Bicarbonate as a predictor of successful insulin transition in critically ill patients with diabetic ketoacidosis: A retrospective cohort study.

BACKGROUND: Treatment of diabetic ketoacidosis with intravenous insulin is effective but resource intensive. Treatment guidelines recommend transitioning to subcutaneous insulin when the anion gap closes, but transition failures due to recrudescent ketoacidosis are common despite adherence to treatment protocols following such guidance. STUDY OBJECTIVE: The primary objective of our study was to evaluate the ability of serum bicarbonate levels of ≤16 mEq/L to predict intravenous to subcutaneous transition failures among those with a normal anion gap at the time of transition. DESIGN AND SETTING: This retrospective cohort study evaluated critically ill adult patients with a primary diagnosis of diabetic ketoacidosis. Historical patient data were obtained by manual chart review. The primary outcome was transition failure, defined as the re-initiation of intravenous insulin within 24 h of transitioning to subcutaneous insulin. Odds ratios were calculated using generalized estimating equations with a logit link and weighted by standardized inverse probability weights to assess the predictive value of serum bicarbonate levels. MAIN RESULTS: The primary analysis included 93 patients with a total of 118 distinct transitions. In the adjusted analysis, patients whose anion gap had normalized but had a serum bicarbonate of ≤16 mEq/L were significantly more likely to experience a transition failure (odds ratio = 4.74, 95% confidence interval: 1.24-18.1, p = 0.02). The results of the unadjusted analysis were similar. CONCLUSIONS: In patients with a normal anion gap at the time of insulin transition, serum bicarbonate levels of ≤16 mEq/L were associated with significantly increased odds of transition failure.

Analysis of Physicians' Probability Estimates of a Medical Outcome Based on a Sequence of Events.

Importance: The probability of a conjunction of 2 independent events is the product of the probabilities of the 2 components and therefore cannot exceed the probability of either component; violation of this basic law is called the conjunction fallacy. A common medical decision-making scenario involves estimating the probability of a final outcome resulting from a sequence of independent events; however, little is known about physicians' ability to accurately estimate the overall probability of success in these situations. Objective: To ascertain whether physicians are able to correctly estimate the overall probability of a medical outcome resulting from 2 independent events. Design, Setting, and Participants: This survey study consisted of 3 separate substudies, in which 215 physicians were asked via internet-based survey to estimate the probability of success of each of 2 components of a diagnostic or prognostic sequence as well as the overall probability of success of the 2-step sequence. Substudy 1 was performed from April 2 to 4, 2021, substudy 2 from November 2 to 11, 2021, and substudy 3 from May 13 to 19, 2021. All physicians were board certified or board eligible in the primary specialty germane to the substudy (ie, obstetrics and gynecology for substudies 1 and 3 and pulmonology for substudy 2), were recruited from a commercial survey service, and volunteered to participate in the study. Exposures: Case scenarios presented in an online survey. Main Outcomes and Measures: Respondents were asked to provide their demographic information in addition to 3 probability estimates. The first substudy included a scenario describing a brow presentation discovered during labor; the 2 conjuncts were the probabilities that the brow presentation would resolve and that the delivery would be vaginal. The second substudy involved a diagnostic evaluation of an incidentally discovered pulmonary nodule; the 2 conjuncts were the probabilities that the patient had a malignant condition and that a technically successful transthoracic needle biopsy would reveal a malignant condition. The third substudy included a modification of the first substudy in an attempt to debias the conjunction fallacy prevalent in the first substudy. Respondents' own probability estimates of the individual events were used to calculate the mathematically correct conjunctive probability. Results: Among 215 respondents, the mean (SD) age was 54.0 (9.5) years; 142 respondents (66.0%) were male. Data on race and ethnicity were not collected. A total of 168 physicians (78.1%) estimated the probability of the 2-step sequence to be greater than the probability of at least 1 of the 2 component events. Compared with the product of their 2 estimated components, respondents overestimated the combined probability by 12.8% (95% CI, 9.6%-16.1%; P < .001) in substudy 1, 19.8% (95% CI, 16.6%-23.0%; P < .001) in substudy 2, and 18.0% (95% CI, 13.4%-22.5%; P < .001) in substudy 3, results that were mathematically incoherent (ie, formally illogical and mathematically incorrect). Conclusions and Relevance: In this survey study of 215 physicians, respondents consistently overestimated the combined probability of 2 events compared with the probability calculated from their own estimates of the individual events. This biased estimation, consistent with the conjunction fallacy, may have substantial implications for diagnostic and prognostic decision-making.

Common things are common, but what is common? Incorporating probability information into differential diagnosis.

The well-known clinical axiom declaring that 'common things are common' attests to the pivotal role of probability in diagnosis. Despite the popularity of this and related axioms, there is no operationalized definition of a common disease, and no practicable way of incorporating actual disease frequencies into differential diagnosis. In this essay, we aim to disambiguate the definition of a common (or rare) disease and show that incidence-not prevalence-is the proper metric of disease frequency for differential diagnosis. We explore how numerical estimates of disease frequencies based on incidence can be incorporated into differential diagnosis as well as the inherent limitations of this method. These concepts have important implications for diagnostic decision making and medical education, and hold promise as a method to improve diagnostic accuracy.

Clinical, Bronchoscopic, and Imaging Findings of e-Cigarette, or Vaping, Product Use-Associated Lung Injury Among Patients Treated at an Academic Medical Center.

Importance: e-Cigarette, or vaping, product use-associated lung injury (EVALI) has caused more than 2800 illnesses and 68 deaths in the United States. Better characterization of this novel illness is needed to inform diagnosis and management. Objective: To describe the clinical features, bronchoscopic findings, imaging patterns, and outcomes of EVALI. Design, Setting, and Participants: This case series of 31 adult patients diagnosed with EVALI between June 24 and December 10, 2019, took place at an academic medical center in Salt Lake City, Utah. Exposures: e-Cigarette use, also known as vaping. Main Outcomes and Measures: Symptoms, laboratory findings, bronchoscopic results, imaging patterns, and clinical outcomes. Results: Data from 31 patients (median [interquartile range] age, 24 [21-31] years) were included in the study. Patients were primarily men (24 [77%]) and White individuals (27 [87%]) who used e-cigarette products containing tetrahydrocannabinol (THC) (29 [94%]). Patients presented with respiratory (30 [97%]), constitutional (28 [90%]), and gastrointestinal (28 [90%]) symptoms. Serum inflammatory markers were elevated in all patients. Bronchoscopy was performed in 23 of 28 inpatients (82%) and bronchoalveolar lavage (BAL) revealed the presence of lipid-laden macrophages (LLMs) in 22 of 24 cases (91%). BAL samples tested positive for Pneumocystis jirovecii (3 patients [13%]), rhinovirus (2 patients [8%]), human metapneumovirus and Aspergillus (1 patient each [4%]); all except human metapneumovirus were determined to be false-positives or clinically inconsequential. The exclusive or dominant computed tomography (CT) pattern was organizing pneumonia in 23 of 26 cases (89%). Patients received antibiotics (26 [84%]) and corticosteroids (24 [77%]), and all survived; 20 patients (65%) seen in follow-up showed marked improvement, but residual symptoms (13 [65%]), radiographic opacities (8 [40%]), and abnormal pulmonary function tests (8 of 18 [44%]) were common. Conclusions and Relevance: In this case series, patients with EVALI characteristically presented with a flu-like illness with elevated inflammatory markers, LLMs on BAL samples, and an organizing pneumonia pattern on CT imaging. Bronchoscopic testing for infection had a high incidence of false-positive results. Patients had substantial residual abnormal results at early follow-up. These data suggest a limited role for bronchoscopy in typical presentations of EVALI without risk factors for alternative diagnoses and the need for careful longitudinal follow-up.

Diagnosis of EVALI: General Approach and the Role of Bronchoscopy.

A 23-year-old man arrives at the ED with a 3-week history of dyspnea, dry cough, fevers, and night sweats. Two weeks previously, he was evaluated in an outpatient clinic and given a course of azithromycin for presumed infectious pneumonia. His symptoms did not improve, and he was seen 1 week later in an urgent care center and given a prescription for doxycycline, which he has been taking without improvement. He states that he feels miserable, has severe nausea and vomiting, and has not eaten in several days. His only medical history is childhood asthma. He reports no surgeries and takes no medications. He has no risk factors for HIV, does not smoke combustible cigarettes or use IV drugs, and has not recently traveled. Examination shows a room air saturation of 89%, a temperature of 38.3°C, and a respiratory rate of 22 breaths/min. Results of his examination are normal, and there are no rales or wheezing heard in the lungs. Chest radiograph shows bilateral, consolidative opacities. WBC count is 14,000, with left shift. Results of biochemistries are normal. Erythrocyte sedimentation rate is 104, and procalcitonin is 0.08. Urine toxicology screen is positive for tetrahydrocannabinol (THC). Asked specifically about vaping and e-cigarette use, he reports that he recently began using THC "carts" that his friend gets from an unknown supplier. What is the diagnosis and what additional steps are necessary to confirm it? Is bronchoscopy indicated?

Do non-inferiority trials of reduced intensity therapies show reduced effects? A descriptive analysis.

OBJECTIVES: To identify non-inferiority trials within a cohort where the experimental therapy is the same as the active control comparator but at a reduced intensity and determine if these non-inferiority trials of reduced intensity therapies have less favourable results than other non-inferiority trials in the cohort. Such a finding would provide suggestive evidence of biocreep in these trials. DESIGN: This metaresearch study used a cohort of non-inferiority trials published in the five highest impact general medical journals during a 5-year period. Data relating to the characteristics and results of the trials were abstracted. PRIMARY OUTCOME MEASURES: Proportions of trials with a declaration of superiority, non-inferiority and point estimates favouring the experimental therapy and mean absolute risk differences for trials with outcomes expressed as a proportion. RESULTS: Our search yielded 163 trials reporting 182 non-inferiority comparisons; 36 comparisons from 31 trials were between the same therapy at reduced and full intensity. Compared with trials not evaluating reduced intensity therapies, fewer comparisons of reduced intensity therapies demonstrated a favourable result (non-inferiority or superiority) (58.3%vs82.2%; P=0.002) and fewer demonstrated superiority (2.8%vs18.5%; P=0.019). Likewise, point estimates for reduced intensity therapies more often favoured active control than those for other trials (77.8%vs39.7%; P<0.001) as did mean absolute risk differences (+2.5% vs -0.7%; P=0.018). CONCLUSIONS: Non-inferiority trials comparing a therapy at reduced intensity to the same therapy at full intensity showed reduced effects compared with other non-inferiority trials. This suggests these trials may have a high rate of type 1 errors and biocreep, with significant implications for the design and interpretation of future non-inferiority trials.

Empirical Consequences of Current Recommendations for the Design and Interpretation of Noninferiority Trials.

BACKGROUND: Noninferiority trials are increasingly common, though they have less standardized designs and their interpretation is less familiar to clinicians than superiority trials. OBJECTIVE: To empirically evaluate a cohort of noninferiority trials to determine 1) their interpretation as recommended by CONSORT, 2) choice of alpha threshold and its sidedness, and 3) differences between methods of analysis such as intention-to-treat and per-protocol. DESIGN: We searched MEDLINE for parallel-group randomized controlled noninferiority trials published in the five highest-impact general medical journals between 2011 and 2016. MAIN MEASURES: Data abstracted included trial design parameters, results, and interpretation of results based on CONSORT recommendations. KEY RESULTS: One hundred sixty-three trials and 182 noninferiority comparisons were included in our analysis. Based on CONSORT-recommended interpretation, 79% of experimental therapies met criteria for noninferiority, 13% met criteria for superiority, 20% were declared inconclusive, and 2% met criteria for inferiority. However, for 12% of trials, the experimental therapy was statistically significantly worse than the active control, but CONSORT recommended an interpretation of inconclusive or noninferior. A two-sided alpha equivalent of greater than 0.05 was used in 34% of the trials, and in five of these trials, the use of a standard two-sided alpha of 0.05 led to changes in the interpretation of results that disfavored the experimental therapy. In four of the five comparisons where different methods of analysis (e.g., intention-to-treat and per-protocol) yielded different results, the intention-to-treat analysis was the more conservative. In 11% of trials, a secondary advantage of the new therapy was neither reported nor could it be inferred by reviewers. CONCLUSIONS: In this cohort, the design and interpretation of noninferiority trials led to significant and systematic bias in favor of the experimental therapy. Clinicians should exercise caution when interpreting these trials. Future trials may be more reliable if design parameters are standardized.

Effect sizes in ongoing randomized controlled critical care trials.

BACKGROUND: An important limitation of many critical care trial designs is that they hypothesize large, and potentially implausible, reductions in mortality. Interpretation of trial results could be improved by systematic assessment of the plausibility of trial hypotheses; however, such assessment has not been attempted in the field of critical care medicine. The purpose of this study was to determine clinicians' views about prior probabilities and plausible effect sizes for ongoing critical care trials where the primary endpoint is landmark mortality. METHODS: We conducted a systematic review of clinical trial registries in September 2015 to identify ongoing critical care medicine trials where landmark mortality was the primary outcome, followed by a clinician survey to obtain opinions about ten large trials. Clinicians were asked to estimate the probability that each trial would demonstrate a mortality effect equal to or larger than that used in its sample size calculations. RESULTS: Estimates provided by individual clinicians varied from 0% to 100% for most trials, with a median estimate of 15% (IQR 10-20%). The median largest absolute mortality reduction considered plausible was 4.5% (IQR 3.5-5%), compared with a median absolute mortality reduction used in sample size calculations of 5% (IQR 3.6-10%) (P = 0.27). CONCLUSIONS: For some of the largest ongoing critical care trials, many clinicians regard prior probabilities as low and consider that plausible effects on absolute mortality are less than 5%. Further work is needed to determine whether pooled estimates obtained by surveying clinicians are replicable and accurate or whether other methods of estimating prior probability are preferred.