Objective: To describe and ascertain adverse

A case control study on the effect of threatened miscarriage on selected pregnancy outcome

Relationship between peak lactate and patient outcome following high-risk gastrointestinal surgery: Influence of the nature of their surgery: Elective versus emergency

Objectives: The association between hyperlactatemia and adverse outcome in patients admitted to ICUs following gastrointestinal surgery has not been reported. To explore the hypothesis that in a large cohort of gastrointestinal surgical patients, the peak serum lactate (in the first 24 hr) observed in patients admitted to ICU following surgery is associated with unadjusted and severity-adjusted acute hospital mortality and that the strength of association is greater in patients admitted following “emergency” surgery than in patients admitted following “elective” surgery. Design: A retrospective cohort study of all patients who had gastrointestinal surgery and were admitted directly to the ICU between 2008 and 2012. Setting: Two hundred forty-nine hospitals in the United Kingdom. Patients: One hundred twenty-one thousand nine hundred ninety patients. Interventions: None. Measurements and Main Results: Peak blood lactate in the first 24 hours of admission to critical care, acute hospital mortality, length of stay, and other variables routinely collected within the U.K. Intensive Care National Audit and Research Centre Case Mix Programme database. Elevated blood lactate was associated with increased risk of death and prolonged duration of stay, and the relationship was maintained once adjusted for confounding variables. The positive association between mortality and levels of blood lactate continued down into the “normal range,” without evidence of a plateau. There was no difference in the extent to which hyperlactatemia was related to mortality between patients admitted following elective and emergency surgery. Conclusions: These findings have implications for our understanding of the role of lactate in critically ill patients.</p

Relationship Between Peak Lactate and Patient Outcome Following High-Risk Gastrointestinal Surgery: Influence of the Nature of Their Surgery: Elective Versus Emergency

Objectives: The association between hyperlactatemia and adverse outcome in patients admitted to ICUs following gastrointestinal surgery has not been reported. To explore the hypothesis that in a large cohort of gastrointestinal surgical patients, the peak serum lactate (in the first 24 hr) observed in patients admitted to ICU following surgery is associated with unadjusted and severity-adjusted acute hospital mortality and that the strength of association is greater in patients admitted following “emergency” surgery than in patients admitted following “elective” surgery. Design: A retrospective cohort study of all patients who had gastrointestinal surgery and were admitted directly to the ICU between 2008 and 2012. Setting: Two hundred forty-nine hospitals in the United Kingdom. Patients: One hundred twenty-one thousand nine hundred ninety patients. Interventions: None. Measurements and Main Results: Peak blood lactate in the first 24 hours of admission to critical care, acute hospital mortality, length of stay, and other variables routinely collected within the U.K. Intensive Care National Audit and Research Centre Case Mix Programme database. Elevated blood lactate was associated with increased risk of death and prolonged duration of stay, and the relationship was maintained once adjusted for confounding variables. The positive association between mortality and levels of blood lactate continued down into the “normal range,” without evidence of a plateau. There was no difference in the extent to which hyperlactatemia was related to mortality between patients admitted following elective and emergency surgery. Conclusions: These findings have implications for our understanding of the role of lactate in critically ill patients

Performance of critical care prognostic scoring systems in low and middle-income countries: a systematic review

Background: Prognostic models-used in critical care medicine for mortality predictions, for benchmarking and for illness stratification in clinical trials-have been validated predominantly in high-income countries. These results may not be reproducible in low or middle-income countries (LMICs), not only because of different case-mix characteristics but also because of missing predictor variables. The study objective was to systematically review literature on the use of critical care prognostic models in LMICs and assess their ability to discriminate between survivors and non-survivors at hospital discharge of those admitted to intensive care units (ICUs), their calibration, their accuracy, and the manner in which missing values were handled. Methods: The PubMed database was searched in March 2017 to identify research articles reporting the use and performance of prognostic models in the evaluation of mortality in ICUs in LMICs. Studies carried out in ICUs in high-income countries or paediatric ICUs and studies that evaluated disease-specific scoring systems, were limited to a specific disease or single prognostic factor, were published only as abstracts, editorials, letters and systematic and narrative reviews or were not in English were excluded. Results: Of the 2233 studies retrieved, 473 were searched and 50 articles reporting 119 models were included. Five articles described the development and evaluation of new models, whereas 114 articles externally validated Acute Physiology and Chronic Health Evaluation, the Simplified Acute Physiology Score and Mortality Probability Models or versions thereof. Missing values were only described in 34% of studies; exclusion and or imputation by normal values were used. Discrimination, calibration and accuracy were reported in 94.0%, 72.4% and 25% respectively. Good discrimination and calibration were reported in 88.9% and 58.3% respectively. However, only 10 evaluations that reported excellent discrimination also reported good calibration. Generalisability of the findings was limited by variability of inclusion and exclusion criteria, unavailability of post-ICU outcomes and missing value handling. Conclusions: Robust interpretations regarding the applicability of prognostic models are currently hampered by poor adherence to reporting guidelines, especially when reporting missing value handling. Performance of mortality risk prediction models in LMIC ICUs is at best moderate, especially with limitations in calibration. This necessitates continued efforts to develop and validate LMIC models with readily available prognostic variables, perhaps aided by medical registrie

Improving ICU services in resource-limited settings: Perceptions of ICU workers from low-middle-, and high-income countries

To evaluate perceptions of intensive care unit (ICU) workers from low-and-middle income countries (LMICs) and high income countries (HICs).A cross sectional design. Data collected from doctors using an anonymous online, questionnaire.Hundred seventy-five from LMICs and 43 from HICs participated. Barriers in LMICs were lack of formal training (Likert score median 3 [inter quartile range 3]), lack of nurses (3[3]) and low wages (3[4]). Strategies for LMICs improvement were formal training of ICU staff (4[3]), an increase in number of ICU nurses (4[2]), collection of outcome data (3[4]), as well as maintenance of available equipment [3(3)]. The most useful role of HIC ICU staff was training of LMIC staff (4[2]). Donation of equipment [2(4)], drugs [2(4)], and supplies (2[4]) perceived to be of limited usefulness. The most striking difference between HIC and LMIC staff was the perception on the lack of physician leadership as an obstacle to ICU functioning (4[3] vs. 0[2], p<0.005).LMICs ICU workers perceived lack of training, lack of nurses, and low wages as major barriers to functioning. Training, increase of nurse workforce, and collection of outcome data were proposed as useful strategies to improve LMIC ICU services

Improving ICU services in resource-limited settings: Perceptions of ICU workers from low-middle-, and high-income countries

To evaluate perceptions of intensive care unit (ICU) workers from low-and-middle income countries (LMICs) and high income countries (HICs).A cross sectional design. Data collected from doctors using an anonymous online, questionnaire.Hundred seventy-five from LMICs and 43 from HICs participated. Barriers in LMICs were lack of formal training (Likert score median 3 [inter quartile range 3]), lack of nurses (3[3]) and low wages (3[4]). Strategies for LMICs improvement were formal training of ICU staff (4[3]), an increase in number of ICU nurses (4[2]), collection of outcome data (3[4]), as well as maintenance of available equipment [3(3)]. The most useful role of HIC ICU staff was training of LMIC staff (4[2]). Donation of equipment [2(4)], drugs [2(4)], and supplies (2[4]) perceived to be of limited usefulness. The most striking difference between HIC and LMIC staff was the perception on the lack of physician leadership as an obstacle to ICU functioning (4[3] vs. 0[2], p&lt;0.005).LMICs ICU workers perceived lack of training, lack of nurses, and low wages as major barriers to functioning. Training, increase of nurse workforce, and collection of outcome data were proposed as useful strategies to improve LMIC ICU services

A cross-sectional survey of critical care services in Sri Lanka: a lower middle-income country

To describe the extent and variation of critical care services in Sri Lanka as a first step towards the development of a nationwide critical care unit (CCU) registry. A cross-sectional survey was conducted in all state CCUs by telephone or by visits to determine administration, infrastructure, equipment, staffing, and overall patient outcomes. There were 99 CCUs with 2.5 CCU beds per 100000 population and 13 CCU beds per 1 000 hospital beds. The median number of beds per CCU was 5. The overall admissions were 194 per 100000 population per year. The overall bed turnover was 76.5 per unit per year, with CCU mortality being 17%. Most CCUs were headed by an anesthetist. There were a total of 790 doctors (1.6 per bed), 1,989 nurses (3.9 per bed), and 626 health care assistants (1.2 per bed). Majority (87.9%) had 1:1 nurse-to-patient ratio, although few (11.4%) nurses had received formal intensive care unit training. All CCUs had basic infrastructure (electricity, running water, piped oxygen) and basic equipment (such as electronic monitoring and infusion pumps). Sri Lanka, a lower middle-income country has an extensive network of critical care facilities but with inequalities in its distribution and facilitie

Applicability of the APACHE II model to a lower middle income country

To determine the utility of APACHE II in a low-and middle-income (LMIC) setting and the implications of missing data.Patients meeting APACHE II inclusion criteria admitted to 18 ICUs in Sri Lanka over three consecutive months had data necessary for the calculation of APACHE II, probabilities prospectively extracted from case notes. APACHE II physiology score (APS), probabilities, Standardised (ICU) Mortality Ratio (SMR), discrimination (AUROC), and calibration (C-statistic) were calculated, both by imputing missing measurements with normal values and by Multiple Imputation using Chained Equations (MICE).From a total of 995 patients admitted during the study period, 736 had APACHE II probabilities calculated. Data availability for APS calculation ranged from 70.6% to 88.4% for bedside observations and 18.7% to 63.4% for invasive measurements. SMR (95% CI) was 1.27 (1.17, 1.40) and 0.46 (0.44, 0.49), AUROC (95% CI) was 0.70 (0.65, 0.76) and 0.74 (0.68, 0.80), and C-statistic was 68.8 and 156.6 for normal value imputation and MICE, respectively.An incomplete dataset confounds interpretation of prognostic model performance in LMICs, wherein imputation using normal values is not a suitable strategy. Improving data availability, researching imputation methods and developing setting-adapted and simpler prognostic models are warranted