SWATH-MS-based proteogenomic analysis reveals the involvement of alternative splicing in poplar upon lead stress.

Alternative splicing (AS) regulates gene expression and increases proteomic diversity for the fine tuning of stress responses in plants, but the exact mechanism through which AS functions in plant stress responses is not thoroughly understood. Here, we investigated how AS functions in poplar (Populus trichocarpa), a popular plant for bioremediation, in response to lead (Pb) stress. Using a proteogenomic analysis, we determine that Pb stress induced alterations in AS patterns that are characterized by an increased use of nonconventional splice sites and a higher abundance of Pb-responsive splicing factors (SFs) associated with Pb-responsive transcription factors. A strong Pb(II)-inducible chaperone protein, PtHSP70, that undergoes AS was further characterized. Overexpression of its two spliced isoforms, PtHSP70-AS1 and PtHSP70-AS2, in poplar and Arabidopsis significantly enhances the tolerance to Pb. Further characterization shows that both isoforms can directly bind to Pb(II), and PtHSP70-AS2 exhibits 10-fold higher binding capacities and a greater increase in expression under Pb stress, thereby reducing cellular toxicity through Pb(II) extrusion and conferring Pb tolerance. AS of PtHSP70 is found to be regulated by PtU1-70K, a Pb(II)-inducible core SF involved in 5'-splice site recognition. Because the same splicing pattern is also found in HSP70 orthologs in other plant species, AS of HSP70 may be a common regulatory mechanism to cope with Pb(II) toxicity. Overall, we have revealed a novel post-transcriptional machinery that mediates heavy metal tolerance in diverse plant species. Our findings offer new molecular targets and bioengineering strategies for phytoremediation and provide new insight for future directions in AS research.

Disruption of p-coumaroyl-CoA:monolignol transferases in rice drastically alters lignin composition.

Grasses are abundant feedstocks that can supply lignocellulosic biomass for production of cell-wall-derived chemicals. In grass cell walls, lignin is acylated with p-coumarate. These p-coumarate decorations arise from the incorporation of monolignol p-coumarate conjugates during lignification. A previous biochemical study identified a rice (Oryza sativa) BAHD acyltransferase (AT) with p-coumaroyl-CoA:monolignol transferase (PMT) activity in vitro. In this study, we determined that that enzyme, which we name OsPMT1 (also known as OsAT4), and the closely related OsPMT2 (OsAT3) harbor similar catalytic activity toward monolignols. We generated rice mutants deficient in either or both OsPMT1 and OsPMT2 by CRISPR/Cas9-mediated mutagenesis and subjected the mutants' cell walls to analysis using chemical and nuclear magnetic resonance methods. Our results demonstrated that OsPMT1 and OsPMT2 both function in lignin p-coumaroylation in the major vegetative tissues of rice. Notably, lignin-bound p-coumarate units were undetectable in the ospmt1 ospmt2-2 double-knockout mutant. Further, in-depth structural analysis of purified lignins from the ospmt1 ospmt2-2 mutant compared with control lignins from wild-type rice revealed stark changes in polymer structures, including alterations in syringyl/guaiacyl aromatic unit ratios and inter-monomeric linkage patterns, and increased molecular weights. Our results provide insights into lignin polymerization in grasses that will be useful for the optimization of bioengineering approaches for the effective use of biomass in biorefineries.

Multifunctional 5-hydroxyconiferaldehyde O-methyltransferases (CAldOMTs) in plant metabolism.

Lignin, flavonoids, melatonin, and stilbenes are plant specialized metabolites with diverse physiological and biological functions, supporting plant growth and conferring stress resistance. Their biosynthesis requires O-methylations catalyzed by 5-hydroxyconiferaldehyde O-methyltransferase (CAldOMT; also called caffeic acid O-methyltransferase, COMT). CAldOMT was first known for its roles in syringyl (S) lignin biosynthesis in angiosperm cell walls and later found to be multifunctional. This enzyme also catalyzes O-methylations in flavonoid, melatonin, and stilbene biosynthetic pathways. Phylogenetic analysis indicated the convergent evolution of enzymes with OMT activities towards the monolignol biosynthetic pathway intermediates in some gymnosperm species that lack S-lignin and Selaginella moellendorffii, a lycophyte which produces S-lignin. Furthermore, neofunctionalization of CAldOMTs occurred repeatedly during evolution, generating unique O-methyltransferases (OMTs) with novel catalytic activities and/or accepting novel substrates, including lignans, 1,2,3-trihydroxybenzene, and phenylpropenes. This review summarizes multiple aspects of CAldOMTs and their related proteins in plant metabolism and discusses their evolution, molecular mechanism, and roles in biorefineries, agriculture, and synthetic biology.

Improving the performance of machine learning penicillin adverse drug reaction classification with synthetic data and transfer learning.

BACKGROUND: Machine learning may assist with the identification of potentially inappropriate penicillin allergy labels. Strategies to improve the performance of existing models for this task include the use of additional training data, synthetic data and transfer learning. AIMS: The aims of this study were to investigate the use of additional training data and novel machine learning strategies, namely synthetic data and transfer learning, to improve the performance of penicillin adverse drug reaction (ADR) machine learning classification. METHODS: Machine learning natural language processing was applied to free-text penicillin ADR data extracted from a public health system electronic health record (EHR). The models were developed by training on various labelled data sets. ADR entries were split into training and testing data sets and used to develop and test a variety of machine learning models. The effect of training on additional data and synthetic data versus the use of transfer learning was analysed. RESULTS: Following the application of these techniques, the area under the receiver operator curve of best-performing models for the classification of penicillin allergy (vs intolerance) and high-risk allergy (vs low-risk allergy) improved to 0.984 (using the artificial neural network model) and 0.995 (with the transfer learning approach) respectively. CONCLUSIONS: Machine learning models demonstrate high levels of accuracy in the classification and risk stratification of penicillin ADR labels using the reaction documented in the EHR. The model can be further optimised by incorporating additional training data and using transfer learning. Practical applications include automating case detection for penicillin allergy delabelling programmes.

Tracing the barriers to decarbonising ophthalmology: A review.

As climate change demands increasingly urgent mitigation of greenhouse gas emissions, the health sector needs to do its part to decarbonise. Ophthalmologists share concerns about climate change and seek opportunities to reduce their environmental impact. When measuring the footprint of ophthalmology, major contributions are from patient travel to clinics, and from the large amounts of single-use disposable materials that are consumed during surgeries and sterile procedures. Ophthalmic services in India have already demonstrated systems that consume far fewer of these products through efficient throughput of patients and the safe reuse of many items, while maintaining equivalent safety and quality outcomes. Choosing these low-cost low-emission options would seem obvious, but many ophthalmologists experience barriers that prevent them operating as Indian surgeons do. Understanding these barriers to change is a crucial step in the decarbonisation of ophthalmology and the health sector more broadly.

Asymptomatic Covid-19 Trauma Patients Have Worse Outcomes and Resource Utilization: A Matched Cohort Study.

OBJECTIVE: To evaluate the impact of COVID-19 positivity on outcomes and resource utilization in the trauma population. INTRODUCTION: COVID-19 infection worsens outcomes of trauma patients, but it is not known if asymptomatic COVID-19 trauma patients have different outcomes from COVID-19-negative patients. METHODS: All trauma patients admitted to an urban level 1 trauma center between March 2020 and October 2021 were collected and reviewed for COVID-19 status. COVID-19-positive patients with symptoms or initial chest radiographs consistent with infections were excluded. Propensity score model 1:3 matched asymptomatic COVID-19-positive to COVID-19-negative trauma patients for their age, body mass index, MOA, injury severity score, SBP<90, GCS<9, and comorbidities. Outcomes included mortality, complications, and resource utilization. RESULTS: A total of 185 asymptomatic COVID-19-positive patients were matched with 554 COVID-19-negative patients. Asymptomatic COVID-19 -positive patients had higher rates of myocardial infarction and cardiac arrest (3.2% vs. 0.9%, P =0.023), higher ventilator days (3.33 vs. 1.49 days, P <0.001), ICU-length of stay [LOS (4.92 vs. 3.41 d, P =0.034)], overall LOS (11.41 vs. 7.24 d, P <0.001), and hospital charges ($ 176.505.80 vs. 107.591.93, P =0.002). CONCLUSION: Asymptomatic COVID-19 trauma patients have significantly higher rates of cardiac events, longer LOS, and higher hospital charges when compared with similar trauma patients who are COVID-19-negative.

Prevalence of Trimethoprim-Sulfamethoxazole Adverse Reaction Mislabelling in Australia.

INTRODUCTION: Trimethoprim-sulfamethoxazole (TMP-SMX) is an important antibiotic, with the most compelling indications for Pneumocystis jirovecii pneumonia prophylaxis and methicillin-resistant Staphylococcus aureus treatment. Previous adverse reactions (AR) to TMP-SMX may limit the usability of TMP-SMX. Electronic medical record (EMR) of AR for other antibiotics has previously been shown to be inaccurate; however, the extent to which this occurs for TMP-SMX is unknown. METHODS: A multi-centre retrospective observational study was conducted for consecutive inpatient admissions over a 2.5-year period commencing 2020. Adverse reactions to TMP-SMX recorded in the EMR were collected and reviewed by two independent medical officers using pre-defined expert criteria for the classification of allergies and intolerances. RESULTS: TMP-SMX AR were present in the EMR of 759 individuals (prevalence 0.6%). The majority were labelled as allergy (725, 95.5%) rather than intolerance (34, 4.5%). Most common AR were rash, vomiting, and swelling. When classified against the gold-standard expert criteria, there were 437 allergies (57.6%) and 159 intolerances (21.0%). Overall, the number of incorrect EMR AR labels was 133/759 (17.5%). Both medical and surgical specialties had significant numbers of patients with TMP-SMX AR labels and incorrectly classified EMR AR labels. CONCLUSION: TMP-SMX AR labels affect inpatients admitted under multiple specialty units. The user-entered categorization as allergy or intolerance labels in EMRs are frequently used incorrectly. These incorrect labels may inappropriately contraindicate the use of TMP-SMX, and formal evaluation of TMP-SMX ARs with immunological assessment and relabelling where appropriate may increase the use of this agent.

Antibiotic Prescribing Practices Differ between Patients with Penicillin Intolerance and Penicillin Allergy Labels.

INTRODUCTION: Penicillin allergy labels are common. However, many penicillin allergy labels have been applied incorrectly and in fact represent penicillin intolerance. Patients with penicillin intolerance can receive penicillin antibiotics. The effect of penicillin intolerance labels on prescribing practices is uncertain. METHODS: This multicenter retrospective cohort study included consecutive general medicine patients admitted to two tertiary hospitals over a 12-month period. Electronic medical records were reviewed for allergy and prescribing practices. Instances of penicillin prescription to patients with previously labeled penicillin allergies underwent case note review. RESULTS: There were 12,134 individual hospital admissions included in the study. The number of admissions with a previous penicillin allergy label was 1,312 (10.8%) and with a penicillin intolerance label was 60 (0.5%). Penicillin allergy labels were associated with increased likelihood of being prescribed vancomycin (odds ratio 1.42, 95% confidence interval 1.16-1.75, p = 0.001) and moxifloxacin (odds ratio 20.0, 95% confidence interval 13.4-29.9, p < 0.001). Penicillin intolerance was not associated with increased likelihood of receiving these antibiotics. There were 75 admissions during which an individual with a penicillin allergy label was prescribed one of the specified penicillins and only one adverse reaction in this group. These cases included eight deliberate challenges and 15 cases in which allergy history clarification was sufficient to delabel the allergy. CONCLUSIONS: This study supports that prescribing practices differ between patients with penicillin allergy labels and intolerance labels. Penicillin challenges may be undertaken safely in the inpatient setting. Further studies are required to investigate how best to interrogate penicillin allergy labels in this cohort.

Intravenous immunoglobulin alteration in response to adverse reactions in neurological conditions: A retrospective cohort study.

INTRODUCTION: Intravenous immunoglobulin (IVIg) is an important treatment in a range of neurological conditions. There is currently limited evidence regarding the frequency and management of IVIg-associated adverse reactions (AR) in neurological disorders. METHODS: A single-centre 18-month retrospective cohort study was conducted for all patients at a single tertiary hospital receiving IVIg as an inpatient or the medical day unit. Electronic medical record AR and alerts were reviewed for entries relating to IVIg, and prescribing records associated with recent IVIg administration were reviewed for the use of premedications. Case note review was undertaken to identify AR associated with alterations in IVIg treatment (such as reduction in rate, use of premedications or cessation of IVIg). Demographic, patient, and treatment factors were analysed for associations with AR necessitating alteration in IVIg treatment. RESULTS: This study included 98 individuals who received IVIg during the study period. Of these, 12 (12.1%) patients required an alteration in their IVIg treatment. In total, 3 (3.1%) of the 98 included patients required a reduced rate of IVIg, and 10 (10.2%) patients received premedication. The most common premedications were normal saline at the time of the infusion, cetirizine, and hydrocortisone. No demographic factors, indications or comorbidities were found to be associated with an increased likelihood of AR. However, an IVIg daily dose of >35 g and >45 g were associated with an increased likelihood of requiring IVIg treatment alteration due to AR. CONCLUSIONS: Alterations to IVIg treatment due to AR are commonly required in neurology patients, and may be associated with higher daily doses of IVIg.

Artificial intelligence-enabled penicillin allergy delabelling: an implementation study.

Inaccurate penicillin allergy labels may be delabelled following evaluation. The intervention in this study was an email-based notification system regarding the appropriateness for penicillin allergy evaluation, with a view to delabelling, as identified by a deep learning artificial intelligence algorithm. Of the intervention group (n = 59), three (5.1%) individuals had their penicillin allergies delabelled, which was significantly more than the control group (0%, P = 0.002). Further research to optimise such approaches is required.

Evaluating the Ability of Open-Source Artificial Intelligence to Predict Accepting-Journal Impact Factor and Eigenfactor Score Using Academic Article Abstracts: Cross-sectional Machine Learning Analysis.

BACKGROUND: Strategies to improve the selection of appropriate target journals may reduce delays in disseminating research results. Machine learning is increasingly used in content-based recommender algorithms to guide journal submissions for academic articles. OBJECTIVE: We sought to evaluate the performance of open-source artificial intelligence to predict the impact factor or Eigenfactor score tertile using academic article abstracts. METHODS: PubMed-indexed articles published between 2016 and 2021 were identified with the Medical Subject Headings (MeSH) terms "ophthalmology," "radiology," and "neurology." Journals, titles, abstracts, author lists, and MeSH terms were collected. Journal impact factor and Eigenfactor scores were sourced from the 2020 Clarivate Journal Citation Report. The journals included in the study were allocated percentile ranks based on impact factor and Eigenfactor scores, compared with other journals that released publications in the same year. All abstracts were preprocessed, which included the removal of the abstract structure, and combined with titles, authors, and MeSH terms as a single input. The input data underwent preprocessing with the inbuilt ktrain Bidirectional Encoder Representations from Transformers (BERT) preprocessing library before analysis with BERT. Before use for logistic regression and XGBoost models, the input data underwent punctuation removal, negation detection, stemming, and conversion into a term frequency-inverse document frequency array. Following this preprocessing, data were randomly split into training and testing data sets with a 3:1 train:test ratio. Models were developed to predict whether a given article would be published in a first, second, or third tertile journal (0-33rd centile, 34th-66th centile, or 67th-100th centile), as ranked either by impact factor or Eigenfactor score. BERT, XGBoost, and logistic regression models were developed on the training data set before evaluation on the hold-out test data set. The primary outcome was overall classification accuracy for the best-performing model in the prediction of accepting journal impact factor tertile. RESULTS: There were 10,813 articles from 382 unique journals. The median impact factor and Eigenfactor score were 2.117 (IQR 1.102-2.622) and 0.00247 (IQR 0.00105-0.03), respectively. The BERT model achieved the highest impact factor tertile classification accuracy of 75.0%, followed by an accuracy of 71.6% for XGBoost and 65.4% for logistic regression. Similarly, BERT achieved the highest Eigenfactor score tertile classification accuracy of 73.6%, followed by an accuracy of 71.8% for XGBoost and 65.3% for logistic regression. CONCLUSIONS: Open-source artificial intelligence can predict the impact factor and Eigenfactor score of accepting peer-reviewed journals. Further studies are required to examine the effect on publication success and the time-to-publication of such recommender systems.

Artificial intelligence and the potential for perioperative delabeling of penicillin allergies for neurosurgery inpatients.

PURPOSE OF THE ARTICLE: Patients with penicillin allergy labels are more likely to have postoperative wound infections. When penicillin allergy labels are interrogated, a significant number of individuals do not have penicillin allergies and may be delabeled. This study was conducted to gain preliminary evidence into the potential role of artificial intelligence in assisting with perioperative penicillin adverse reaction (AR) evaluation. MATERIAL AND METHODS: A single-centre retrospective cohort study of consecutive emergency and elective neurosurgery admissions was conducted over a two-year period. Previously derived artificial intelligence algorithms for the classification of penicillin AR were applied to the data. RESULTS: There were 2063 individual admissions included in the study. The number of individuals with penicillin allergy labels was 124; one patient had a penicillin intolerance label. Of these labels, 22.4% were not consistent with classifications using expert criteria. When the artificial intelligence algorithm was applied to the cohort, the algorithm maintained a high level of classification performance (classification accuracy 98.1% for allergy versus intolerance classification). CONCLUSIONS: Penicillin allergy labels are common among neurosurgery inpatients. Artificial intelligence can accurately classify penicillin AR in this cohort, and may assist in identifying patients suitable for delabeling.

Professionalism and clinical short answer question marking with machine learning.

Machine learning may assist in medical student evaluation. This study involved scoring short answer questions administered at three centres. Bidirectional encoder representations from transformers were particularly effective for professionalism question scoring (accuracy ranging from 41.6% to 92.5%). In the scoring of 3-mark professionalism questions, as compared with clinical questions, machine learning had a lower classification accuracy (P < 0.05). The role of machine learning in medical professionalism evaluation warrants further investigation.

Neurosurgery inpatient outcome prediction for discharge planning with deep learning and transfer learning.

INTRODUCTION: Deep learning may be able to assist with the prediction of neurosurgical inpatient outcomes. The aims of this study were to investigate deep learning and transfer learning in the prediction of several inpatient outcomes including timing of discharge and discharge destination. METHOD: Data were collected on consecutive neurosurgical admissions from existing databases over a 15-month period. Following pre-processing artificial neural networks were applied to admission notes and ward round notes to predict four inpatient outcomes. Models were developed on the training dataset, before being tested on a hold-out test dataset and a validation dataset. RESULTS: 1341 individual admissions were included in the study. Using transfer learning and an artificial neural network an area under the receiver operator curve (AUC) of 0.81 and 0.80 on the derivation and validation datasets was able to be achieved for the prediction of discharge within the next 48 hours using daily ward round notes. This result is in comparison to an AUC of 0.71 and 0.68 using an artificial neural network without transfer learning for the same outcome. When the artificial neural network with transfer learning was applied to the other outcomes AUC of 0.72, 0.93 and 0.83 was achieved on the validation datasets for predicting discharge within the next 7 days, survival to discharge and discharge to home as a destination. CONCLUSIONS: Deep learning may predict inpatient neurosurgery outcomes from free-text medical data. Recurrent predictions with ward round notes enable the use of information obtained throughout hospital admissions in these estimates.

Surviving Nonsurvivable Injuries: Patients Who Elude the 'Lethal' Abbreviated Injury Scale Score of Six.

BACKGROUND: The Abbreviated Injury Scale (AIS) score is used widely to quantify injury severity by body region. The maximal AIS score is 6, which defines a nonsurvivable injury. This study was undertaken to define mortality after AIS-6 injuries in order to determine if they are uniformly lethal and, if not, if differences between survivors and nonsurvivors exist which may aid in prognostication or refinement of the current AIS system. METHODS: All patients in the National Trauma Data Bank (2007-2017) with ≥1 AIS-6 injury were included. Exclusions were age <16 years, AIS-6 coding in the face/extremities (i.e., coding errors, as there are no AIS-6 injuries in these regions), and missing data. In-hospital mortality defined study groups, i.e., survivors vs. nonsurvivors. Univariable analysis compared clinical/injury data and outcomes. Multivariable analysis examined independent factors associated with mortality. RESULTS: 19,247 patients met inclusion/exclusion criteria. Of these, 25% (n=4,886) survived to hospital discharge and 75% (n=14,361) died. The most common discharge destination among survivors was home (n=2,187,45%) Nonsurvivors had significantly worse GCS in the field (3 vs. 14, p<0.001) and ED (3 vs. 15, p<0.001). Median AIS was higher among nonsurvivors in the Head (5 vs. 3, p<0.001), Abdomen (3 vs. 2, p<0.001), and External regions (1 vs. 1, p<0.001). Median time to death was 0.65h, with maximum time to death 8.76h. Multivariable analysis revealed External AIS-6 injuries were associated with greatest odds of mortality (OR 34.002, p<0.001) followed by Head AIS-6 (OR 10.501, p<0.001). CONCLUSION: AIS-6 injuries are not uniformly fatal, with 25% of such patients surviving to hospital discharge. Therefore, AIS-6 injuries may not be as catastrophic as previously considered. External and Head AIS-6, i.e. extensive burns and severe traumatic brain injuries, were associated with greatest odds of mortality. When death occurs after AIS-6 injury, it occurs rapidly, with all mortalities in this series occurring <9h after arrival. We suggest that the AIS-6 verbiage be revised to remove 'nonsurvivable'.

Selective Nonoperative Management of Abdominal Shotgun Wounds.

BACKGROUND: Selective nonoperative management (SNOM) of abdominal gunshot wounds (GSWs) has not been specifically examined after shotgun injuries. Because of the unpredictable nature of shotgun pellets, it is unclear if SNOM after shotgun wounds is safe. The study objective was to examine outcomes after SNOM for shotgun wounds to the abdomen. METHODS: Patients with isolated abdominal shotgun wounds were identified from the National Trauma Data Bank (2007-2017). Transfers, arrival without signs of life, death in the emergency department, severe (Abbreviated Injury Scale ≥3) extra-abdominal injuries, abdominal Abbreviated Injury Scale = 6, and missing data were exclusion criteria. Patients with abdominal handgun wounds (GSWs) were used for comparison. Study groups of shotgun-injured patients were defined by management strategy: operative management (OM) (exploratory laparotomy ≤4h) versus SNOM (no exploratory laparotomy ≤4h). Outcomes were compared by mechanism of injury (shotgun versus GSW) and management strategy (OM versus SNOM) using univariate and multivariate analyses. RESULTS: After exclusions, 1425 patients injured by abdominal shotgun wounds were included. Shotgun-injured patients underwent SNOM more frequently than GSW patients (42% versus 34%, P < 0.001). On multivariate analysis, injury by shotgun was independently associated with SNOM (OR 1.443, P = 0.040). Shotgun injuries were significantly more likely to fail SNOM (OR 2.401, P = 0.018). Failure of SNOM occurred earlier among shotgun-than GSW-injured patients (15 versus 24h, P = 0.011). SNOM after shotgun injury was associated with lower mortality than OM, even when patients failed SNOM (P < 0.001). Complications were uniformly higher after OM than SNOM, even when SNOM failed (P < 0.05). CONCLUSIONS: SNOM was utilized more commonly after shotgun wounds than GSWs. However, SNOM was more likely to fail after shotgun injury and tended to occur earlier after admission. SNOM after shotgun injury was associated with improved mortality and decreased complication rates when compared with OM, even when patients failed SNOM. SNOM appears to be a safe and beneficial management strategy after shotgun wounds to the abdomen.

Intra-Abdominal Hemorrhage Control: The Need for Routine Four-Quadrant Packing Explored.

BACKGROUND: Routine four-quadrant packing (4QP) for hemorrhage control immediately upon opening is a standard practice for acute trauma laparotomy. The aim of this study was to evaluate the utility of 4QP for bleeding control in acutely injured patients undergoing trauma laparotomy. METHODS: Retrospective single-center study (01/2015-07/2019), including adult patients who underwent trauma laparotomy within 4 h of admission. Only patients with active intra-abdominal hemorrhage, defined as bleeding within the peritoneal cavity or expanding retroperitoneal hematoma, were considered for analysis. Bleeding sources were categorized anatomically: liver/retrohepatic inferior vena cava (RIVC), spleen, retroperitoneal zones 1, 2 and 3, mesentery and others. Hemorrhage was further categorized as originating from a single bleeding site (SBS) or from multiple bleeding sites (MBS). The effectiveness of directed versus 4QP was evaluated for bleeding from the liver/RIVC, spleen and retroperitoneal zone 3, areas that are potentially compressible. Directed packing was defined as indicated if the bleeding was restricted to one of the anatomic sites suitable for packing, 4QP was defined as indicated if ≥ 2 of the anatomic sites suitable for packing were bleeding. RESULTS: During the study time frame, 924 patients underwent trauma laparotomy, of which 148 (16%) had active intra-abdominal hemorrhage. Of these, 47% had a SBS and 53% had MBS. The liver/RIVC was the most common bleeding source in both patients with SBS (42%) and in patients with MBS (54%). According to our predefined indications, 22 of 148 patients (15%) would have benefitted from initial 4QP, 90 of 148 patients (61%) from directed packing and 36 of 148 patients (24%) packing would not have been of any value. CONCLUSION: Routine four-quadrant packing is frequently practiced. However, this is only required in a small proportion of patients undergoing trauma laparotomy. Directed packing can be equally effective, saves time and decreases the risk of iatrogenic injury from unnecessary packing.

Practical assessment of different saw types for field amputation: A cadaver-based study.

INTRODUCTION: Field amputation can be life-saving for entrapped patients requiring surgical extrication. Under these austere conditions, the procedure must be performed as rapidly as possible with limited equipment, often in a confined space, while minimizing provider risk. The aim of this study was to determine the ideal saw, and optimal approach, through bone or joint, for a field amputation. METHODS: This was a prospective cadaver-based study. Four saws (Gigli, manual pruning, electric oscillating and electric reciprocating) were tested in human cadavers. Each saw was used to transect four separate long bones (humerus, ulna/radius, femur and tibia/fibula), previously exposed at a standardized location. The time required for each saw to cut through the bone, the number of attempts required to seat the saw when transecting the bone, slippage, quality of proximal bone cut and extent of body fluid splatter as well as the physical space required by each device during the amputation were recorded. Additionally, the most effective saw in the through bone assessment was compared to limb amputation using scalpel and scissors for a through joint amputation at the elbow, wrist, knee and ankle. Univariate analysis was used to compare the outcomes between the different saws. RESULTS: The fastest saw for the through bone amputation was the reciprocating followed by oscillating (2.1 [1.4-3.7] seconds vs 3.0 [1.6-4.9] seconds). The manual pruning (58.8 [25-121] seconds) was the slowest (p = 0.007). Overall, the oscillating saw was superior or equivalent to the other devices in number of attempts (1), slippage (0), quality of bone cut (100% good) and physical space requirements (4500 cm3), and was the second fastest. In comparison, a through joint amputation (125.0 [50-147] seconds for scalpel and scissor; 125.5 [86-217] seconds for the oscillating saw) was significantly slower than through bone with the Gigli (p = 0.029), the oscillating (p = 0.029) and the reciprocal saw (p = 0.029). CONCLUSIONS: The speed, precision, safety, space required, as well as the adjustable blade of the oscillating saw make it ideal for a field amputation. A Gigli saw is an excellent backup for when electrical tools cannot be used. Through bone amputation is faster than a through joint amputation.

Contemporary Trends and Outcomes of Blunt Traumatic Colon Injuries Requiring Resection.

BACKGROUND: After traumatic injury, primary anastomosis after colon resection has overtaken ostomy diversion. Improved technology facilitating primary anastomosis speed and integrity may have driven this change. Trends in ostomy versus anastomosis have yet to be quantified, and recent literature comparing outcomes is incomplete. METHODS: The National Trauma Databank (2007-2014) was queried for all blunt colon injuries requiring resection. Patients were dichotomized into study groups based on whether they underwent ostomy creation. Ostomy creation frequency was compared over time. After subgrouping patients by colon injury location, multivariate regression adjusted for baseline characteristics and evaluated the impact of ostomy on clinical outcomes. RESULTS: A total of 13,949 colon injuries requiring colectomy were identified. Ostomy frequency did not vary by study year (P = 0.536). Univariate analysis showed that patients undergoing ostomy were older (median, 40 versus 32; P < 0.001) and more often had comorbidities (65% versus 56%; P < 0.001). Multivariate analysis showed that ostomy creation was significantly associated with lower mortality after sigmoid colon injury (odds ratio, 0.512; P = 0.011) and higher rates of unplanned reoperation after transverse colon injury (odds ratio, 3.135; P = 0.048). Across all colon injuries, ostomies were significantly associated with longer hospital length of stay, intensive care unit length of stay, and ventilator days. CONCLUSIONS: Ostomy creation for colonic injury has reached an equilibrium trough. The impact of ostomy creation varies by not only clinical outcome but also injury location. Further study is needed to define the optimal surgical management for blunt colon injuries requiring resection.

Transfusion-Related Hypocalcemia After Trauma.

BACKGROUND: Hypocalcemia is cited as a complication of massive transfusion. However, this is not well studied as a primary outcome in trauma patients. Our primary outcome was to determine if transfusion of packed red blood cells (pRBC) was an independent predictor of severe hypocalcemia (ionized calcium ≤ 3.6 mg/dL). METHODS: Retrospective, single-center study (01/2004-12/2014) including all trauma patients ≥ 18 yo presenting to the ED with an ionized calcium (iCa) level drawn. Variables extracted included demographics, interventions, outcomes, and iCa. Regression models identified independent risk factors for severe hypocalcemia (SH). RESULTS: Seven thousand four hundred and thirty-one included subjects, 716 (9.8%) developed SH within 48 h of admission. Median age: 39 (Range: 18-102), systolic blood pressure: 131 (IQR: 114-150), median Glasgow Coma Scale (GCS): 15 (IQR: 10-15), Injury Severity Score (ISS): 14 (IQR: 9-24). SH patients were more likely to have depressed GCS (13 vs 15, p < 0.0001), hypotension (23.2% vs 5.1%, p < 0.0001) and tachycardia (57.0% vs 41.9%, p < 0.0001) compared to non-SH patients. They also had higher emergency operative rate (71.8% vs 29%, p < 0.0001) and higher blood administration prior to minimum iCa [pRBC: (8 vs 0, p < 0.0001), FFP: (4 vs 0, p < 0.0001), platelet: (1 vs 0, p < 0.0001)]. Multivariable analysis revealed penetrating mechanism (AOR: 1.706), increased ISS (AOR: 1.029), and higher pRBC (AOR: 1.343) or FFP administered (AOR: 1.097) were independent predictors of SH. SH was an independent predictor of mortality (AOR: 2.658). Regression analysis identified a significantly higher risk of SH at pRBC + FFP administration of 4 units (AOR: 18.706, AUC:. 897 (0.884-0.909). CONCLUSION: Transfusion of pRBC is an independent predictor of SH and is associated with increased mortality. The predicted probability of SH increases as pRBC + FFP administration increases.