Performance evaluation of ChatGPT in detecting diagnostic errors and their contributing factors: an analysis of 545 case reports of diagnostic errors.

BACKGROUND: Manual chart review using validated assessment tools is a standardised methodology for detecting diagnostic errors. However, this requires considerable human resources and time. ChatGPT, a recently developed artificial intelligence chatbot based on a large language model, can effectively classify text based on suitable prompts. Therefore, ChatGPT can assist manual chart reviews in detecting diagnostic errors. OBJECTIVE: This study aimed to clarify whether ChatGPT could correctly detect diagnostic errors and possible factors contributing to them based on case presentations. METHODS: We analysed 545 published case reports that included diagnostic errors. We imputed the texts of case presentations and the final diagnoses with some original prompts into ChatGPT (GPT-4) to generate responses, including the judgement of diagnostic errors and contributing factors of diagnostic errors. Factors contributing to diagnostic errors were coded according to the following three taxonomies: Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC) and Generic Diagnostic Pitfalls (GDP). The responses on the contributing factors from ChatGPT were compared with those from physicians. RESULTS: ChatGPT correctly detected diagnostic errors in 519/545 cases (95%) and coded statistically larger numbers of factors contributing to diagnostic errors per case than physicians: DEER (median 5 vs 1, p<0.001), RDC (median 4 vs 2, p<0.001) and GDP (median 4 vs 1, p<0.001). The most important contributing factors of diagnostic errors coded by ChatGPT were 'failure/delay in considering the diagnosis' (315, 57.8%) in DEER, 'atypical presentation' (365, 67.0%) in RDC, and 'atypical presentation' (264, 48.4%) in GDP. CONCLUSION: ChatGPT accurately detects diagnostic errors from case presentations. ChatGPT may be more sensitive than manual reviewing in detecting factors contributing to diagnostic errors, especially for 'atypical presentation'.

The importance of the palatine bone for endoscopic endonasal skull base surgery.

Endoscopic endonasal skull base surgery is increasingly prevalent, with its scope expanding from pathogens in the midline region to those in the paramedian region. Maximizing anterior sphenoidectomy is important for the median approach, and lateralizing the pterygopalatine fossa is crucial for the paramedian approach. Maximizing the surgical corridor in the nasal cavity and minimizing damage to neurovascular structures are vital for establishing a surgical field with minimal bleeding, ensuring safe, precise, and gentle procedures. However, the relationship between the maxillofacial and skull base bones in endoscopic endonasal skull base surgery is difficult to understand because these bones are intricately articulated, making it challenging to visualize each bone's outline. Understanding important bones and their related neurovascular structures is essential for all skull base surgeons to maximize the surgical corridor and minimize iatrogenic injury to neurovascular structures. This study aimed to elucidate the role of the palatine bone from a microsurgical anatomical perspective. Three dry skulls were used to demonstrate the structure of the palatine bone and its relationship with surrounding bones. A formalin-perfused cadaveric head was dissected to show the related neurovascular structures. The arteries and veins of the cadaveric heads were injected with red- and blue-colored silicon. Dissection was performed using a surgical microscope and endoscope. In addition, the utilization of the palatine bone as a landmark to identify neurovascular structures, which aids in creating a wider surgical field with less bleeding, was shown in two representative cases. The palatine bone consists of unique complex structures, including the sphenoidal process, ethmoidal crest, pterygopalatine canal, and sphenopalatine notch, which are closely related to the sphenopalatine artery, maxillary nerve, and its branches. The ethmoidal crest of the palatine bone is a well-known structure that is useful for identifying the sphenopalatine foramen, controlling the sphenopalatine artery and nerve, and safely opening the pterygopalatine fossa. The sphenoidal process of the palatine bone is a valuable landmark for identifying the palatovaginal artery, which is a landmark used to safely and efficiently expose the vidian canal. The sphenoidal process is easily cracked with an osteotome and removed to expose the palatovaginal artery, which runs along the pharyngeal groove, just medial to the vidian canal. By opening the pterygopalatine canal (also known as the greater palatine canal), further lateralization of the periosteum-covered pterygopalatine fossa contents can be achieved. Overall, the sphenoidal process and ethmoidal crest can be used as important landmarks to maximize the surgical corridor and minimize unnecessary injury to neurovascular structures.

Evaluating ChatGPT-4's Diagnostic Accuracy: Impact of Visual Data Integration.

BACKGROUND: In the evolving field of health care, multimodal generative artificial intelligence (AI) systems, such as ChatGPT-4 with vision (ChatGPT-4V), represent a significant advancement, as they integrate visual data with text data. This integration has the potential to revolutionize clinical diagnostics by offering more comprehensive analysis capabilities. However, the impact on diagnostic accuracy of using image data to augment ChatGPT-4 remains unclear. OBJECTIVE: This study aims to assess the impact of adding image data on ChatGPT-4's diagnostic accuracy and provide insights into how image data integration can enhance the accuracy of multimodal AI in medical diagnostics. Specifically, this study endeavored to compare the diagnostic accuracy between ChatGPT-4V, which processed both text and image data, and its counterpart, ChatGPT-4, which only uses text data. METHODS: We identified a total of 557 case reports published in the American Journal of Case Reports from January 2022 to March 2023. After excluding cases that were nondiagnostic, pediatric, and lacking image data, we included 363 case descriptions with their final diagnoses and associated images. We compared the diagnostic accuracy of ChatGPT-4V and ChatGPT-4 without vision based on their ability to include the final diagnoses within differential diagnosis lists. Two independent physicians evaluated their accuracy, with a third resolving any discrepancies, ensuring a rigorous and objective analysis. RESULTS: The integration of image data into ChatGPT-4V did not significantly enhance diagnostic accuracy, showing that final diagnoses were included in the top 10 differential diagnosis lists at a rate of 85.1% (n=309), comparable to the rate of 87.9% (n=319) for the text-only version (P=.33). Notably, ChatGPT-4V's performance in correctly identifying the top diagnosis was inferior, at 44.4% (n=161), compared with 55.9% (n=203) for the text-only version (P=.002, χ2 test). Additionally, ChatGPT-4's self-reports showed that image data accounted for 30% of the weight in developing the differential diagnosis lists in more than half of cases. CONCLUSIONS: Our findings reveal that currently, ChatGPT-4V predominantly relies on textual data, limiting its ability to fully use the diagnostic potential of visual information. This study underscores the need for further development of multimodal generative AI systems to effectively integrate and use clinical image data. Enhancing the diagnostic performance of such AI systems through improved multimodal data integration could significantly benefit patient care by providing more accurate and comprehensive diagnostic insights. Future research should focus on overcoming these limitations, paving the way for the practical application of advanced AI in medicine.

Misleading presentations in functional food trials led by contract research organizations were frequently observed in Japan: meta-epidemiological study.

OBJECTIVES: The functional food market has experienced significant growth, leading to an uptick in clinical trials conducted by contract research organizations (CROs). Research focusing on CRO-managed trials and the communication of trial outcomes to the consumer market remains underexplored. This metaepidemiological study aims to evaluate the quality of randomized controlled trials (RCTs) facilitated by prominent CROs in Japan and to examine the quality of the representations used to convey their results to consumers. STUDY DESIGN AND SETTING: This study focused on the food trials that were registered in the University Hospital Medical Information Network Clinical Trial Registry or the International Clinical Trials Registry Platform by the top 5 CROs. Press releases of study results or advertisements of food products based on the study results were identified by conducting a Google search. The risk of bias in the RCT publications was independently assessed by 2 reviewers, who also evaluated the presence of "spin" in the abstracts and full texts. An assessment of "spin" in press releases/advertisements was undertaken. RESULTS: A total of 76 RCT registrations, 32 RCT publications, and 11 press releases/advertisements were included. Approximately 72% of the RCT publications exhibited a high risk of bias due to selective outcome reporting. "Spin" was present in the results of the abstract (72%), abstract conclusion (81%), full-text results (44%), and full-text conclusion (84%). "Spin" appeared in 73% of press releases/advertisements due to the selective outcome reporting. CONCLUSION: Functional food presentations in Japan frequently contained "spin." The Japanese government should more rigorously check whether food manufacturers report outcomes selectively.

ChatGPT-Generated Differential Diagnosis Lists for Complex Case-Derived Clinical Vignettes: Diagnostic Accuracy Evaluation.

BACKGROUND: The diagnostic accuracy of differential diagnoses generated by artificial intelligence chatbots, including ChatGPT models, for complex clinical vignettes derived from general internal medicine (GIM) department case reports is unknown. OBJECTIVE: This study aims to evaluate the accuracy of the differential diagnosis lists generated by both third-generation ChatGPT (ChatGPT-3.5) and fourth-generation ChatGPT (ChatGPT-4) by using case vignettes from case reports published by the Department of GIM of Dokkyo Medical University Hospital, Japan. METHODS: We searched PubMed for case reports. Upon identification, physicians selected diagnostic cases, determined the final diagnosis, and displayed them into clinical vignettes. Physicians typed the determined text with the clinical vignettes in the ChatGPT-3.5 and ChatGPT-4 prompts to generate the top 10 differential diagnoses. The ChatGPT models were not specially trained or further reinforced for this task. Three GIM physicians from other medical institutions created differential diagnosis lists by reading the same clinical vignettes. We measured the rate of correct diagnosis within the top 10 differential diagnosis lists, top 5 differential diagnosis lists, and the top diagnosis. RESULTS: In total, 52 case reports were analyzed. The rates of correct diagnosis by ChatGPT-4 within the top 10 differential diagnosis lists, top 5 differential diagnosis lists, and top diagnosis were 83% (43/52), 81% (42/52), and 60% (31/52), respectively. The rates of correct diagnosis by ChatGPT-3.5 within the top 10 differential diagnosis lists, top 5 differential diagnosis lists, and top diagnosis were 73% (38/52), 65% (34/52), and 42% (22/52), respectively. The rates of correct diagnosis by ChatGPT-4 were comparable to those by physicians within the top 10 (43/52, 83% vs 39/52, 75%, respectively; P=.47) and within the top 5 (42/52, 81% vs 35/52, 67%, respectively; P=.18) differential diagnosis lists and top diagnosis (31/52, 60% vs 26/52, 50%, respectively; P=.43) although the difference was not significant. The ChatGPT models' diagnostic accuracy did not significantly vary based on open access status or the publication date (before 2011 vs 2022). CONCLUSIONS: This study demonstrates the potential diagnostic accuracy of differential diagnosis lists generated using ChatGPT-3.5 and ChatGPT-4 for complex clinical vignettes from case reports published by the GIM department. The rate of correct diagnoses within the top 10 and top 5 differential diagnosis lists generated by ChatGPT-4 exceeds 80%. Although derived from a limited data set of case reports from a single department, our findings highlight the potential utility of ChatGPT-4 as a supplementary tool for physicians, particularly for those affiliated with the GIM department. Further investigations should explore the diagnostic accuracy of ChatGPT by using distinct case materials beyond its training data. Such efforts will provide a comprehensive insight into the role of artificial intelligence in enhancing clinical decision-making.

Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors.

OBJECTIVES: To assess the usefulness of case reports as sources for research on diagnostic errors in uncommon diseases and atypical presentations. CONTENT: We reviewed 563 case reports of diagnostic error. The commonality of the final diagnoses was classified based on the description in the articles, Orphanet, or epidemiological data on available references; the typicality of presentation was classified based on the description in the articles and the judgment of the physician researchers. Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC), and Generic Diagnostic Pitfalls (GDP) taxonomies were used to assess the factors contributing to diagnostic errors. SUMMARY AND OUTLOOK: Excluding three cases in that commonality could not be classified, 560 cases were classified into four categories: typical presentations of common diseases (60, 10.7 %), atypical presentations of common diseases (35, 6.2 %), typical presentations of uncommon diseases (276, 49.3 %), and atypical presentations of uncommon diseases (189, 33.8 %). The most important DEER taxonomy was "Failure/delay in considering the diagnosis" among the four categories, whereas the most important RDC and GDP taxonomies varied with the categories. Case reports can be a useful data source for research on the diagnostic errors of uncommon diseases with or without atypical presentations.

Comparing clinical outcomes of ARB and ACEi in patients hospitalized for acute COVID-19.

Continued receipt of Renin-Angiotensin-Aldosterone inhibitors in patients with COVID-19 has shown potential in producing better clinical outcomes. However, superiority between ACEi (angiotensin-converting enzyme inhibitors) and ARB (angiotensin II receptor blockers) regarding clinical outcomes in this setting remains unknown. We retrospectively collected data on patients hospitalized for acute COVID-19 using the nationwide administrative database (Diagnosis and Procedure Combinations, DPC). The DPC data covered around 25% of all acute care hospitals in Japan. Patient outcomes, with focus on inpatient mortality, were compared between patients previously prescribed ACEi and those prescribed ARB. Comparisons based on crude, multivariate and propensity-score adjusted analysis were conducted. We examined a total of 7613 patients (ARB group, 6903; ACEi group 710). The ARB group showed lower crude in-hospital mortality, compared to the ACEi group (5% vs 8%; odds ratio, 0.65; 95% CI 0.48-0.87), however not in the multivariate-adjusted model (odds ratio, 0.95; 95% CI 0.69-1.3) or propensity-score adjusted models (odds ratio, 0.86; 95% CI 0.63-1.2). ARB shows potential in reducing hospital stay duration over ACEi in patients admitted for COVID-19, but does not significantly reduce in-hospital mortality. Further prospective studies are needed to draw a definitive conclusion, but continuation of either of these medications is warranted to improve clinical outcomes.

Takedown and Reuse of a Posterior Septal Nasal Floor Mucosal Flap for Skull Base Reconstruction in a Revision Surgery for a Recurrent Pituitary Tumor.

Various types of mucosal flaps can be used for skull base reconstruction after endoscopic endonasal skull base surgery (EESS). Preventing postoperative cerebrospinal fluid (CSF) leakage is essential. Flap creation during revision surgery can be problematic. We present a patient in whom a posterior septal nasal floor flap (PS-NF) was successfully reused for reconstruction after multiple reoperations for pituitary tumor resection. A 22-year-old female underwent EESS for resection of a pituitary tumor and experienced multiple recurrences after repeated operations. For the third recurrence, a skull base surgery team comprising otolaryngologists and neurosurgeons performed a binostril combined transnasal/transseptal approach and used a PS-NF for reconstruction. For the fourth recurrence, a PS-NF was successfully taken down and reused for reconstruction. No postoperative CSF leakage or intranasal complications occurred. Skull base reconstruction using a PS-NF is feasible and preserves the mucous membrane of the nasal septum and the morphology of the nasal cavity. PS-NF takedown and reuse is an option for revision EESS for recurrent pituitary tumors.

Anatomy of small canals around the jugular foramen: Special reference to Jacobson's and Arnold's nerves.

The jugular foramen harbors anatomically complex bony, venous and neural structures. It is closely associated with small canals including the mastoid, tympanic, and cochlear canaliculi, and the stylomastoid foramen. The minute intraosseous branches of Arnold's and Jacobson's nerves (<1 mm in length) remain difficult to study with current imaging techniques, and cadaveric dissection is the most reliable approach. Our aim was to examine the variations of Jacobson's and Arnold's canaliculi and nerves and to provide detailed cadaveric graphics. To reveal the anatomical structures of small canals around the jugular foramen, 25 sides of dry skulls and 14 sides of cadaveric heads were examined. Intraosseous branches varied more in Arnold's nerve than Jacobson's nerve. In our cadaveric dissection, all specimens formed a single canal for Jacobson's nerve connecting the jugular foramen to the tympanic cavity. The intraosseous course of Arnold's nerve varied in its communication with the facial nerve. A descending branch crossing the facial nerve was identified in five of 14 sides, an ascending branch in 13. In two specimens, an ascending branch clearly reached the base of the stapedius muscle. Classical anatomical studies of cadavers remain a supplementary tool for analyzing these tiny structures. The present study confirms Gray's findings of 1913. Variations of these nerves could be even more complex than previously reported. Our study provides additional information regarding the anatomy of Jacobson's and Arnold's nerves.

Inpatient antibiotic prescribing patterns using the World Health Organization (WHO) Access Watch and Reserve (AWaRe) classification in Okinawa, Japan: A point-prevalence survey.

Using point-prevalence methodology and the World Health Organization (WHO) Access, Watch, and Reserve Classification, we measured antibiotic use in 5 hospitals in Okinawa, Japan, on October 1, 2020. Overall, 29% of patients were prescribed an antibiotic on the survey date and the 3 most used antibiotics in the "Watch" category were cefazolin, ampicillin-sulbactam, and ampicillin.

Prevalence and characteristics of antibiotic prescription for acute COVID-19 patients in Japan.

COVID-19 is a viral infection and does not require antibiotics. The study aimed to elucidate a prescribing pattern of antibiotics for COVID-19. A nationwide cross-sectional study was conducted in Japan. The Diagnosis and Procedure Combinations (DPC) data was used to collect information, covering 25% of all acute care hospitals in the country. In 140,439 COVID-19 patients, 18,550 (13.21%) patients received antibiotics. Antibiotics were prescribed more often in inpatients (10,809 out of 66,912, 16.15%) than outpatients (7741 out of 73,527, 10.53%) (p < 0.001). Outpatient prescription was significantly associated with older patients (odds ratio [OR], 4.66; 95% confidence interval [CI] 4.41-4.93) and a greater Charlson index (OR with one-point index increase, 1.22; 95% CI 1.21-1.23). Inpatient prescription was significantly associated with older patients (OR 2.10; 95% CI 2.01-2.21), male gender (OR 1.12, 95% CI 1.07-1.18), a greater Charlson index (OR with one-point increase, 1.06; 95% CI 1.05-1.07), requirement of oxygen therapy (OR 3.44; 95% CI 3.28-3.60) and mechanical ventilation (OR 15.09; 95% CI 13.60-16.74). The most frequently prescribed antibiotic among outpatients was cefazolin, while that among inpatients was ceftriaxone. Antibiotic prescription is relatively low for acute COVID-19 in Japan. Antibiotic prescription was associated with older age, multi-morbidity, severe disease, and winter season.

Retracted randomized controlled trials were cited and not corrected in systematic reviews and clinical practice guidelines.

BACKGROUND AND OBJECTIVES: To investigate whether and when the correction is done in Systematic Reviews (SRs) and Clinical Practice Guidelines (CPGs) when included Randomized Controlled Trials (RCTs) have been retracted. METHODS: In this meta-epidemiological study, we included SRs and CPGs citing the retracted RCTs from the Retraction Watch Database. We investigated how often the retracted RCTs were cited in SRs and CPGs. We also investigated whether and when such SRs and CPGs corrected themselves. RESULTS: We identified 587 articles (525 SRs and 62 CPGs) citing retracted RCTs. Among the 587 articles, 252 (43%) were published after retraction, and 335 (57%) were published before retraction. Among 127 articles published citing already retracted RCTs in their evidence synthesis without caution, none corrected themselves after publication. Of 335 articles published before retraction, 239 included RCTs that were later retracted in their evidence synthesis. Among them, only 5% of SRs (9/196) and 5% of CPGs (2/43) corrected or retracted their results. CONCLUSION: Many SRs and CPGs included already or later retracted RCTs without caution. Most of them were never corrected. The scientific community, including publishers and researchers, should make systematic and concerted efforts to remove the impact of retracted RCTs.

Lung Rest with Femoro-Femoral Veno-Venous Extracorporeal Membrane Oxygenation for COVID-19 Severe Pneumonia with Pneumomediastinum.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sometimes causes severe coronavirus disease 2019 (COVID-19) pneumonia. Here, we report the case of a 35-year-old man with obesity who showed severe respiratory failure from SARS-CoV-2 infection. Immediate high-resolution computed tomography (HRCT) of the chest after endotracheal intubation revealed a significant pneumomediastinum with diffuse ground-glass opacity and consolidation. Ventilator management was difficult with low tidal volume and low positive end expiratory pressure. Therefore, we administered extracorporeal membrane oxygenation (ECMO) to allow lung rest and prevent further progression of the pneumomediastinum and maintain oxygenation. Since implementing ECMO, the patient's oxygenation has stabilized and follow-up HRCT of the chest revealed dramatic improvement of the pneumomediastinum. We gradually tapered off ECMO and employed a pressure-control mode. He was extubated on day 11. To our knowledge, this is the first reported patient who showed complete pneumomediastinum recovery from COVID-19 pneumonia with ECMO.

External validation for sensitivity of the Ottawa subarachnoid hemorrhage rule in a Japanese tertiary teaching hospital.

The Ottawa subarachnoid hemorrhage (OSAH) rule is a validated clinical prediction rule for ruling out subarachnoid hemorrhage (SAH). Another SAH rule (Ottawa-like rule) was developed in Japan but was not well validated. We aimed to validate both rules by examining the sensitivity for ruling out SAH in Japanese patients diagnosed with SAH. We conducted a retrospective cohort study by reviewing the medical records of consecutive adult patients hospitalized with SAH at a tertiary-care teaching hospital in Japan who visited our emergency department between July 2009 and June 2019. Sensitivity and its 95% confidence interval (CI) were estimated for each rule for the diagnosis of SAH. In a total of 280 patients with SAH, 56 (20.0%) patients met the inclusion criteria and were analyzed for the OSAH rule, and a sensitivity of the OSAH rule was 56/56 (100%; 95% CI 93.6-100%). While, 126 (45%) patients met the inclusion criteria of the Ottawa-like rule, and the rule showed a sensitivity of 125/126 (99.2%; 95%CI 95.7-100%). The OSAH rule showed 100% sensitivity among our Japanese patients diagnosed with SAH. The implementation of the Ottawa-like rule should be cautious because the false-negative rate is up to 4%.

Auditory function analysis in immunodeficient STAT1 knock-out mice: Considerations for viral infection models.

The STAT1 knock-out (KO) mouse is a frequently used transgenic immunodeficient strain to model human viral and bacterial diseases. The Lassa fever model was established in the STAT1 KO mice mimicking phenotypes seen in human patients including deafness in survivors. This model develops hearing loss at high prevalence and is a valuable tool to investigate viral infection-induced hearing loss. However, Lassa virus is a highly contagious and regulated agent requiring the unique logistics of the biosafety level 4 posing limitations for experimental work. Therefore, we did a detailed auditory analysis of the STAT1 KO mice to assess baseline auditory function in preparation for further auditory behavioral studies. Auditory brainstem response and distortion product otoacoustic emission tests were performed on males and females of the STAT1 KO mice and was compared to 129S6/SvEv wild type (WT) mice. The male WT mice had the best auditory performance and the female WT mice had the worst hearing performance. The male and female STAT1 KO mice had similar auditory performance to each other, which was intermediate between WT males and females. We conclude that both male and female STAT1 KO mice are suitable for studying viral infection-induced hearing loss.

Cardiac auscultation skills among junior doctors: effects of sound simulation lesson.

OBJECTIVES: To evaluate the effect of a sound simulation lesson to improve cardiac auscultation skills among junior doctors. METHODS: This study is based on the design of test comparison before and after educational intervention using a convenient sample. For 50 junior doctors in Japan, diagnostic accuracy before and after a sound simulation lesson for cardiac auscultation skills was compared. There were 15 doctors who experienced cardiology rotation. The lesson used seven abnormal cardiac recordings (third heart sound, double gallop, aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, and pericardial friction rub). At tests before and after the lesson, the doctors listened to random sound outputs of the same seven recordings, chose diagnostic findings from multiple-choice items, and obtained individual diagnostic accuracy based on the total number of choosing correct findings. Top 10 doctors obtaining the greatest individual accuracy received a commendation. RESULTS: Pre-lesson diagnostic accuracy was not different between doctors with cardiology rotation training (total diagnostic accuracy of the group, 27/105 [26%]) and those without cardiology rotation (70/245 [29%]). Compared to pre-lesson, post-lesson total diagnostic accuracy significantly improved with about two-folds (97/350 [28%] vs 170/350 [61%]; McNemar Test, p<0.0001). The improvement was significant for double gallop (5/50 [10%] vs. 15/50 [30%]), mitral stenosis (0/50 [0%] vs. 6/50 [12%]), and pericardial friction rub (1/50 [2%] vs. 35/50 [70%]). CONCLUSIONS: The use of a simple sound simulation lesson may help junior doctors to learn cardiac auscultation skills. Clinician educators are encouraged to use this strategy in addition to cardiology rotation training.

History of diabetes may delay antibiotic administration in patients with severe sepsis presenting to emergency departments.

Clinical manifestations of sepsis differ between patients with and without diabetes mellitus (DM), and these differences could influence the clinical behaviors of medical staff. Therefore, we aimed to investigate whether pre-existing DM was associated with the time to antibiotics or sepsis care protocols.This was a retrospective cohort study.It conducted at 53 intensive care units (ICUs) in Japan.Consecutive adult patients with severe sepsis admitted directly to ICUs form emergency departments from January 2016 to March 2017 were included.The primary outcome was time to antibiotics.Of the 619 eligible patients, 142 had DM and 477 did not have DM. The median times (interquartile ranges) to antibiotics in patients with and without DM were 103 minutes (60-180 minutes) and 86 minutes (45-155 minutes), respectively (P = .05). There were no significant differences in the rates of compliance with sepsis protocols or with patient-centred outcomes such as in-hospital mortality. The mortality rates of patients with and without DM were 23.9% and 21.6%, respectively (P = .55). Comparing patients with and without DM, the gamma generalized linear model-adjusted relative difference indicated that patients with DM had a delay to starting antibiotics of 26.5% (95% confidence intervals (95%CI): 4.6-52.8, P = .02). The gamma generalized linear model-adjusted relative difference with multiple imputation for missing data of sequential organ failure assessment was 19.9% (95%CI: 1.0-42.3, P = .04). The linear regression model-adjusted beta coefficient indicated that patients with DM had a delay to starting antibiotics of 29.2 minutes (95%CI: 6.8-51.7, P = .01). Logistic regression modelling showed that pre-existing DM was not associated with in-hospital mortality (odds ratio, 1.26; 95%CI: 0.72-2.19, P = .42).Pre-existing DM was associated with delayed antibiotic administration among patients with severe sepsis or septic shock; however, patient-centred outcomes and compliance with sepsis care protocols were comparable.

Strength of Humic Acid Aggregates: Effects of Divalent Cations and Solution pH.

Aggregation-dispersion, charging, and aggregate strength of Leonardite humic acid (LHA) were investigated in CaCl2 and MgCl2 solutions as a function of pH and ionic strength (I). The strength or the withstanding force of aggregates of humic substances (HSs) against breakage is important because this force influences the transport and distribution of pollutants and nutrients along with HSs through the change in the size of HS aggregates as a transport unit. We observed the dominancy of aggregation of LHA at high pH than at low pH in every case of CaCl2 and MgCl2 solutions. This observation suggests the higher binding efficiency of these divalent ions at high pH, though there was no obvious relation with electrophoretic mobility and aggregation of LHA. Further, we first revealed the numerical value of the strength of HS aggregates by using a simple experimental setup of aggregate breakup under laminar converging flow through a capillary tube. The obtained values of the strength of LHA aggregates were higher in the presence of CaCl2 solution than MgCl2 solution, and the strength increased with pH. The highest strengths of LHA aggregates in 30 mM (I) CaCl2 and MgCl2 solutions were around 5.8 and 2.4 nN, respectively, at pH around 9.