by deformation of the joint due to cartilage damage and increased turnover of subchondral bone. Consequently, deficiency in DNA repair, often associated with premature aging, may lead to increased pathology of these two tissues. To examine this possibility, we analyzed the bone and cartilage phenotype of male and female knee joints derived from 52- to 104-week-old WT C57Bl/6 and trichothiodystrophy (TTD) mice, who carry a defect in the nucleotide excision repair pathway and display many features of premature aging. Using micro-CT, we found bone loss in all groups of 104-week-old compared to 52-week-old mice. Cartilage damage was mild to moderate in all mice. Surprisingly, female TTD mice had less cartilage damage, proteoglycan depletion, and osteophytosis compared to WT controls. OA severity in males did not significantly differ between genotypes, although TTD males had less osteophytosis. These results indicate that in premature aging TTD mice age-related changes in cartilage were not more severe compared to WT mice, in striking contrast with bone and many other tissues. This segmental aging character may be explained by a difference in vasculature and thereby oxygen load in cartilage and bone. Alternatively, a difference in impact of an anti-aging response, previously found to be triggered by accumulation of DNA damage, might help explain why female mice were protected from cartilage damage. These findings underline the exceptional segmental nature of progeroid conditions and provide an explanation for pro- and anti-aging features occurring in the same individual

Spatiotemporal modeling of microbial metabolism

Background Microbial systems in which the extracellular environment varies both spatially and temporally are very common in nature and in engineering applications. While the use of genome-scale metabolic reconstructions for steady-state flux balance analysis (FBA) and extensions for dynamic FBA are common, the development of spatiotemporal metabolic models has received little attention. Results We present a general methodology for spatiotemporal metabolic modeling based on combining genome-scale reconstructions with fundamental transport equations that govern the relevant convective and/or diffusional processes in time and spatially varying environments. Our solution procedure involves spatial discretization of the partial differential equation model followed by numerical integration of the resulting system of ordinary differential equations with embedded linear programs using DFBAlab, a MATLAB code that performs reliable and efficient dynamic FBA simulations. We demonstrate our methodology by solving spatiotemporal metabolic models for two systems of considerable practical interest: (1) a bubble column reactor with the syngas fermenting bacterium Clostridium ljungdahlii; and (2) a chronic wound biofilm with the human pathogen Pseudomonas aeruginosa. Despite the complexity of the discretized models which consist of 900 ODEs/600 LPs and 250 ODEs/250 LPs, respectively, we show that the proposed computational framework allows efficient and robust model solution. Conclusions Our study establishes a new paradigm for formulating and solving genome-scale metabolic models with both time and spatial variations and has wide applicability to natural and engineered microbial systems

Experiences of ICU survivors in a low middle income country - A multicenter study

Background Stressful patient experiences during the intensive care unit (ICU) stay is associated with reduced satisfaction in High Income Countries (HICs) but has not been explored in Lower and Middle Income Countries (LMICs). This study describes the recalled experiences, stress and satisfaction as perceived by survivors of ICUs in a LMIC. Methods This follow-up study was carried out in 32 state ICUs in Sri Lanka between July and December 2015.ICU survivors’ experiences, stress factors encountered and level of satisfaction were collected 30 days after ICU discharge by a telephone questionnaire adapted from Granja and Wright Results Of 1665 eligible ICU survivors, 23.3% died after ICU discharge, 49.1% were uncontactable and 438 (26.3%) patients were included in the study. Whilst 78.1% (n = 349) of patients remembered their admission to the hospital, only 42.3% (n = 189) could recall their admission to the ICU. The most frequently reported stressful experiences were: being bedridden (34.2%), pain (34.0%), general discomfort (31.7%), daily needle punctures (32.9%), family worries (33.6%), fear of dying and uncertainty in the future (25.8%). The majority of patients (376, 84.12%) found the atmosphere of the ICU to be friendly and calm. Overall, the patients found the level of health care received in the ICU to be “very satisfactory” (93.8%, n = 411) with none of the survivors stating they were either “dissatisfied” or “very dissatisfied”. Conclusions In common with HIC, survivors were very satisfied with their ICU care. In contrast to HIC settings, specific ICU experiences were frequently not recalled, but those remembered were reported as relatively stress-free. Stressful experiences, in common with HIC, were most frequently related to uncertainty about the future, dependency, family, and economic concerns.</p

Evaluation of the feasibility and performance of early warning scores to identify patients at risk of adverse outcomes in a low-middle income country setting

Objective This study describes the availability of core parameters for Early Warning Scores (EWS), evaluates the ability of selected EWS to identify patients at risk of death or other adverse outcome and describes the burden of triggering that front-line staff would experience if implemented. Design Longitudinal observational cohort study. Setting District General Hospital Monaragala Participants All adult (age >17 years) admitted patients. Main outcome measures Existing physiological parameters, adverse outcomes and survival status at hospital discharge were extracted daily from existing paper records for all patients over an 8-month period. Statistical Analysis Discrimination for selected aggregate weighted track and trigger systems (AWTTS) was assessed by the area under the receiver operating characteristic (AUROC) curve. Performance of EWS are further evaluated at time points during admission and across diagnostic groups. The burden of trigger to correctly identify patients who died was evaluated using positive predictive value (PPV). Results Of the 16 386 patients included, 502 (3.06%) had one or more adverse outcomes (cardiac arrests, unplanned intensive care unit admissions and transfers). Availability of physiological parameters on admission ranged from 90.97% (95% CI 90.52% to 91.40%) for heart rate to 23.94% (95% CI 23.29% to 24.60%) for oxygen saturation. Ability to discriminate death on admission was less than 0.81 (AUROC) for all selected EWS. Performance of the best performing of the EWS varied depending on admission diagnosis, and was diminished at 24 hours prior to event. PPV was low (10.44%). Conclusion There is limited observation reporting in this setting. Indiscriminate application of EWS to all patients admitted to wards in this setting may result in an unnecessary burden of monitoring and may detract from clinician care of sicker patients. Physiological parameters in combination with diagnosis may have a place when applied on admission to help identify patients for whom increased vital sign monitoring may not be beneficial. Further research is required to understand the priorities and cues that influence monitoring of ward patients.</p

Evaluation of the feasibility and performance of early warning scores to identify patients at risk of adverse outcomes in a low-middle income country setting

Objective This study describes the availability of core parameters for Early Warning Scores (EWS), evaluates the ability of selected EWS to identify patients at risk of death or other adverse outcome and describes the burden of triggering that front-line staff would experience if implemented. Design Longitudinal observational cohort study. Setting District General Hospital Monaragala Participants All adult (age &gt;17 years) admitted patients. Main outcome measures Existing physiological parameters, adverse outcomes and survival status at hospital discharge were extracted daily from existing paper records for all patients over an 8-month period. Statistical Analysis Discrimination for selected aggregate weighted track and trigger systems (AWTTS) was assessed by the area under the receiver operating characteristic (AUROC) curve. Performance of EWS are further evaluated at time points during admission and across diagnostic groups. The burden of trigger to correctly identify patients who died was evaluated using positive predictive value (PPV). Results Of the 16 386 patients included, 502 (3.06%) had one or more adverse outcomes (cardiac arrests, unplanned intensive care unit admissions and transfers). Availability of physiological parameters on admission ranged from 90.97% (95% CI 90.52% to 91.40%) for heart rate to 23.94% (95% CI 23.29% to 24.60%) for oxygen saturation. Ability to discriminate death on admission was less than 0.81 (AUROC) for all selected EWS. Performance of the best performing of the EWS varied depending on admission diagnosis, and was diminished at 24 hours prior to event. PPV was low (10.44%). Conclusion There is limited observation reporting in this setting. Indiscriminate application of EWS to all patients admitted to wards in this setting may result in an unnecessary burden of monitoring and may detract from clinician care of sicker patients. Physiological parameters in combination with diagnosis may have a place when applied on admission to help identify patients for whom increased vital sign monitoring may not be beneficial. Further research is required to understand the priorities and cues that influence monitoring of ward patients.</p

Comparison of quick sequential organ failure assessment and modified systemic inflammatory response syndrome criteria in a lower middle income setting

Introduction: Quick Sequential Organ Failure Assessment (qSOFA) is potentially feasible tool to identify risk of deteriorating in the context of infection for to use in resource limited settings. Purpose: To compare the discriminative ability of qSOFA and a simplified systemic inflammatory response syndrome (SIRS) score to detect deterioration in patients admitted with infection. Methods: Observational study conducted at District General Hospital Monaragala, Sri Lanka, utilising bedside available observations extracted from healthcare records. Discrimination was evaluated using area under the receiver operating curve (AUROC). 15,577 consecutive adult ( ≥ 18 years) admissions were considered. Patients classified as having infection per ICD-10 diagnostic coding were included. Results: Both scores were evaluated for their ability to discriminate patients at risk of death or a composite adverse outcome (death, cardiac arrest, intensive care unit [ICU], admission or critical care transfer). 1844 admissions (11.8%) were due to infections with 20 deaths (1.1%), 29 ICU admissions (1.6%), 30 cardiac arrests and 9 clinical transfers to a tertiary hospital (0.5%). Sixty-seven (3.6%) patients experienced at least one event. Complete datasets were available for qSOFA in 1238 (67.14%) and for simplified SIRS (mSIRS) in 1628 (88.29%) admissions. Mean (SD) qSOFA score and mSIRS score at admission were 0.58 (0.69) and 0.66 (0.79) respectively. Both demonstrated poor discrimination for predicting adverse outcome AUROC = 0.625; 95% CI, 0.56-0.69 and AUROC = 0.615; 95% CI, 0.55- 0.69 respectively) with no significant difference (p value = 0.74). Similarly, both systems had poor discrimination for predicting deaths (AUROC = 0.685; 95% CI, 0.55-0.82 and AUROC = 0.629; 95% CI, 0.50-0.76 respectively) with no statistically significant difference (p value = 0.31). Conclusions: qSOFA at admission had poor discrimination and was not superior to the bedside observations featured in SIRS. Availability of observations, especially for mentation, is poor in these settings and requires strategies to improve reporting

Comparison of quick sequential organ failure assessment and modified systemic inflammatory response syndrome criteria in a lower middle income setting

Introduction: Quick Sequential Organ Failure Assessment (qSOFA) is potentially feasible tool to identify risk of deteriorating in the context of infection for to use in resource limited settings. Purpose: To compare the discriminative ability of qSOFA and a simplified systemic inflammatory response syndrome (SIRS) score to detect deterioration in patients admitted with infection. Methods: Observational study conducted at District General Hospital Monaragala, Sri Lanka, utilising bedside available observations extracted from healthcare records. Discrimination was evaluated using area under the receiver operating curve (AUROC). 15,577 consecutive adult ( ≥ 18 years) admissions were considered. Patients classified as having infection per ICD-10 diagnostic coding were included. Results: Both scores were evaluated for their ability to discriminate patients at risk of death or a composite adverse outcome (death, cardiac arrest, intensive care unit [ICU], admission or critical care transfer). 1844 admissions (11.8%) were due to infections with 20 deaths (1.1%), 29 ICU admissions (1.6%), 30 cardiac arrests and 9 clinical transfers to a tertiary hospital (0.5%). Sixty-seven (3.6%) patients experienced at least one event. Complete datasets were available for qSOFA in 1238 (67.14%) and for simplified SIRS (mSIRS) in 1628 (88.29%) admissions. Mean (SD) qSOFA score and mSIRS score at admission were 0.58 (0.69) and 0.66 (0.79) respectively. Both demonstrated poor discrimination for predicting adverse outcome AUROC = 0.625; 95% CI, 0.56-0.69 and AUROC = 0.615; 95% CI, 0.55- 0.69 respectively) with no significant difference (p value = 0.74). Similarly, both systems had poor discrimination for predicting deaths (AUROC = 0.685; 95% CI, 0.55-0.82 and AUROC = 0.629; 95% CI, 0.50-0.76 respectively) with no statistically significant difference (p value = 0.31). Conclusions: qSOFA at admission had poor discrimination and was not superior to the bedside observations featured in SIRS. Availability of observations, especially for mentation, is poor in these settings and requires strategies to improve reporting

A retrospective study of physiological observation-reporting practices and the recognition, response, and outcomes following cardiopulmonary arrest in a low-to-middle-income country

Background and Aims In Sri Lanka, as in most low‑to‑middle‑income countries (LMICs), early warning systems (EWSs) are not in use. Understanding observation‑reporting practices and response to deterioration is a necessary step in evaluating the feasibility of EWS implementation in a LMIC setting. This study describes the practices of observation reporting and the recognition and response to presumed cardiopulmonary arrest in a LMIC. Patients and Methods This retrospective study was carried out at District General Hospital Monaragala, Sri Lanka. One hundred and fifty adult patients who had cardiac arrests and were reported to a nurse responder were included in the study. Results Availability of six parameters (excluding mentation) was significantly higher at admission (P Conclusions Observations commonly used to detect deterioration are poorly reported, and reporting practices would need to be improved prior to EWS implementation. These findings reinforce the need for training in acute care and resuscitation skills for health‑care teams in LMIC settings as part of a program of improving recognition and response to acute deterioration.</p