Big data and clinical research: perspective from a clinician

Diagnostic accuracy of STAF, LADS, and iPAB scores for predicting paroxysmal atrial fibrillation in patients with acute cerebral infarction

BACKGROUND AND OBJECTIVE

The scoring scales scoring system for targeting atrial fibrillation (STAF), left atrial diameter, age, diagnosis of stroke, and smoking status (LADS), and identified by past history of arrhythmia or antiarrhythmic agent use, atrial dilation, and elevation of Brain natriuretic peptide (iPAB) have been proposed for predicting atrial fibrillation in patients with acute cerebral infarction, but their relative accuracies are not clear. This prospective study compared STAF, LADS, and iPAB scores for predicting paroxysmal atrial fibrillation (PAF) in patients with acute cerebral infarction.

METHODS

Patients with acute cerebral infarction (n = 744; 495 men, 249 women; aged 65 ± 12 years) were consecutively enrolled throughout the year 2016 at the Department of Neurology of Huizhou Municipal Central Hospital. Patients were followed for 3 months. The sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and best cutoff points of STAF, LADS, and iPAB scores for predicting PAF were computed.

RESULTS

Among the 744 patients, 37 patients had PAF. The AUCs of the STAF, LADS, and iPAB scores for predicting PAF were 0.87, 0.79, and 0.84, respectively, and with a cutoff at four points, the sensitivities were 73%, 70.3%, and 83.8%, and specificities were 92.1%, 82.2%, and 77%.

CONCLUSIONS

The STAF, LADS, and iPAB scores could satisfactorily predict PAF in patients with acute cerebral infarction. STAF was superior to the others in diagnostic performance.

Prompt admission to intensive care is associated with improved survival in patients with severe sepsis and/or septic shock

Objective To investigate the association between time from hospital admission to intensive care unit (ICU) admission (door to ICU time) and hospital mortality in patients with sepsis. Methods This retrospective observational study included routinely collected healthcare data from patients with sepsis. The primary endpoint was hospital mortality, defined as the survival status at hospital discharge. Door to ICU time was calculated and included in a multivariable model to investigate its association with mortality. Results Data from 13 115 patients were included for analyses, comprising 10 309 survivors and 2 806 non-survivors. Door to ICU time was significantly longer for non-survivors than survivors (median, 43.0 h [interquartile range, 12.4, 91.3] versus 26.7 h [7.0, 74.2]). In the multivariable regression model, door to ICU time remained significantly associated with mortality (odds ratio [OR] 1.11, 95% confidence interval [CI] 1.006, 1.017) and there was a significant interaction between age and door to ICU time (OR 0.99, 95% CI 0.99, 1.00). Conclusion A shorter time from hospital door to ICU admission was shown to be independently associated with reduced hospital mortality in patients with severe sepsis and/or septic shock.

How Registry Data Will Change Our Approach to Lymphedema Research and Clinical Management

In 2018 the American Physical Therapy Association officially launched the Physical Therapy Outcomes Registry (PTOR). The purpose of the registry is to accumulate clinical data from therapists around the country in order to analyze aggregate information on patient populations. Such an approach can help our profession better understand how to optimize treatment outcomes and can enhance data-driven clinical decision making. Additionally, a recent collaborative effort between Stanford University and the Lymphatic Education & Research Network (LE&RN) has created The International Lymphatic Disease and Lymphedema Patient Registry and Biorepository, a patient registry that aims to collect information about individuals who are diagnosed with a lymphatic disease or lymphedema. While these efforts are both Registries of condition-specific data, they are different in how they collect data and produce information. Researchers and clinical providers should have an understanding of what registry data currently exists and what the opportunities are to support clinical lymphedema management and lymphedema-focused research efforts by leveraging registry data.

Laboratory epidemiology of respiratory viruses in a large children's hospital: A STROBE-compliant article

Acute respiratory tract infection (ARTI) is the most common causes of outpatient visit and hospital admission for children. The study aimed to report epidemiological data on respiratory viruses in a university-affiliated children's hospital.The study was a retrospective study conducted in a university affiliated children's hospital from 2016 May to 2017 April. The results of all nasopharyngeal swab and sputum samples sent for the test for respiratory viruses (adenovirus, influenza A, influenza B, and respiratory syncytial virus) were extracted from the electronic healthcare records. Clinical characteristics were compared between groups with positive versus negative results for respiratory viruses. Multivariable regression models were employed by including age, gender, type of sample (swab vs sputum), source (emergency department vs others), and season to explore the independent factors associated with positive results for respiratory viruses.A total of 34,961 samples were identified during the study period. A total of 3102 (8.9%) samples were positive for adenovirus, 2811 (8.0%) were positive for influenza A, 3460 (9.9%) were positive for influenza B, and 4527 (13.0%) were positive for respiratory syncytial virus. The positive rate of adenovirus was highest in April (50.8%), and lowest in November (3%). The absolute number of positive samples for adenovirus was highest in June (n = 587) and April (n = 544). For the test of influenza A, age was independently associated with positive result. With 1 year increase in age, the odds of positive result increased by 12% (odds ratio [OR]: 1.12; 95% confidence interval [CI]: 1.11-1.13; P < .001). As compared with the autumn, the summer showed significantly lower rate of positive for RSV (OR: 0.49; 95% CI: 0.38-0.62; P < .001), whereas the winter had higher risk of positive result (OR: 3.88; 95% CI: 3.37-4.50; P < .001).The study reported epidemiological data on the prevalence of respiratory viruses in a large tertiary care children's hospital. Age, gender, type of sample, source, and season were associated with the positive rates for respiratory viruses.

Preliminary experience of tigecycline treatment in critically ill children with ventilator-associated pneumonia

Objective

Ventilator-associated pneumonia (VAP) is a life-threatening complication for children who are treated in a paediatric intensive care unit. Tigecycline treatment of children with VAP has not been well studied. This study aimed to describe tigecycline use in children with VAP in a tertiary care hospital.

Methods

We conducted a retrospective chart review in a tertiary hospital from May 1, 2012 to May 1, 2017.

Results

Twenty-four children (20 girls) with median age of 8 months (range, 27 days to 6 years and 9 months) were treated with tigecycline. In-hospital mortality was 41.7% (10/24). The primary diagnosis was congenital heart disease (15/24). A total of 70.8% (17/24) of patients received a loading dose (1.5 mg/kg), followed by 1 mg/kg every 12 hours. The median duration of tigecycline therapy was 10.75 days (range, 3–21.5 days). Sulperazone was the most frequently used concomitant antibiotic. Eighteen pathogens were isolated in 16 cases. Tigecycline therapy failed in 41.6% (10/24) of patients and 20.8% (5/24) died. The pathogen was eradicated in 37.5% (6/16) of patients. No serious adverse effects were detected.

Conclusion

Tigecycline combined with other agents as salvage therapy in children with VAP is well tolerated. Our preliminary results show a positive clinical response.

Propensity score method: a non-parametric technique to reduce model dependence

Propensity score analysis (PSA) is a powerful technique that it balances pretreatment covariates, making the causal effect inference from observational data as reliable as possible. The use of PSA in medical literature has increased exponentially in recent years, and the trend continue to rise. The article introduces rationales behind PSA, followed by illustrating how to perform PSA in R with MatchIt package. There are a variety of methods available for PS matching such as nearest neighbors, full matching, exact matching and genetic matching. The task can be easily done by simply assigning a string value to the method argument in the matchit() function. The generic summary() and plot() functions can be applied to an object of class matchit to check covariate balance after matching. Furthermore, there is a useful package PSAgraphics that contains several graphical functions to check covariate balance between treatment groups across strata. If covariate balance is not achieved, one can modify model specifications or use other techniques such as random forest and recursive partitioning to better represent the underlying structure between pretreatment covariates and treatment assignment. The process can be repeated until the desirable covariate balance is achieved.

Effectiveness of enteral feeding protocol on clinical outcomes in critically ill patients: A before and after study

BACKGROUND AND OBJECTIVE

Enteral nutrition (EN) feeding protocol was proposed to have positive impact on critically ill patients. However, current studies showed conflicting results. The present study aimed to investigate whether enteral feeding protocol was able to improve clinical outcomes in critically ill patients.

METHODS

A before (stage 1) and after (stage 2) interventional study was performed in 10 tertiary care hospitals. All patients expected to stay in the intensive care unit (ICU) for over three days were potentially eligible. Clinical outcomes such as 28-day mortality, ICU length of stay, duration of mechanical ventilation (MV), and nosocomial infection were compared between the two stages.

MAIN RESULTS

A total of 410 patients were enrolled during the study period, including 236 in stage 1 and 174 in stage 2. EN feeding protocol was able to increase the proportion of EN in day 2 (41.8±22.3 vs. 50.0±28.3%; p = 0.006) and day 6 (70.3±25.2 vs. 77.6±25.8%; p = 0.006). EN percentages tended to be higher in stage 1 than that in stage 2 on other days, but statistical significance was not reached. There was no difference in 28-day mortality between stage 1 and 2 (0.14 vs. 0.14; p = 0.984). Implementation of EN feeding protocol marginally reduced ICU length of stay (19.44±18.48 vs. 16.29±16.19 days; p = 0.077). There was no difference in the duration of MV between stage a and stage 2 (14.24±14.49 vs. 14.51±17.55 days; p = 0.877).

CONCLUSIONS

The study found that the EN feeding protocol was able to increase the proportion of EN feeding, but failed to reduce 28-day mortality, incidence of nosocomial infection or duration of MV.

AME evidence series 001-The Society for Translational Medicine: clinical practice guidelines for diagnosis and early identification of sepsis in the hospital

Sepsis is a heterogeneous disease caused by an infection stimulus that triggers several complex local and systemic immuno-inflammatory reactions, which results in multiple organ dysfunction and significant morbidity and mortality. The diagnosis of sepsis is challenging because there is no gold standard for diagnosis. As a result, the clinical diagnosis of sepsis is ever changing to meet the clinical and research requirements. Moreover, although there are many novel biomarkers and screening tools for predicting the risk of sepsis, the diagnostic performance and effectiveness of these measures are less than satisfactory, and there is insufficient evidence to recommend clinical use of these new techniques. As a consequence, diagnostic criteria for sepsis need regular revision to cope with emerging evidence. This review aims to present the most updated information on diagnosis and early recognition of sepsis. Recommendations for clinical use of different diagnostic tools rely on the Grades of Recommendation Assessment, Development and Evaluation (GRADE) framework. Because most of the studies were observational and did not allow a reliable assessment of these tools, a two-step inference approach was employed. Future trials need to confirm or refute a particular index test and should directly explore relevant patient outcome parameters.

Is real world evidence influencing practice? A systematic review of CPRD research in NICE guidances

BACKGROUND

There is currently limited evidence regarding the extent Real World Evidence (RWE) has directly impacted the health and social care systems. The aim of this review is to identify national guidelines or guidances published in England from 2000 onwards which have referenced studies using the governmental primary care data provider the Clinical Practice Research Datalink (CPRD).

METHODS

The methodology recommended by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was followed. Four databases were searched and documents of interest were identified through a search algorithm containing keywords relevant to CPRD. A search diary was maintained with the inclusion/exclusion decisions which were performed by two independent reviewers.

RESULTS

Twenty-five guidance documents were included in the final review (following screening and assessment for eligibility), referencing 43 different CPRD/GPRD studies, all published since 2007. The documents covered 12 disease areas, with the majority (N =7) relevant to diseases of the Central Nervous system (CNS). The 43 studies provided evidence of disease epidemiology, incidence/prevalence, pharmacoepidemiology, pharmacovigilance and health utilisation.

CONCLUSIONS

A slow uptake of RWE in clinical and therapeutic guidelines (as provided by UK governmental structures) was noticed. However, there seems to be an increasing trend in the use of healthcare system data to inform clinical practice, especially as the real world validity of clinical trials is being questioned. In order to accommodate this increasing demand and meet the paradigm shift expected, organisations need to work together to enable or improve data access, undertake translational and relevant research and establish sources of reliable evidence.

Opportunities and challenges for thoracic surgery collaborations in China: a commentary

Through a unique combination of factors-including a huge population, rapid social development, and concentration of resources in its mega-cities-China is witnessing phenomenal developments in the field of thoracic surgery. Ultra-high-volume centers are emerging that provide fantastic new opportunities for surgical training and clinical research to surgeons in China and partners from other countries. However, there are also particular shortcomings that are limiting clinical and academic developments. To realize the potential and reap the rewards, the challenges posed by these limitations must be overcome. Thoracic surgeons from Europe may be particularly well-placed to achieve this through multi-dimensional exchanges with their Chinese counterparts.

Data management by using R: big data clinical research series

Electronic medical record (EMR) system has been widely used in clinical practice. Instead of traditional record system by hand writing and recording, the EMR makes big data clinical research feasible. The most important feature of big data research is its real-world setting. Furthermore, big data research can provide all aspects of information related to healthcare. However, big data research requires some skills on data management, which however, is always lacking in the curriculum of medical education. This greatly hinders doctors from testing their clinical hypothesis by using EMR. To make ends meet, a series of articles introducing data management techniques are put forward to guide clinicians to big data clinical research. The present educational article firstly introduces some basic knowledge on R language, followed by some data management skills on creating new variables, recoding variables and renaming variables. These are very basic skills and may be used in every project of big data research.

When do confounding by indication and inadequate risk adjustment bias critical care studies? A simulation study

Introduction

In critical care observational studies, when clinicians administer different treatments to sicker patients, any treatment comparisons will be confounded by differences in severity of illness between patients. We sought to investigate the extent that observational studies assessing treatments are at risk of incorrectly concluding such treatments are ineffective or even harmful due to inadequate risk adjustment.

Methods

We performed Monte Carlo simulations of observational studies evaluating the effect of a hypothetical treatment on mortality in critically ill patients. We set the treatment to have either no association with mortality or to have a truly beneficial effect, but more often administered to sicker patients. We varied the strength of the treatment’s true effect, strength of confounding, study size, patient population, and accuracy of the severity of illness risk-adjustment (area under the receiver operator characteristics curve, AUROC). We measured rates in which studies made inaccurate conclusions about the treatment’s true effect due to confounding, and the measured odds ratios for mortality for such false associations.

Results

Simulated observational studies employing adequate risk-adjustment were generally able to measure a treatment’s true effect. As risk-adjustment worsened, rates of studies incorrectly concluding the treatment provided no benefit or harm increased, especially when sample size was large (n = 10,000). Even in scenarios of only low confounding, studies using the lower accuracy risk-adjustors (AUROC < 0.66) falsely concluded that a beneficial treatment was harmful. Measured odds ratios for mortality of 1.4 or higher were possible when the treatment’s true beneficial effect was an odds ratio for mortality of 0.6 or 0.8.

Conclusions

Large observational studies confounded by severity of illness have a high likelihood of obtaining incorrect results even after employing conventionally “acceptable” levels of risk-adjustment, with large effect sizes that may be construed as true associations. Reporting the AUROC of the risk-adjustment used in the analysis may facilitate an evaluation of a study’s risk for confounding.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-015-0923-8) contains supplementary material, which is available to authorized users.