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Introduction This paper aims to provide an overview of the administrative and clinical preparations done in a tertiary care cancer hospital in continuing operation theatre (OT) services through the COVID pandemic.Methods Retrospective data collection, data for the past 1.5 years (COVID period) March 2020 to August 2021 were compared to surgical output for a similar duration of time before the COVID era (September 2018-February 2020).Results A total of 1,022 surgeries were done under anesthesia in the COVID period as against 1,710 surgeries done in a similar time frame in the pre-COVID era. Overall, we saw a 40%drop in the total number of cases. Thorax, abdominal, and miscellaneous surgeries (soft tissue sarcomas, urology, and gyneconcology) saw a maximum fall in numbers;however, head and neck cases saw an increase in numbers during the pandemic. Surgical morbidity and mortality were similar in the COVID and pre-COVID era. No cases of severe COVID infection were reported among the healthcare staff working in OT.Discussion We could successfully continue our anesthesia services with minimal risk to healthcare staff throughout the pandemic by adopting major guidelines in a pragmatic and practical approach with minor changes to suit our setup.
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Aims: NHSE/I and The RCS England have advocated that The separation of elective and surgical care is fundamental in recovering surgical services. It is suggested that The separation is physical and many Trusts are transforming pathways into elective and emergency hospitals. Croydon Hospital (CHS) have created an alternative, with 'a Hospital within a Hospital', separating these pathways within one estate, and considers whether this is a successful model for The future. Method(s): The day surgery unit On The ground floor was converted into an emergency centre with an ambulatory surgical hub, a hot clinic, clinical space, 4 emergency theatres and an USS room. The main theatre suite was converted into The Croydon Elective Centre (CEC) with a 12-bedded coronary catheter suite, a lift onto The second floor, 10 theatres, a 12 bedded children's day unit, Moorfields' eye unit, a new canteen, an admissions unit as well as a 28-bedded elective ward with a new 4-bedded level 1.5 critical care unit. Result(s): At The end of wave 1, 3,068 patients awaited treatment, an increase of 30.44% of baseline activity with theatre activity at 28% of normal activity. Activity resumed to 100% within 6 weeks of CEC go live. 2/9,606 patients were Covid-19 positive in The first year. During wave 2, 60% of pre-Covid-19 activity continued. Currently, 2,098 patients await treatment. Conclusion(s): The implementation of a surgical hub has supported The treatment of patients as well as provided continuous training opportunities for surgical and anaesthetic trainees as well as The theatre team.
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Introduction: We are faced with long waiting lists coupled with a loss of training opportunities for surgical trainees as a result of CoVID-19. It is imperative to ensure training opportunities are optimised and trainees are encouraged to contribute to The service recovery efforts we are faced with. Method(s): A pilot 'The hernia fest' was undertaken with The aim of training core trainees, supporting senior trainees as independent practitioners coupled with supporting The delivery of high volume, low complexity (HVLC) care. Parallel bespoke theatre lists with The grouping of specific cases (hernias), have been run with a consultant surgeon overseeing 2-3 lists. Each list includes a selected senior trainee who is suitable to train colleagues. Cases were screened prior to booking. All theatre staff were briefed On The purpose of The lists. All patients, trainees and theatre staff completed a questionnaire. Result(s): 50 hernia training cases were carried out over 15 sessions. 100% of patients were confident with their treatment and would recommend The service. 100% of trainees felt they had progressed in their operative competence and skill acquisition. 100%oftrainees were satisfied. Senior trainees enjoyed The responsibility of running an independent list. 100% of theatre staff felt they would participate in future lists. Conclusion(s): This model cultivates a learning environment whilst addressing waiting lists. The grouping of operations together allows for repetitive practice and may encourage rapid skill acquisition. We discuss lessons learnt and a proposed framework & checklist which can be applied to The future planning of such lists.
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Background: Cancer patients are at increased risk of infection due to immunosuppression, poor nutrition, and other health problems. Various studies have shown that cancer patients have a higher risk of serious complications related to Coronavirus disease (COVID-19) than patients without cancer, however, the strength of associated varied significantly across the studies. We aim to analyze the differences in the clinical characteristics, laboratory parameters, and hospital outcomes of COVID-19 among patients with and without cancer. Method(s): This was a retrospective study of 1873 patients including 102 cancer patients who presented with SARS-CoV-2 infection at our hospital. Our primary outcome was the in-hospital mortality rate due to COVID-19 and the secondary outcome was a comparison of demographic, clinical, laboratory, and treatment parameters of cancer patients compared to non-cancer patients. Multivariate logistic regression models were fitted to identify factors predictive of disease progression in the hospital, including death. Result(s): Cancer patients had a higher in-hospital mortality rate than non-cancer patients (26.5 vs 21.2 %, P=0.211). The proportion of people with anemia, thrombocytopenia, and leukopenia was significantly higher in the cancer group. The median value of inflammatory markers (ferritin, D-dimer, and IL-6) in the cancer group is approximately two times than non-cancer group. The odds of worsening [1.73 (1.01-2.95)] and death [2.83 (1.46-5.47)] during hospital stay were significantly higher in cancer patients. Hematological malignancies had higher odds of developing critical illness [4.96 (1.57-15.7)] and receiving mechanical ventilation [4.35 (1.27-15.0)] compared to non-cancer cases. In cancer patients, breathlessness and hypoxia at presentation were significant predictors of mortality when adjusted for other clinical features. Conclusion(s): Cancer patients with COVID-19 infection have abnormally high inflammatory responses compared with non-cancer patients and the development of breathlessness and hypoxia are important predictors of mortality. Patients with hematological malignancies have a higher risk of developing serious disease. Legal entity responsible for the study: The authors. Funding(s): Has not received any funding. Disclosure: All authors have declared no conflicts of interest. Copyright © 2022
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Introduction: COVID-19 pandemic has placed the health systemworldwide in unprecedented stress, therefore, prompt identification and management of patients having severe disease is essential fortriaging of patients at the time of admission.Aims &Objectives: To identify hematological biomarkers ofCOVID-19 disease severity in patients admitted in a tertiary carehospital.Materials &Methods: A retrospective study was conducted over aperiod of 17 months (20th March 2020-19 August 2021) on 7416COVID-19 patients. Patients with cancers, pregnancy and chronichematological diseases were excluded from the study. Patients wereclassified clinically as per severity of disease as non-severe (asymptomatic, mild, moderate) or severe and their hematological parameterswere analyzed.Mann-Whitney test was used to compare between the groups. Optimal predictive cut off points for the variables were defined by receiveroperating characteristic (AUC) curve to dichotomize the variables.Univariate analysis was performed to screen out independent variables to be used in the binary logistic regression (BLR). A p valueof< = 0.05 was considered as statistically significant.Result: Age, duration of hospital stay, RBC count, WBC, Plateletcount, RDW, Neutrophils %, Absolute neutrophil count (ANC),Absolute monocyte count (AMC), NLR, PLR, NMR were statisticallyhigher whereas hemoglobin, hematocrit, MCHC, lymphocyte %,Absolute lymphocyte count (ALC), Eosinophils %, Absolute eosinophil count (AEC), Monocytes %, Basophils %, Absolute Basophilcount (ABC) and Lymphocyte Monocyte ratio (LMR) were lower insevere group. MCV and MCHC were not significant, so wereexcluded from the logistic regression model. All variables were significant in univariate analysis. Age (>42 yrs), duration of hospitalstay (>10 days), RBC count (B 4.33 106/lL),WBC count (> 7.73103/lL), RDW (>14.8%), Neutrophils (>71.7%), Eosinophils(B 0.3%), Monocytes (B 5%), ALC (B 1.01 103/lL), LMR(B 3.125) with adjusted odd ratio of 1.8, 1.5, 1.3,1.3, 1.4, 2.0, 2.1, 1.5,2.0 and 1.3 respectively were found to be significant predictors ofseverity.Conclusions: Age, duration of hospital stay, RBC count, WBC,RDW, Neutrophils %, Eosinophils %, Monocytes %, ALC, LMRshould be assessed and monitor at the earliest to halt unfavorableoutcome of mortality or morbidity.
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Aim: COVID had an unprecedented effect on the NHS elective surgical care. To overcome the deficit created due to the pandemic, the concept of a 'COVID protected zone' gave birth to the 'hospital within the hospital'. This included 9 elective theatres, 28 ring fenced elective beds, a surgical enhanced care unit, a canteen and a separated entrance. Of the fundamentals of the model were enhanced infection control and PPE guidance for staff. The aim of our study was to evaluate the recovery of elective activity brought about by this elective centre. Methods: Theatre activity data was collected weekly (7/20 to 1/21) through the business informatics system. This was used to compare the activity achieved during the recovery phase from COVID after the first and subsequent wave. Results: Pre COVID-19, 11 theatres were operating. These managed an average of 263 cases were per week. In the first week of operation of elective centre, 31% of theatre capacity was achieved. By week 7, 106% of pre COVID was recorded and 130% by week 11. During the 2nd wave the capacity was reduced to 42% as opposed to 0% during the first wave. This was only possible due to our model elective centre. Conclusion: This model elective centre has enabled elective care to return to above normal levels, with increased efficiencies. This has not only shortened patient waiting times and cleared the back-log but also delivered training to surgical trainees without compromising safety.
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Background: Intubation is a highly aerosol generating procedure. Recent airway management guidelines advocate the use of appropriate personal protective equipment, a video laryngoscope and 'intubation box' while intubating a suspected or an infected COVID patient.1 We undertook a study to compare CMAC Videolaryngoscope with Mc Grath Videolaryngoscope for tracheal intubation using an intubation box along with PPE. Methods: The patients were randomly allocated to two groups by computer-generated random numbers, depending upon the Video laryngoscope used: Group C (n=30) where C-MAC VL was used and Group M (n=30) where Mc Grath VL was used. The primary outcome was total time required for successful intubation. The secondary outcomes included number of attempts required, CL grade, POGO score, difficulty faced while using the device and user's preference. Results: The time to intubation was 57.17± 19.98 seconds with C-MAC laryngoscope as compared to 57.93 ± 14.92 seconds with McGrath laryngoscope (p=0.134). The POGO score and CL grade were comparable. Both the devices had a good POGO score. Twelve patients in each group were found to have a CL grade of 1. The time to glottis visualization was more with Mc Grath than with C-MAC although not significant (23.8±14.03 vs 20.10±10.78). Both the devices were easy to use. Conclusions: Both C-MAC and McGrath video laryngoscopes, are equally effective devices for intubation by a donned anaesthesiologist using an intubation box but McGrath with a disposable blade is better suited in these conditions.
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Aims & Objectives: The present study was undertaken to evaluate prognostic relevance of hematological parameters in COVID-19 infected patients for early identification of critical patients for early management. Patients/Materials & Methods: A retrospective study was conducted over a period of 2 months (01st July 2020 to 1st September 2020) on 912 admitted COVID-19 positive patients. 2 ml venous blood was aseptically collected in EDTA vaccutainer and processed in automated hematology analyser (ADVIA 2120i). Patients with hematological malignancy were excluded from the study. Patients were assigned into three groups according to the severity of disease (mild/asymptomatic, moderate and severe) as well as on the basis of clinical outcome (discharged ordeath). Results: To talleucocyte count, absolute neutrophil count, neutrophillymphocyte ratio, plateletlymphocyte ratio, reddistribution width were significantly higher (p<0.05) is the decreased patients and in severe disease group where as hemoglobin and hematocr it was significant lower in these patients. Lymphopenia was recorded in decreased patient but was not statically significant. Discussion & Conclusion: COVID-19 patients with severe disease and poor outcome showed significant difference in ther outine hematological parameter such as total leucocyte count, absolute neutrophil count, absolute monocyte count, neutrophillymphocyte ratio, plateletlymphocyte ratio, reddistribution width and hematocrit which are readily available and can be helpful in the prediction of COVID-19 patien toutcome.