Monitoring Temporal Changes in SARS-CoV-2 Spike Antibody Levels and Variant-Specific Risk for Infection, Dominican Republic, March 2021-August 2022.

To assess changes in SARS-CoV-2 spike binding antibody prevalence in the Dominican Republic and implications for immunologic protection against variants of concern, we prospectively enrolled 2,300 patients with undifferentiated febrile illnesses in a study during March 2021-August 2022. We tested serum samples for spike antibodies and tested nasopharyngeal samples for acute SARS-CoV-2 infection using a reverse transcription PCR nucleic acid amplification test. Geometric mean spike antibody titers increased from 6.6 (95% CI 5.1-8.7) binding antibody units (BAU)/mL during March-June 2021 to 1,332 (95% CI 1,055-1,682) BAU/mL during May-August 2022. Multivariable binomial odds ratios for acute infection were 0.55 (95% CI 0.40-0.74), 0.38 (95% CI 0.27-0.55), and 0.27 (95% CI 0.18-0.40) for the second, third, and fourth versus the first anti-spike quartile; findings were similar by viral strain. Combining serologic and virologic screening might enable monitoring of discrete population immunologic markers and their implications for emergent variant transmission.

SARS-CoV-2 seroprevalence, cumulative infections, and immunity to symptomatic infection - A multistage national household survey and modelling study, Dominican Republic, June-October 2021.

Background: Population-level SARS-CoV-2 immunological protection is poorly understood but can guide vaccination and non-pharmaceutical intervention priorities. Our objective was to characterise cumulative infections and immunological protection in the Dominican Republic. Methods: Household members ≥5 years were enrolled in a three-stage national household cluster serosurvey in the Dominican Republic. We measured pan-immunoglobulin antibodies against the SARS-CoV-2 spike (anti-S) and nucleocapsid glycoproteins, and pseudovirus neutralising activity against the ancestral and B.1.617.2 (Delta) strains. Seroprevalence and cumulative prior infections were weighted and adjusted for assay performance and seroreversion. Binary classification machine learning methods and pseudovirus neutralising correlates of protection were used to estimate 50% and 80% protection against symptomatic infection. Findings: Between 30 Jun and 12 Oct 2021 we enrolled 6683 individuals from 3832 households. We estimate that 85.0% (CI 82.1-88.0) of the ≥5 years population had been immunologically exposed and 77.5% (CI 71.3-83) had been previously infected. Protective immunity sufficient to provide at least 50% protection against symptomatic SARS-CoV-2 infection was estimated in 78.1% (CI 74.3-82) and 66.3% (CI 62.8-70) of the population for the ancestral and Delta strains respectively. Younger (5-14 years, OR 0.47 [CI 0.36-0.61]) and older (≥75-years, 0.40 [CI 0.28-0.56]) age, working outdoors (0.53 [0.39-0.73]), smoking (0.66 [0.52-0.84]), urban setting (1.30 [1.14-1.49]), and three vs no vaccine doses (18.41 [10.69-35.04]) were associated with 50% protection against the ancestral strain. Interpretation: Cumulative infections substantially exceeded prior estimates and overall immunological exposure was high. After controlling for confounders, markedly lower immunological protection was observed to the ancestral and Delta strains across certain subgroups, findings that can guide public health interventions and may be generalisable to other settings and viral strains. Funding: This study was funded by the US CDC.

Telemedicine to Expand Access to Critical Care Around the World.

This multiauthored communication gives a state-of-the-art global perspective on the increasing adoption of tele-critical care. Exponentially increasing sophistication in the deployment of Computers, Information, and Communication Technology has ensured extending the reach of limited intensivists virtually and reaching the unreached. Natural disasters, COVID-19 pandemic, and wars have made tele-intensive care a reality. Concerns and regulatory issues are being sorted out, cross-border cost-effective tele-critical care is steadily increasing Components to set up a tele-intensive care unit, and overcoming barriers is discussed. Importance of developing best practice guidelines and retraining is emphasized.

Interfacility Transport of Critically Ill Patients.

OBJECTIVES: To assess recent advances in interfacility critical care transport. DATA SOURCES: PubMed English language publications plus chapters and professional organization publications. STUDY SELECTION: Manuscripts including practice manuals and standard (1990-2021) focused on interfacility transport of critically ill patients. DATA EXTRACTION: Review of society guidelines, legislative requirements, objective measures of outcomes, and transport practice standards occurred in work groups assessing definitions and foundations of interfacility transport, transport team composition, and transport specific considerations. Qualitative analysis was performed to characterize current science regarding interfacility transport. DATA SYNTHESIS: The Task Force conducted an integrative review of 496 manuscripts combined with 120 from the authors' collections including nonpeer reviewed publications. After title and abstract screening, 40 underwent full-text review, of which 21 remained for qualitative synthesis. CONCLUSIONS: Since 2004, there have been numerous advances in critical care interfacility transport. Clinical deterioration may be mitigated by appropriate patient selection, pretransport optimization, and transport by a well-resourced team and vehicle. There remains a dearth of high-quality controlled studies, but notable advances in monitoring, en route management, transport modality (air vs ground), as well as team composition and training serve as foundations for future inquiry. Guidance from professional organizations remains uncoupled from enforceable regulations, impeding standardization of transport program quality assessment and verification.

Prehospital Mechanical Ventilation: An NAEMSP Position Statement and Resource Document.

Airway emergencies and respiratory failure frequently occur in the prehospital setting. Patients undergoing advanced airway management customarily receive manual ventilations. However, manual ventilation is associated with hypo- and hyperventilation, variable tidal volumes, and barotrauma, among other potential complications. Portable mechanical ventilators offer an important strategy for optimizing ventilation and mitigating ventilatory complications.EMS clinicians, including those performing emergency response as well as interfacility transports, should consider using mechanical ventilation after advanced airway insertion.Prehospital mechanical ventilation techniques, strategies, and parameters should be disease-specific and should mirror in-hospital best practices.EMS clinicians must receive training in the general principles of mechanical ventilation as well as detailed training in the operation of the specific system(s) used by the EMS agency.Patients undergoing mechanical ventilation must receive appropriate sedation and analgesia.

Clinical validation demonstrates concordance of qSOFA and POC lactate Bayesian model: Results from the ACDC Phase-2 program.

Sepsis is a common and lethal medical problem. The objective of this study was to validate a Bayesian Model that integrates qSOFA and prehospital Lactate, with a comparison analysis from a real clinical data of patients with sepsis. METHODS: We conducted a two tired validation study with one arm focusing on Bayesian modeling and a second retrospective observational arm addressing real data validation. For Bayesian modeling, sensitivity and specificity of prehospital lactate were attained from pooled meta-analysis data. Later, for clinical validation, we used data from 2016 to 2017 of ED patients diagnosed with sepsis. Pretest probabilities from qSOFA score where combined with prehospital lactate and inserted into a Bayesian model to calculate posttest probabilities. Absolute and relative diagnostic gains were calculated. Statistical significance was assessed via t-test, chi square and odds ratio. P value was set to be 0.05. RESULTS: For the Bayesian arm; meta-analysis data for prehospital lactate resulted in a positive likelihood ratio (LR+) of 1.69 and negative likelihood ratio (LR-) of 0.44. Integration of lactate and qSOFA demonstrated significant post-test improvements. On the Clinical Validation arm, 1470 patients were included with 176 patients meeting analysis criteria. When comparing qSOFA + Abnormal Lactate vs qSOFA and normal Lactate, the ICU vs Non-ICU cohorts were statistically different (p < 0.01) Odds Ratio: 2.35 (95% CI [1.22-4.6]). CONCLUSION: Bayesian mathematical model demonstrated that a qSOFA-based clinical decision can be complemented by the use of point of-care lactate. These results were confirmed by our clinical validation arm.

Seroprevalence of Specific Antibodies against SARS-CoV-2 from Hotspot Communities in the Dominican Republic.

Seroprevalence surveys are of utmost importance to assess the proportion of a population that has developed antibodies against a newly introduced virus and could therefore potentially exhibit immunologic protection against subsequent infection. This study aims to understand the distribution of IgM and IgG antibodies in the Dominican Republic. We surveyed a total of 12,897 participants between April and June 2020 in 10 provinces of the Dominican Republic. Survey efforts in emerging hotspots yielded a positivity for all participants of anti-SARS-CoV-2 IgM of 3.8% and IgG of 5.4%, indicating that the pathogen was in circulation before the identification of those particular communities as hotspots. We found important age differences between participants who participated in the serological study where a higher mean age is associated IgM positivity and a lower age with IgG positivity. Our results highlight the need for strategies that involve community-based seroprevalence monitoring. These should preclude syndromic case identification. Also, the higher mean age of IgM-positive participants suggests that strategies based on syndromic surveillance could identify hotspots at later phases, based on the number of cases detected at the healthcare center, as such community-based seroprevalence monitoring may be an effective intervention for future outbreaks.

A dignitary medicine curriculum developed using a modified Delphi methodology.

BACKGROUND: Dignitary medicine is an emerging field of training that involves the specialized care of diplomats, heads of state, and other high-ranking officials. In an effort to provide guidance on training in this nascent field, we convened a panel of experts in dignitary medicine and using the Delphi methodology, created a consensus curriculum for training in dignitary medicine. METHODS: A three-round Delphi consensus process was performed with 42 experts in the field of dignitary medicine. Predetermined scores were required for an aspect of the curriculum to advance to the next round. The scores on the final round were used to determine the components of the curriculum. Scores below the threshold to advance were dropped in the subsequent round. RESULTS: Our panel had a high degree of agreement on the required skills needed to practice dignitary medicine, with active practice in a provider's baseline specialty, current board certification, and skills in emergency care and resuscitation being the highest rated skills dignitary medicine physicians need. Skills related to vascular and emergency ultrasound and quality improvement were rated the lowest in the Delphi analysis. No skills were dropped from consideration. CONCLUSIONS: The results of our work can form the basis of formal fellowship training, continuing medical education, and publications in the field of dignitary medicine. It is clear that active medical practice and knowledge of resuscitation and emergency care are critical skills in this field, making emergency medicine physicians well suited to practicing dignitary medicine.

Latin America intensive care unit disaster preparedness: Results from a web-based attitudes and perceptions survey.

BACKGROUND: Disasters burden on hospital emergency intensive care units (ICUs). This burden is increased in Latin America (LATAM) where hospital resources, intrahospital disaster simulations, and perceived level of preparedness vary greatly among different communities. The objective of the study was to assess LATAM ICU leaders' knowledge and attitudes regarding disaster preparedness. METHODS: We developed a ten-item, web-based knowledge and attitude survey administered via LATAM ICU leaders online forums. Descriptive statistics were used. Epi Info™ software was used for analysis. Chi-square and Fisher's exact test with P < 0.05 were implemented for statistical significance, and odds ratio was used to measure the strength of association among variables. RESULTS: There were 68 respondents in the survey. 13/68 respondents felt prepared for disasters. 16/68 worked at hospitals with 250+ beds and 52/68 represented hospitals with <250 beds. 23/68 participated in hospital committees for disaster, 24/68 participated in simulations or drills, and 22/68 participated in trainings or courses for disasters. Feeling prepared for disasters did not correlate with hospital size (odds ratio [OR] = 2.87 [95% confidence interval (CI): 0.83-9.92], P = 0.91), participation in hospital committees for disaster (OR = 3.10 [95% CI: 1.02-9.26], P = 0.08), and participation in simulations or drills (OR = 2.78 [95% CI: 0.93-8.29], P = 0.11), but participation in disaster trainings and courses appeared to directly correlate with the perception of being prepared (OR = 3.43 [95% CI: 1.13-10.41], P = 0.03). CONCLUSION: Among the 68 centers represented, the majority did not feel their institution to be adequately prepared for disasters, but training appeared to change that perception. A small sample size represents the major limitation of this study.

Natural Disasters.

Natural disasters are extreme events generally caused by abrupt climate change and other environmental factors. Intensive care units (ICUs) need to be prepared, because in the event of a natural disaster, the number of patients that require service stresses an already occupied facility. It is critical that personnel be able to do a proper ICU triage. Efforts have been made to prepare the health care system to be ready for a disaster. A natural disaster can disrupt the daily routine of a hospital and ICU personal need to be equipped with the necessary tools to be able to respond appropriately.

Development of multiple organ dysfunction syndrome in older and young adult trauma patients.

OBJECTIVE: We sought out to determine the correlation between the injury severity score (ISS) and multiple organ dysfunction syndrome (MODS) between severely injured young adults (18-54 years) and elderly (>55 years) patients. MATERIALS AND METHODS: This was a cross-sectional observational study. We included all adult cases (>18 years) diagnosed with trauma defined by the International Classification of Diseases, Ninth Revision. For significance testing, Chi-square test and odds ratio were used. Severe injuries were defined by an ISS >15. The presence of MODS was based on the definitions proposed by society for critical care medicine. RESULTS: A total of 469 young and 173 elderly patients were included in the study. Among the 469 young adults, 193 had ISS >15, whereas out of the 173 elderly patients, 88 had an ISS >15. Severely injured young and elderly groups were more likely to develop MODS compared with those with an ISS <15 (P < 0.001 and P < 0.001, respectively). The elderly had a higher likelihood of developing MODS (P < 0.001; odds ratio: 5.17; 95% confidence interval: 2.74-9.80). CONCLUSION: This study demonstrated a direct relationship between an ISS >15 and the development of MODS. We also observed a five-fold increase in the development of MODS among severely injured elderly patients.

A Bayesian decision support sequential model for severity of illness predictors and intensive care admissions in pneumonia.

BACKGROUND: Community-acquired pneumonia (CAP) is one of the leading causes of morbidity and mortality in the USA. Our objective was to assess the predictive value on critical illness and disposition of a sequential Bayesian Model that integrates Lactate and procalcitonin (PCT) for pneumonia. METHODS: Sensitivity and specificity of lactate and PCT attained from pooled meta-analysis data. Likelihood ratios calculated and inserted in Bayesian/ Fagan nomogram to calculate posttest probabilities. Bayesian Diagnostic Gains (BDG) were analyzed comparing pre and post-test probability. To assess the value of integrating both PCT and Lactate in Severity of Illness Prediction we built a model that combined CURB65 with PCT as the Pre-Test markers and later integrated the Lactate Likelihood Ratio Values to generate a combined CURB 65 + Procalcitonin + Lactate Sequential value. RESULTS: The BDG model integrated a CUBR65 Scores combined with Procalcitonin (LR+ and LR-) for Pre-Test Probability Intermediate and High with Lactate Positive Likelihood Ratios. This generated for the PCT LR+ Post-test Probability (POSITIVE TEST) Posterior probability: 93% (95% CI [91,96%]) and Post Test Probability (NEGATIVE TEST) of: 17% (95% CI [15-20%]) for the Intermediate subgroup and 97% for the high risk sub-group POSITIVE TEST: Post-Test probability:97% (95% CI [95,98%]) NEGATIVE TEST: Post-test probability: 33% (95% CI [31,36%]) . ANOVA analysis for CURB 65 (alone) vs CURB 65 and PCT (LR+) vs CURB 65 and PCT (LR+) and Lactate showed a statistically significant difference (P value = 0.013). CONCLUSIONS: The sequential combination of CURB 65 plus PCT with Lactate yielded statistically significant results, demonstrating a greater predictive value for severity of illness thus ICU level care.

The acute care diagnostics collaboration: Performance assessment of contrast-enhanced ultrasound compared to abdominal computed tomography and conventional ultrasound in an emergency trauma score bayesian clinical decision scheme.

BACKGROUND: Bayes' theorem describes the probability of an event, based on conditions that might be related to the event.[1] We developed the Bayesian Diagnostic Gains (BDG) method as a simple tool for interpreting diagnostic impact.[234567]. AIM: We aimed to evaluate the clinical diagnostic impact of contrast-enhanced ultrasound (CEUS) compared to traditional abdominal computed tomography (CT) and standard ultrasound (US) in a Bayesian Clinical Decision Scheme. MATERIALS AND METHODS: Our mathematical method uses Bayesian Diagnostic Gains (BDG) model. For the purposes of our model, the EMTRAS was used as pretest probability and stratified as low risk (0-3 points = 10%), moderate risk (4-6 points = 42%), and high risk (7-12 points = 80%) based on mortality risk. Sensitivity and specificity for US, CT, and CEUS were obtained from pooled data and used to calculate LR- and LR+. Bayesian/Fagan nomogram was used to attain posttest probabilities using baseline probability of an event on the first axis (PRE), with LR on the second axis, and read off the pos-test probability (POST) on the third axis. For the nomogram analysis, the pretest probability (Pre) scoring for the EMTRAS score was obtained using the original EMTRAS data. Posttest probabilities were obtained based on the Bayes/Fagan Nomgram. Relative diagnostic gain (RDG) and absolute diagnostic gain (ADG) were calculated based on the differences deducted from pre- and post-test probabilities. IBM® SPSS® Statistics 20 was used for analysis and modeling. ANOVA was used for association between EMTRAS, CT scan, and CEUS, where P value set at 0.05. RESULTS: Pooled data for Sensitivity (Se), Specificity (Sp), LR+, and LR- were obtained for US (Se = 45.7%, Sp = 91.8%, LR+ = 5.57, and LR- = 0.59), CEUS (Se 91.4%, Sp 100%, LR+ 91, and LR-0.09), and CT (Se = 94.8%, SP = 98.7%, LR+ = 73, and LR- =0.05). ANOVA analysis for LR+ and LR- showed no significant difference (P < 0.8745 and P < 0.9841). Comparison of CT and CEUS did not yield statistically significant differences for LR+ (P < 0.1). CONCLUSION: In this Bayesian model, the diagnostic performance of CEUS was found to be similar to traditional abdominal CT. The greatest diagnostic gain was observed in low pretest positive LR groups.

Incremental diagnostic quality gain of CTA over V/Q scan in the assessment of pulmonary embolism by means of a Wells score Bayesian model: results from the ACDC collaboration.

OBJECTIVE: Our objective was to evaluate the diagnostic value of computed tomography angiography (CTA) and ventilation perfusion (V/Q) scan in the assessment of pulmonary embolism (PE) by means of a Bayesian statistical model. METHODS: Wells criteria defined pretest probability. Sensitivity and specificity of CTA and V/Q scan for PE were derived from pooled meta-analysis data. Likelihood ratios calculated for CTA and V/Q were inserted in the nomogram. Absolute (ADG) and relative diagnostic gains (RDG) were analyzed comparing post- and pretest probability. Comparative gain difference was calculated for CTA ADG over V/Q scan integrating ANOVA p value set at 0.05. RESULTS: The sensitivity for CT was 86.0% (95% CI: 80.2%, 92.1%) and specificity of 93.7% (95% CI: 91.1%, 96.3%). The V/Q scan yielded a sensitivity of 96% (95% CI: 95%, 97%) and a specificity of 97% (95% CI: 96%, 98%). Bayes nomogram results for CTA were low risk and yielded a posttest probability of 71.1%, an ADG of 56.1%, and an RDG of 374%, moderate-risk posttest probability was 85.1%, an ADG of 56.1%, and an RDG of 193.4%, and high-risk posttest probability was 95.2%, an ADG of 36.2%, and an RDG of 61.35%. The comparative gain difference for low-risk population was 46.1%; in moderate-risk 41.6%; and in high-risk a 22.1% superiority. ANOVA analysis for LR+ and LR- showed no significant difference (p = 0.8745, p = 0.9841 respectively). CONCLUSIONS: This Bayesian model demonstrated a superiority of CTA when compared to V/Q scan for the diagnosis of pulmonary embolism. Low-risk patients are recognized to have a superior overall comparative gain favoring CTA.

Acute Care Diagnostic Collaboration: Bayesian modeling comparative diagnostic assessment of lactate, procalcitonin and CRP in risk stratified population by Mortality in ED (MEDS) score.

OBJECTIVE: To assess and compare the diagnostic value of lactate, procalcitonin (PCT) and C-reactive protein (CRP) in low, moderate, and high-risk stratified population applying Mortality in Emergency Department (MEDS) risk score using Bayesian statistical modeling. METHODS: MEDS criteria was used to risk stratify into low, moderate and high risk. Each population was attributed a percentage risk, and used as pre-test probability in the Bayesian nomogram. Sensitivity and specificity lactate, PCT and CRP were attained from pooled meta-analysis data. Absolute and relative diagnostic gains were calculated. RESULTS: Pooled diagnostic quality data obtained from a meta-analysis reflected sensitivity for PCT of 77% and specificity of 79%, for lactate sensitivity 49.1% and specificity 74.3% and CRP yielded a sensitivity of 75% and specificity 67%. likelihood ratios (LR) calculations for PCT were LR+ 3.67 and LR- 0.29; for lactate LR+ 1.88 and LR- 0.69; CRP LR+ 2.27 and LR- 0.37. When computed in Bayesian nomogram post-test probabilities for LR+ were as follows: for PCT low risk absolute gain of 11.7% and relative gain of 220%; moderate absolute gain 25.7% relative gain 148.5%; for high risk absolute gain 25.1% and relative gain 42.6%. Lactate LR+ results for low risk absolute gain of 4.7% and relative gain of 88.6%; moderate absolute gain 10.7% and relative gain 61.8%; high risk relative gain 14.1% and relative gain 23.9%. CRP results for low population and LR+ absolute gain 5.7% and relative gain 107.5%; moderate risk 14.7% absolute gain and 84.9% relative gain; high risk 77% post-test 18.1% absolute gain and 30.7% relative gain. CONCLUSION: Bayesian statistical model demonstrated the superior diagnostic quality of PCT. For ruling out severe disease, lactate yielded a higher benefit with increased relative gain with negative LR.

Improved rule-out diagnostic gain with a combined aortic dissection detection risk score and D-dimer Bayesian decision support scheme.

The objective of this study was to develop a Bayesian clinical decision support mathematical model that can assist in assessing a diagnostic utility integrating the aortic dissection detection risk score (ADD-RS) combined with the diagnostic quality of D-dimer testing. METHODS: Our method uses the Bayes nomogram. Pretest probability scoring for the ADD-RS was obtained using their derived precalculated effects models. Sensitivity, specificity, and positive and negative likelihood ratios (LRs) for D-dimer testing were obtained by meta-analysis. Posttest probability was obtained from Bayesian statistical modeling integrating low, intermediate, and high pretest for the ADD-RS and LRs for D-dimer testing. Relative (RDG) and absolute (AADG) diagnostic gains were calculated. RESULTS: Pool meta-analysis of D-dimer data demonstrated a sensitivity of 0.97 (95% confidence interval [CI], 0.94-0.99), specificity of 0.56 (95% CI, 0.51-0.60), negative LR of 0.06 (95% CI, 0.03-0.12), and positive LR of 2.43 (95% CI, 1.89-3.12). Bayesian modeling for negative LRs demonstrated posttest probabilities scores of 0.24% for low risk (AADG = 4.06% and RDG=94.42%), 3.4% for intermediate risk (AADG = 33.1% and RDG=90.68%), and 7.9% for high risk (AADG = 51.3% and RDG=86.65%). CONCLUSION: The integration of the ADD-RS and D-dimer testing in a decision support scheme suggested rule-out diagnostic value and gains, mostly evidenced in the AADD-RS low and intermediate pretest probability categories. We propose further evaluating the use of this decision support scheme in a prospective model and as a potential triage tool for aortic dissection.

Bayesian comparative assessment of diagnostic accuracy of low-dose CT scan and ultrasonography in the diagnosis of urolithiasis after the application of the STONE score.

OBJECTIVE: The objective of our study was to assess the diagnostic quality of low-dose computed tomography (CT) when compared to ultrasound (US) in diagnosis of urolithiasis using STONE score as a predictor of pre-test probability and the Bayesian statistical model to calculate post-test probabilities (POST) for both diagnostic tests. METHODS: STONE score was used to form risk groups to obtain pre-test probabilities. Likelihood ratios (LR) were calculated from external data for low-dose CT and US. POST were obtained using pre-test probabilities and likelihood ratios with Bayesian nomogram. Absolute (ADG) and relative (RDG) gains in diagnostic value were calculated. RESULTS: Calculated +LR for US was 12 and -LR was 0.32; for CT, +LR was 19 and -LR 0.04. +LR and low STONE for US yielded POST 57% and RDG 470%; intermediate STONE POST 92% and RDG 84%; and high STONE POST 99% and RDG 10%. -LR and low STONE for US POST 3% and RDG -70%; intermediate POST 24% and RDG -52%; and high STONE POST 74% and RDG -17.7%. +LR and low STONE for CT POST 68% and RDG 580%; moderate STONE POST 95% and RDG 90%; and high STONE POST 99% and RDG 10%. -LR and low STONE for CT POST 0% and RDG -100%; intermediate POST 4% and RDG -92%; and high STONE POST 26% and RDG -71.1%. ANOVA calculations comparing CT vs US for +LR showed no statistical significance (P value = 0.9893; LR- P value = 0.5488). CONCLUSION: Bayesian statistical analysis demonstrated slight superiority of CT scan over US on STONE score low- and moderate-risk stratified subtypes, whereas no significant advantage was seen when evaluating high-probability patients.

Bayesian comparative model of CT scan and ultrasonography in the assessment of acute appendicitis: results from the Acute Care Diagnostic Collaboration project.

The objective of this study was to develop a comparative diagnostic model for computed tomography (CT) and ultrasound (US) in the assessment of acute appendicitis using Alvarado risk score as a predictor of pretest probability and Bayesian statistical model as a tool to calculate posttest probabilities for both diagnostic test. Stratification was made by applying the Alvarado score for the prediction of acute appendicitis. Likelihood ratios were calculated using sensitivity and specificity of both CT and US from a Meta-analysis. Posttest probabilities were obtained after inserting Alvarado score and likelihood ratios into Bayesian nomogram. Absolute and relative gains were calculated. ANOVA was used to assess statistical association. 4341 patients from 31 studies yielded a pooled sensitivity and specificity US of 83% (95% CI, 78%-87%) and 93% (95% CI, 90%-96%) and 94% (95% CI, 92%-95%) and 94% (95% CI, 94%-96%), respectively, for CT studies. Positive likelihood ratios (LR) for US were 12 and negative LR was 0.18; for CT +LR was 16 and -LR 0.06. Bayesian statistical modeling posttest probabilities for +LR and low Alvarado risk results yielded a posttest probability for US of 83.72% and 87.27% for CT, intermediate risk gave 95.88% and 96.88%, high risk 99.37% and 99.53 respectively. No statistical differences were found between Ultrasound and CT. This Bayesian analysis demonstrated slight superiority of CT scan over US low-risk patients, whereas no significant advantage was seen when evaluating intermediate and high risk patients. This study also favored elevated accuracy of the Alvarado score.