The taxonomy of Kaposi Sarcoma (KS) is based on a classification system focused on the description of clinicopathological features of KS in geographically and clinically diverse populations. The classification includes classic, endemic, epidemic/HIV associated and iatrogenic KS, and KS in men who have sex with men (MSM). We assessed the medical relevance of the current classification of KS and sought clinically useful improvements in KS taxonomy.We reviewed the demographic and clinicopathological features of 676 patients with KS, who were referred to the national centre for HIV oncology at Chelsea Westminster hospital between 2000 and 2021.2 P = 0.0012*) and disseminated skin involvement (chi2 P < 0.0001*). Immunosuppressed patients had lower CD4 counts, higher CD8 counts and a trend towards higher HHV8 levels compared to non-immunosuppressed patients, however overall survival and disease specific (KS) survival was similar across groups.Demographic differences between the different subtypes of KS exist as tautological findings of the current classification system. However, no definitive differences in clinicopathological, virological or immunological parameters at presentation could be demonstrated between the classic, endemic or MSM KS patients. Reclassifying patients as either immunosuppressed or non-immunosuppressed, showed that the immunosuppressed group had a significantly higher proportion of adverse disease features at presentation including visceral disease and extensive oral involvement, classified together as advanced disease (chiThe current system of KS classification does not reflect meaningful differences in clinicopathological presentation or disease pathogenesis. Reclassification of patients based on the presence or absence of immunosuppression is a more clinically meaningful system that may influence therapeutic approaches to KS.The online version contains supplementary material available at 10.1186/s12967-023-04130-6. The current categorisation of disease is largely based upon histopathology and clinical manifestations and includes several widely employed classifications such as: International Statistical Classification of Diseases and Related Health Problems ICD9/10), Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), Unified Medical Language System (UMLS) and Medical Subject Headings (MeSH). These systems are based on the cataloguing of disease in the nineteenth century that originated with the biostatistician William Farr who grouped together “zymotic” or infectious diseases. The underlying principle behind these schemes was to assist in the diagnosis of diseases and perhaps help the choice of treatment. In recent times, the advances in molecular basis of disease and the associated identification of therapeutic targets for precision medicine has led to calls for a new taxonomy of disease 0, System.Kaposi Sarcoma (KS) is renowned in the medical and wider community as an acquired immune deficiency syndrome (AIDS) defining malignancy, causing highly visible pigmented cutaneous lesions. Those affected were highly stigmatised in the 1980s and early 1990s before the introduction of effective antiretroviral therapy. However, within the specialist medical community KS was already well known, having first been reported in 1872 by Moritz Kaposi . He descThe variety of KS that Kaposi described became known as ‘Classic’ or sporadic KS and occurs mostly in elderly and middle-aged men of Eastern European, Middle Eastern or Mediterranean origin. It typically presents as pigmented plaques or nodules on the lower limbs and frequently runs an indolent cause . In the The higher rate of KS in HIV infected MSM, as compared to other HIV infected populations, such as haemophiliacs , and theAs the causative agent of KS, HHV8 infection is necessary to develop KS, although only a small proportion of those infected will develop KS. In addition to HHV8 infection a degree of impaired host immunity is required. This is clearly identified in HIV associated- and iatrogenic-KS, but is less well defined in the other KS variants. Theories include immunosenescence with ageing for classic KS and a combination of chronic infection and or malnutrition in endemic KS , 15.The initial HHV8 infection is believed to be largely asymptomatic but similar to other herpesviruses infection is lifelong with latent and lytic phases of infection , 17. KS Given that HHV8 is required to cause KS, it is clear that the KS variants described do not have a unique pathology i.e. they are still all caused by HHV8; but rather exist on a clinico-pathological continuum caused by unique population characteristics of HHV8 prevalence, age of infection, population health and presence or absence of immune suppression. In addition, there is little evidence of significant biological differences between some of these groups in terms of clinical manifestations or histopathological features, and in many cases the therapeutic approaches are similar. We hypothesise that the most significant difference may be between KS in the immunocompetent versus KS in the immunodeficient host. To assess the medical relevance of the current classification of KS, we evaluated demographic, clinicopathological features, virological and immunological parameters at presentation, as well as overall and disease specific survival in a dataset including 676 patients all with biopsy proven KS.At the National Centre for HIV malignancies at the Chelsea and Westminster Hospital we prospectively collected routine data on all individuals who attend. All 676 patients diagnosed with biopsy proven Kaposi sarcoma between the years 2000 and 2021 were included in the study. Data collection was approved by the national centre for HIV malignancy. Anonymised data on patient characteristics including biological variables was extracted from the database. The date from KS diagnosis until death, study censoring or loss to follow-up was used to calculate overall survival.2 test, or Fishers exact test , and for non-parametric continuous variables the Mann–Whitney (MW) (2 comparisons) / Kruskal–Wallis (KW) test (> 2 comparisons) were used; all P-values were two-sided. The Bonferroni correction method was used to reduce the type 1 error rate due to multiple comparisons; using the standard level of significance for a single test of P ≤ 0.05, a corrected P value of ≤ 0.0013 was required for significance (39 comparisons). Significant P-values are marked with an asterisk*. Survival was calculated from KS diagnosis until death  or last follow-up. Survival curves were plotted according to the method of Kaplan and Meier [Comparison of variables between the groups for categorical data was by chind Meier . The lognd Meier . AnalysiThe 676 patients were assigned at presentation into the five groups according to Cesarman, Damania . The larThere were a number of tautological findings based on the classification system, including that the MSM group were exclusively cis-male, that the classic KS patients were older and that the endemic KS patient were more likely to be Black Table . There wHHV8 bloods levels were highest in HIV associated KS followed by iatrogenic KS, and lowest in MSM KS Table , Fig. 2AKS was the cause of death in 17 patients, representing 25.4% of deaths. Immunosuppression related deaths (16 deaths), and AIDS defining HIV associated malignancy deaths (16 deaths) were also common Table A. Overal2 P = 0.55), gastrointestinal (4 vs 11% chi2 P = 0.36), and other visceral disease involvement (9 vs 21% chi2 P = 0.24) and no oral involvement. There were non-significant differences in levels of tumour associated oedema (26 vs 42% chi2 P = 0.27) and tumour ulceration (17 vs 21% chi2 p = 0.76), and no difference in presenting histology (chi2 p = 0.09). In addition there was no difference in the proportion of patients with positive plasma HHV8 DNA (chi2 P = 0.71), absolute plasma HHV8 DNA levels (MW P = 0.60) or Log HHV8 levels (MW P = 0.81), and no difference in leukocyte count (MW P = 0.79), lymphocyte count (MW P = 0.91), CD4 count (MW P = 0.39), CD4% (MW P = 0.95), CD8 count (MW P = 0.51) or CD8% (MW P = 0.95) at diagnosis  or mean levels (KW P = 0.128) or mean Log HHV8 (KW P = 0.660), and no significant difference in leukocyte, lymphocyte, CD4 or CD8 levels at diagnosis  versus non-immunosuppressed  would be a clinically suitable classification system.2 P < 0.0001*) (Table 2 P < 0.0001*) and extensive oral mucosal involvement (chi2 P < 0.0001*) was more common in the immunosuppressed (Table 2 P = 0.07), gastrointestinal involvement (chi2 P = 0.09) and other visceral involvement (chi2 P = 0.08) but none reached the level of significance. Defining advanced disease as the presence of visceral disease or extensive oral involvement, showed that immunosuppressed patients were significantly more likely to have advanced disease (26% vs 8% chi2 = 0.0012*) compared to non-immunosuppressed patients. The immunosuppressed group had a lower leukocyte count but similar lymphocypte count, lower CD4 count (MW P < 0.001*) and CD4% (MW P < 0.001*), and higher CD8 counts (MW P < 0.001*) and CD8% (MW P < 0.001*) , whereas the non-immunosuppressed group had more Black people (chi*) Table . KS rela*) Table . Skin KSed Table A and B. *) Table C. Overal*) Table B. The maExploratory analysis was completed on the duration of immunosuppression. Duration of immunosuppression was defined as the time from HIV diagnosis to KS diagnosis in HIV associated KS and the time from start of iatrogenic immunosuppression to KS in the iatrogenic group. Those in whom HIV and KS diagnosis was simultaneous were excluded because the period of immunosuppression could not be defined for these patients. Data was available for 406/593 patients with a median of 45.4 months of immunosuppression (range 1–444 months).Data was available for 392/597 HIV associated KS patients. Median time from HIV to KS diagnosis was 30 months (range 1–184 months) for those with advanced KS involvement at diagnosis  and 51.7 months for patients without advanced KS involvement (range 1–444 months) (P < 0.0001* MW). Data on duration of iatrogenic immunosuppression was available for 14/21 patients. Those with advanced iatrogenic KS involvement had longer periods of immunosuppression (35.9 months versus 63.3), however the difference was not significant (P = 0.11).Multicentric Castleman’s disease (MCD) which is also HHV8 associated, was recorded as a concomitant diagnosis in 32 patients with HIV associated KS. Median viral load was significantly higher at KS diagnosis 506,500 copies/ml (range 0-554 M) in patients with concomitant or prior MCD versus a median of 0 copies/ml (range 0-49 M) in patients without MCD (P < 0.0001* MW). Two other patients had MCD as a concomitant diagnosis, one with iatrogenic KS  and one with classic KS , indicating that MCD occurred almost exclusively in the immunosuppressed cohort.The taxonomy of KS is based on a current classification system focused on the demographics and description of KS clinicopathological features in separate populations affected by KS. This system developed as KS was found to involve each group sequentially; from classic KS (1870s), to endemic KS 1940s), iatrogenic KS (1960s), HIV associated KS (1980s) and MSM KS (2010s) 0s, iatro. These dIn this review of 676 consecutive patients with KS who attended the UK national HIV oncology centre at Chelsea and Westminster hospital, we have shown that a significant proportion of the variance in population demographics between the 5 subgroups of KS are tautological findings based on the characteristics of the current classification system. For example, classic KS patients were older in a group defined as ‘elderly’, similarly, there were more Black people in the endemic KS group defined geographical as patients from Africa, there were more cis-men in the HIV associated KS group (HIV remains most common in MSM in the UK ) and morFurther issues with the current classification system are highlighted as follows. Endemic and classic KS classification are both based upon the geographical location of the patient. However, as migration is possible, geographical location could be based upon the place of birth or upbringing (as most HHV8 acquisition is before the age of 20 years ) or baseIn this study we investigated the current classification system by comparing demographic, clinicopathological, virological and immunological parameters in the classic and endemic KS populations. Whilst demographic differences were present e.g. classic KS patients were older (mean 74 vs 59 years) KW P = 0.0004*, this difference is inherent to the current classification system. In contrast, there were no significant clinicopathological differences between these two classifications nor were there differences in blood based immune cells or HHV8 viral levels. The same was true when classic KS and endemic KS were compared to MSM KS, though overall MSM KS appeared to have a less severe clinical presentation.Given this lack of clinicopathological or immunological differences between classic, endemic and MSM KS, which together comprise those patients defined as non-immunosuppressed, we re-interrogated the dataset based on the presence or absence of immunosuppression as it may reflect a more meaningful difference in pathogenesis of KS than the current classification system.By reclassifying patients to a non-immunosuppressed  or immunosuppressed (HIV associated and iatrogenic KS) system we showed that there were meaningful differences between KS clinicopathological findings at presentation. This included more disseminated skin disease and more advanced disease  at presentation of KS. Within the immunocompromised group, there was a trend towards more visceral involvement of each subtype, including GI, pulmonary and other visceral involvement. In terms of blood parameters there were lower CD4 counts and leuckocyte counts, higher CD8 counts and a trend towards higher HHV8 viral load in the immunocompromised group, and MCD another HHV8 associated disease was also more common. These findings show that this classification system defines a real difference in pathogenesis between the two groups, in contrast to the current classification system. This division of KS into immunosuppressed and non-immunosuppressed also has therapeutic relevance. The approach to KS in immunosuppressed individuals is to improve the immune function either with cART to treat HIV or by reducing the anti-rejection therapy in the case of allograft recipients prior to direct anti-KS therapy. In contrast in immunocompetent individuals with KS, the treatment strategies are directed against the KS lesions directly usually using surgery, radiotherapy or chemotherapy.Potential weaknesses to this proposed classification system exist. Firstly, there is no difference in OS or disease specific survival between the two groups despite the noted clinicopathological differences, and, as the number of deaths was low, the cohorts were underpowered for overall survival analyses. The event rate was even lower for disease specific survival, which was similarly underpowered, and no distinction on the recurrence rate of KS was possible between the two groups. This study was undertaken after the widespread use of cART which produced dramatic improvement in KS survival in the HIV associated KS group , and thuSecondly, our data set is from the national HIV oncology centre and therefore a significant number of the patients in this study have HIV associated KS which subsequently comprises the majority of the immunosuppressed group. This may bias the analysis of the data particularly in the immunosuppressed group. However, this also reflects the rarity of iatrogenic immunosuppression coupled with a potential low level of KS in the iatrogenic group which may be less exposed to the HHV8 virus, and therefore is likely to remain a small component of immunosuppressed KS numbers.Thirdly, it is apparent that immunocompetence does not exist as a binary element but rather as a continuum. This is reflected in patients with HIV associated KS who may have regression of their disease when they start anti-retroviral therapy  or when However, as a broad classification, the immunosuppressed versus non-immunosuppressed is a logical division as those with HIV associated KS and iatrogenic KS have factors causing additional immunosuppression compared to those that maybe in action in the non-immunosuppressed (classic/endemic/MSM) group, including immunosenescence or more poorly understood factors such as chronic infection or malnutrition . As we hIn conclusion, the data we have presented shows that the current classification system is suboptimal, and poorly defines meaningful clinical and pathogenic differences between the subgroups. We propose that a more clinically relevant classification system for KS is to divide patients into immunocompromised and non-immunocompromised groups as this is closely linked with more advanced presentation in the immunocompromised patient and can be more helpful with guiding the need for more aggressive clinical therapeutic approaches.Additional file 1. Clinical Presentation of KS. A) Distribution of skin sites of KS. B) Characteristics of Advanced KS including sites of involvement for disseminated disease tumour oedema and tumour ulceration.Additional file 2. On median overall survival.Additional file 3. Clinicopathological features and virological parameters of patients with Classical versus Endemic KS.Additional file 4. Virological and immunological parameters according to current classification system with Classical, Endemic and MSM KS.


Aims and objectivesThis study was carried out to evaluate the efficacy of 8.4% sodium bicarbonate-buffered local anesthetic solution and conventional local anesthetic in patients requiring bilateral maxillary orthodontic extractions in terms of pain on injection, onset of action, and duration of action.Methods102 patients requiring bilateral maxillary orthodontic extractions were included in the study. Buffered local anesthetic was administered on one side while conventional local anesthesia (LA) was administered on the other side. Pain on injection was measured using a visual analogue scale, while onset of action was measured by probing the buccal mucosa after 30 seconds of administration and duration of action was measured by the time after which the patient experienced pain or took a rescue analgesic. The data was statistically analyzed to determine the significance.ResultsThe pain during injection was found to be lesser at sites where buffered local anesthetic was administered  score = 2.4) as compared to conventional local anesthetic (mean VAS score = 3.9). The onset of action was faster with buffered local anesthetic  as compared to conventional local anesthetic . Lastly, the duration of action was found to be longer for buffered local anesthetic group  as compared to conventional local anesthetic .Conclusion8.4% sodium bicarbonate-buffered local anesthetic was found to be more efficient than conventional local anesthetic in terms of reduction in pain on injection as well as faster onset and longer duration of action. Local anesthesia (LA), over time, has made performing surgical procedures easier for healthcare professionals and leads to a better treatment experience for the patients. It prevents pain during surgical procedures by numbing a specific part of the body. Its effects are short lived; hence, healthcare professionals often use it for minor outpatient procedures. The first procedure in LA was done by Karl Kohler when he used cocaine . NowadayLignocaine 2% with epinephrine 1:100,000, is the most common amide anesthetic used when giving local-infiltration anesthesia. It has a rapid onset and a moderate duration of action. Its low dissociation constant (pKa) and high lipid solubility are both factors that influence the quick onset of action . Yet anoLignocaine is the most common choice for most healthcare professionals. It is an effective anesthetic, with a rapid onset and an excellent safety record. It is very effective and free of any untoward side effects, although, administration of lignocaine can be painful .A plethora of factors influence the pain of injection, including the introduction of needle, rate of injection, pressure from the fluid distention of the tissue, and the pH of the solution ,7. LignoSodium bicarbonate can be added to lignocaine in order to increase the pH of the anesthetic solution to reduce the burning or stinging sensation . Several102 patients requiring bilateral extractions of maxillary premolar teeth for orthodontic treatment were selected. The study was conducted by a split mouth method. The extractions were performed over a single appointment, wherein non buffered 2% lignocaine with 1:80,000 adrenaline was administered to one side (control group), while 2% lignocaine with 1: 80,000 adrenaline freshly buffered with 8.4% sodium bicarbonate in 10:1 ratio was administered on the other (study group). The study was approved by Bharati Vidyapeeth (Deemed to be University), Dental College and Hospital, Pune, India Institutional Research Committee with IRB number BVDU/DCH/680-1/2020-21. Both the operator and the patient were blinded to the solutions used. Patients included in the study were aged 14 years or older of either gender, who had bilateral maxillary premolar teeth indicated for orthodontic extraction, who were willing to participate, and who were free of any significant systemic diseases. Patients excluded from the study consisted of medically compromised patients, patients having known allergy to lidocaine, mentally challenged patients, patients unable to communicate, pregnant and lactating women, and patients unwilling to be a part of the study or unable to come for follow up.Informed consent was obtained from all the patients. The operator was blinded to the solutions that were to be administered to avoid bias. One syringe contained conventional local anesthetic solution while the other syringe contained buffered local anesthetic solution. The first parameter to be measured was pain on injection, which was measured on a visual analogue scale (VAS). It is a 10-point scale, where a score of 0 equals no pain and 10 equals very severe pain. The VAS score was entered after the procedure by showing the VAS scale to the patient. Further, onset of action was measured as the time taken for the anesthetic solution to act. It was measured by probing the buccal mucosa after 30 seconds of administration, in regular intervals of five seconds till the patient did not feel the probe. Lastly, the duration of action was recorded on the subsequent visit by asking the patient the time after which he/she experienced pain or the time when he/she consumed a rescue analgesic.All the data obtained was subjected to statistical analysis (Mann-Whitney U Test).The total sample size on which the parameters were assessed was 102 (204 sites). The pain during injection was found to be lesser at sites where buffered local anesthetic was given in 72.56 % of patients, whereas 18.62 % of patients found buffered anesthesia to be as painful as non buffered anesthesia. However, 8.82 % of patients found buffered anesthesia to be more painful than non buffered. The descriptive statistics for pain in terms of mean VAS score has been provided in Table The onset of anesthesia of buffered anesthetic is believed to be faster than non buffered local anesthetic. Amongst the 102 patients, in 92.34 % patients, the onset of action was faster in buffered LA. On the other hand, there was no difference in onset of action between control & study in 6.68% of patients and in 0.98% of patients, buffered anesthetic took a longer time to act. Table The duration of action was found to be more for buffered local anesthetic in 81.61% of patents, whereas the duration of action was same for both in 7.61% and lesser in 10.78% for buffered local anesthetic. Table The comparison between the study group and the control group with respect to the three important parameters has been conducted using the Mann-Whitney U test as the values did not follow normal distribution and it has been depicted in Table Local anesthetics can be described as salts that have been dissolved in sterile water or saline. The local anesthetic medication is present in solution as positively charged (BNH+) and negatively charged (BN) molecules (cation). Only the base (BN) component of a local anesthetic solution can pass through the epineurium. Charged cation and uncharged base molecules are distributed equally when the pKa equals the pH. The quantity of solution that will cross the epineurium and be transformed into positively charged BNH+ ions, which block sodium channels, will increase in proportion to the amount of the base form present. Therefore, a low pH of a solution or tissue will result in less free BN ions and delay or diminished local anesthetic effect in cases of infections. It is particularly challenging for the normal injection to deliver appropriate anesthesia at the infection site due to lower tissue pH. Because infected tissue is more acidic, BN conversion struggles to take place -15The burning feeling that occurs during injection and the delay in action are two of the main problems that can occur after using a local anesthetic solution . CommercTo maximize stability in solution and shelf life, a commercially available local anesthetic solution must have an acidic pH . An amidLocal anesthetics, however, have a number of disadvantages, such as the stinging effect they produce on injection. A degree of tissue damage upon injection is also linked to local anesthetics. Local anesthetics begin to work relatively slowly. Furthermore, in the presence of infection and inflammation, local anesthetics do not function as consistently.2, and eliminates injection pain, stinging, and tissue harm [Anesthetic buffering can be used to get around each of these limitations. It decreases the onset time, offers anesthetic effect of COsue harm . For nersue harm .Alkalinization may have benefits. First, the patient might feel less stinging discomfort due to the solution's higher pH. Second, the pH of the injected solution may more quickly approximate the pH of the typical tissue following injection. The more quickly a mixture of charged and uncharged forms formed, the more quickly drug diffusion and nerve blockage begin. This may be especially helpful at body sites where there may be a delay in the pH rise after injection due to inadequate tissue buffering capacity .3) to buffer the anesthetic following the injection in vivo (within the body), but the ex vivo (outside the body) method represents a means to achieve the pH change instantly and more consistently [Warming lignocaine, buffering it with a chemical agent, and warming buffered lignocaine are all alkalinization techniques . An alteistently .2 and water are produced as by products of buffering with bicarbonate. Catchlove earlier verified that the interstitial fluid pH within the nerve sheath tends to decrease when CO2 is present [2 diffuses quickly through the nerve sheath and reaches the axon before the anesthetic solution, it has the potential to produce an immediate kind of analgesia in comparison to lignocaine. Buffered anesthetics in a glass carpule may be as useful as gas, but they may also be unstable. The freshly made buffered mixture should be delivered right away because too much alkalinity can lead to precipitation in the solution. According to Momsen et al., buffered lignocaine adrenaline solution is stable for up to 24 hours after preparation [In the world of medicine, the idea of local anesthetic buffering is widely accepted. In a systematic review by Davies on the buffering of LA, it was discovered that using sodium bicarbonate as a buffer significantly decreased injection discomfort without compromising efficacy . The mos present . As a reparation .In our present study, a split-mouth method was used wherein conventional local anesthetic was administered on one side and buffered local anesthetic was administered on the other. Regarding pain on injection, most of the patients experienced less pain in sites where buffered local anesthetic was administered as compared to conventional local anesthetic. For the study group, the minimum pain threshold was 0, while for the control group, it was 1. The study group's maximal pain threshold was 6, whereas the control group's threshold was 8. The study group's mean ± SD was 2.40 ± 1.51, while the control group's was 3.90 ± 1.54. The p value was found to be 0.000* . In terms of onset of action, sodium bicarbonate buffered local anesthetic had a faster onset of action as compared to conventional local anesthetic. All the patients were probed in regular intervals of five seconds after 30 seconds of administration and were asked if they felt pain. The patients claimed to stop experiencing pain sooner on the sides where buffered local anesthetic was administered. However, there were a few exceptions wherein buffered local anesthetic seemed to act slower than conventional local anesthetic. The study group's mean ± SD was 62.30 ± 23.60, while they were significantly higher for the control group at 157.16 ± 36.69. The p value of the same was 0.000* . The dissociation constant (pKa) level of a local anesthetic plays a major role in determining when it starts to work. A lower pKa speeds up the commencement of action and improves tissue penetration. Warming and buffering may cause the pKa to change, increasing the proportion of particles in the unionized state. Unionized particles diffuse into the neuron more quickly, resulting in more speedy and efficient inhibition of nerve.Both our results are in agreement with a study done by Kashyap et al., who evaluated the outcome of buffering 2% lignocaine with 1:80,000 epinephrine using a prospective randomized study with 100 individuals and concluded that the group receiving buffered lignocaine experienced much less injection pain (p = 0.0001) and significantly faster local anesthetic onset (p = 0.001) . A randoIn a study done by Siler et al., there were no appreciable differences between buffered and non-buffered solutions in terms of the spread of analgesia, the length of the process, the duration of total anesthesia, and the regression of anesthesia . They loThe duration of action too was longer on sides where buffered LA was administered. It was measured on the subsequent visit by asking the patient the time when he/she started experiencing pain or consumed a rescue analgesic. The study group's minimum and maximum values were 120 minutes and 274 minutes, respectively, while the control group's values were 150 minutes and 250 minutes, respectively. The study group's mean ± SD were 225.65 ± 30.16 minutes and 187.00 ± 13.78 minutes, respectively, while p value was found to be 0.000* . This result is in agreement with a study done by Afolabi et al., who investigated the effect of buffering lignocaine on pain on injection and duration of action and concluded that buffering lignocaine increased the duration of its anesthetic effect . Although our sample size is relatively larger than the previous studies performed, we would recommend further studies on a much larger sample size for a more comprehensive outcome. Furthermore, our study was performed in cases requiring bilateral orthodontic extractions with no infection. However, routine extractions also consist of teeth with periapical infections and hence, more studies should be conducted with respect to infective cases to determine the efficacy of buffered local anesthetic solution in the same.Advancement in LA is an evergreen prospect in the field of maxillofacial surgery and dentistry as a whole. The ultimate goal is to provide to the patient a painless and pleasant treatment experience and this goal starts with administration of painless anesthesia. Out of all the available modalities, buffered LA seems to be a viable, and at the same time, an economical alteration that could be made to conventional LA for making the administration more pleasant for the patient. Our study proves that buffered local anesthetic is significantly better than conventional local anesthetic owing to its lesser pain on injection, faster onset of action and longer duration of action. The application of buffered LA in dentistry should therefore be looked into as a possible solution in reducing patient discomfort during injection and achieving a faster anesthetic effect. Further studies could also be conducted in the future to explore the utility of buffered LA in infective cases because of its raised pH.


Cyanobacteria  can accumulate to form harmful algal blooms (HABs) on the surface of freshwater ecosystems under eutrophic conditions. Extensive HAB events can threaten local wildlife, public health, and the utilization of recreational waters. For the detection/quantification of cyanobacteria and cyanotoxins, both the United States Environmental Protection Agency (USEPA) and Health Canada increasingly indicate that molecular methods can be useful. However, each molecular detection method has specific advantages and limitations for monitoring HABs in recreational water ecosystems. Rapidly developing modern technologies, including satellite imaging, biosensors, and machine learning/artificial intelligence, can be integrated with standard/conventional methods to overcome the limitations associated with traditional cyanobacterial detection methodology. We examine advances in cyanobacterial cell lysis methodology and conventional/modern molecular detection methods, including imaging techniques, polymerase chain reaction (PCR)/DNA sequencing, enzyme-linked immunosorbent assays (ELISA), mass spectrometry, remote sensing, and machine learning/AI-based prediction models. This review focuses specifically on methodologies likely to be employed for recreational water ecosystems, especially in the Great Lakes region of North America. Aphanizomenon, Cylindrospermopsis, Dolichospermum, Microcystis, Nodularia, Planktothrix, and Trichodesmium, which have regulatory impacts on the ecological processes of aquatic ecosystems . On. OnM. aer 2–4 h)  [42].Similar to ultrasonication, physical cell lysis methods also circumvent the issue of chemical contamination. Despite the inconsistencies in efficiency, bead beating remains a standard method for most cell lysis protocols ,59,60,61Synechocystis and Synechococcus spp., allowing for maximal lysis of cyanobacterial cells . Co. CohttpsChromatography purifies compounds (including cyanotoxins) based on hydrophobic, hydrophilic, ionic, or affinity-based mobility through a separation medium . It can Microcystis and Planktothrix spp. [Conventional polymerase chain reaction (PCR) uses amplification of organism-specific, genomic DNA sequences for qualitative (absence or presence) analysis, while real-time PCR or quantitative PCR incorporates DNA binding dye or probe to quantify the DNA target  in purified DNA  . Newer drix spp. , it is nrix spp. ,100. Attrix spp. ,102,103.mcyE (microcystin gene cluster) assay detects all potential microcystin producers and the nodularin synthetase gene clusters [mcyA assay covers many, but not all, microcystin-producing strains [mcyE and mcyG assays are sensitive and specific to Microcystis and Planktothrix [mcyE assay was reported to be 3–63 gene copies per PCR reaction  can provide a detection limit of 6 × 10−12 M of target DNA [M. aeruginosa can detect approximately 50 cells/mL in purified DNA and 500 cells/mL for river water samples , Medium Resolution Imaging Spectrometer (MERIS), and Ocean and Land Color Instrument (OLCI) due to their optimum temporal, spatial, and spectral resolutions ,129. A nRemote sensing can especially be useful for inland water bodies , includiThere are specific challenges accompanying the application of remote sensing for bloom monitoring, a major one being the need to identify surrogate pigments. Variability in the correlation between chlorophyll-a/phycocyanin and cyanotoxins can make it difficult to accurately infer water toxicity from satellite imagery, especially for microcystins . Remote Microcystis spp.), with average precision values ranging from 0.890 to 0.973 [Following the ever-increasing volume of available data on aquatic ecosystems, artificial intelligence and machine-learning algorithms can become valuable tools in making predictions on cyanobacterial bloom activities. There are multiple ways in which these algorithms can be applied to cyanobacterial monitoring, including cell imaging and water quality prediction deep learning algorithms ,141,142.to 0.973 . Chloropto 0.973 .Unlike conventional or molecular biology methods, models rooted in artificial intelligence and machine learning can solve more complex problems with a greater number of variables . Once prCyanobacterial harmful algal blooms threaten the conservation of essential freshwater ecosystems, including the North American Great Lakes. Conventional/standard molecular methods for cyanobacterial detection are available. However, specific limitations are associated with each method.Cyanobacterial cells resist disruption methods making quantitative recovery of potential diagnostic molecules difficult. However, optimizing protocol parameters and combining multiple lysis methods can lead to complete disruptionELISA-based toxin detection methods (including microfluidic devices) alone cannot resolve or quantify all microcystin congeners. Chromatography–mass spectrometry methods can unambiguously identify microcystins and other cyanotoxins. However, the obtained information is difficult to incorporate into a public health response due to the lack of commercially available standards.Mcy (microcystin synthetase) gene cluster.DNA diagnostic methods  targeting the 16 s rRNA gene, while useful for other bacteria, is of limited value for cyanobacteria due to insufficient specificity. This obstacle can be countered by metabarcoding or targeting a toxin gene such as the Bloom monitoring may be aided by novel technologies, particularly in quickly establishing spatiotemporal characteristics of specific events. These technologies can augment traditional characterization methods in producing a public health response. However, while ongoing, standardization of common tools for this ancillary information still needs to be completed.Newer/modern technologies, including satellite imaging, biosensors, and machine learning/artificial intelligence methods, can be integrated with the conventional/standard molecular methods to overcome the problems associated with cyanobacterial detection in recreational water ecosystems, including the Great Lakes.


During the COVID-19 pandemic, web-based media coverage of preventative strategies proliferated substantially. News media was constantly informing people about changes in public health policy and practices such as mask-wearing. Hence, exploring news media content on face mask use is useful to analyze dominant topics and their trends.The aim of the study was to examine news related to face masks as well as to identify related topics and temporal trends in Australian web-based news media during the early COVID-19 pandemic period.Following data collection from the Google News platform, a trend analysis on the mask-related news titles from Australian news publishers was conducted. Then, a latent Dirichlet allocation topic modeling algorithm was applied along with evaluation matrices . Afterward, topic trends were developed and analyzed in the context of mask use during the pandemic.A total of 2345 face mask–related eligible news titles were collected from January 25, 2020, to January 25, 2021. Mask-related news showed an increasing trend corresponding to increasing COVID-19 cases in Australia. The best-fitted latent Dirichlet allocation model discovered 8 different topics with a coherence score of 0.66 and a perplexity measure of –11.29. The major topics were T1 , T2 (introducing mask mandate in places such as Melbourne and Sydney), and T4 (antimask sentiment). Topic trends revealed that T2 was the most frequent topic in January 2021 (77 news titles), corresponding to the mandatory mask-wearing policy in Sydney.This study demonstrated that Australian news media reflected a wide range of community concerns about face masks, peaking as COVID-19 incidence increased. Harnessing the news media platforms for understanding the media agenda and community concerns may assist in effective health communication during a pandemic response. In response to the initial phase of the COVID-19 pandemic, Australia implemented widespread testing, strict lockdown, and hotel quarantine measures . In JuneThe SARS-CoV-2 is the viral pathogen that caused the COVID-19 pandemic in 2020 . Face maIn line with existing supportive evidence on community use of face masks, many countries that historically do not have a mask-wearing culture have initially adopted a mask-wearing policy, while other countries with an established mask-wearing culture have continued to use masks . AustralDuring national crises and health emergencies, news media plays a central role in a contested landscape of uncertainty -15. NewsAgenda-setting theory has been considered one of the most popular conceptual frameworks in communication research , referriWhile news media exercises the power of considerable discretion in choosing content for its storylines, media reporting on face masks can be designed within the skeleton of agenda-setting theory . An ideaAt the beginning of the COVID-19 pandemic, Thomas et al  identifiLee et al  and Suh Manual thematic analysis has limitations, especially in terms of scale. Natural language processing–based computational topic modeling techniques, in contrast, can handle complex and large amounts of data . As partThe aim of the study was to examine news related to face masks as well as to identify related topics and temporal trends in Australian web-based news media during the early COVID-19 pandemic period.Relevant data for the analysis were collected, both retrospectively and prospectively, from keyword-specific Google News search and Google News alert. Retrospective data were collected from January 25, 2020, to September 11, 2020, via Google News search. Subsequently, a customized Google News alert was set to collect prospective data from September 12, 2020, to January 25, 2021. For the retrospective and prospective data extraction, the keyword “mask” was used in conjunction with the ~ (tilde) symbol. That means the generated results, for both the Google News search and Google News alerts, contained the keyword or the synonyms (or both).The results were then joined to form a combined data repository and named as “News topic data set.” In that repository, news titles containing the search keyword and its synonyms were regarded as most relevant, and therefore only those news titles were selected for the analysis. Additional eligibility criteria were established to include consistent, reliable, and uniform data.The inclusion criteria were (1) news titles in the English language and (2) news published by Australian news publishers only.The study excluded irrelevant “mask”-related news articles such as beauty mask and sheet mask.As part of the descriptive data analysis, the trend in the number of mask-related items published in news on the internet was explored by plotting the frequency of occurrence in relation to key events during the COVID-19 pandemic, face mask–related incidents, and policy announcements in Australia (as described in the Result section). The key events were obtained from the Australian Government’s website and national news reports.Exploratory data analysis of the news titles in the “News topic data set” was done by topic modeling technique. Topic modeling is a probabilistic computational method that identifies latent semantic patterns of word co-occurrence, also known as topic, in a collection of digital documents . There aPreprocessing of the news titles was performed in Python  . The datMeaningful numerical representation of the features in the corpus is called vectorization. It represents the textual data for better understanding by the machine and is often considered to be imperative in natural language processing applications . Term frWe again used Python to develop the LDA model . LDA reqAs there is no statistical test to determine the number of topics (k), evaluation matrices can be used as a guide to identifying the best fit for the data set. We developed our model with different numbers of topics (k=1 to 20) and evaluated them according to both quantitative and qualitative matrices. Initially, we selected the top 3 models according to their performances on the quantitative evaluation scale. We then qualitatively analyzed those top 3 models and selected the best model for our data set.Two quantitative matrices were used to evaluate the models.Perplexity is a statistical measure to estimate the performance of a probability model in predicting a sample. A lower perplexity score indicates a better model for predicting the existing topics in the data set . HoweverThe coherence score refers to the degree of semantic similarity among high-scoring words in a topic ,43. It iResults section.Both the perplexity measures and the coherence scores for our LDA topic models (with different numbers of topics) are shown in the To visualize the topics, we used LDAvis , a bubblA word cloud for each topic shows dominating terms for the topic. The word cloud is constructed using the topic terms and their probabilities in the topic construction. Dominating terms can be easily identified and compared contextually, both within and outside the topic. The word cloud of our final LDA model is visualized in the Results section.For a contextual analysis of the topics, we tabulated the most-representative news title for each topic and the proportion of the topic in that particular news title.Upon selection of the best-fitted model, the model can be examined at both macro and micro levels. At the macro level, the model provides an overview of the individual topic throughout the observation period. In contrast, microlevel observation can use the temporal variation of the data and illustrate the trends of the topics. In this study, the observation period was separated per month, resulting in 13 time slices, spanning January 25, 2020, to January 25, 2021. Each news title was tagged with its dominant topic . Then, the distribution of the dominant topics for news titles was plotted for the 13 time slices. The evolution of the topics is illustrated in a heat map.A total of 2404 mask-related Google News titles were identified in Australian web-based news websites from January 25, 2020, through to January 25, 2021. After excluding 59 irrelevant items (2.45%), a data set of 2345 mask-related news titles was finalized. The leading publishers were the national mainstream news media, such as ABC News, 7 News, and Sydney Morning Herald.As part of the qualitative evaluation, we used the Intertopic distance maps of the models. We named the topics according to their dominant terms: mask-related international affairs (T1), introducing mask mandate in places such as Victoria and Sydney (T2), implementing mask mandate in Sydney (T3), antimask sentiment (T4), miscellaneous topic (T5), mask use in public places (T6), promoting mask-wearing (T7), and mask-wearing after the lifting of restriction (T8).The miscellaneous topic (T5) included news articles related to the challenges of mask-wearing in western culture. In addition to the example in The heat map distinctly represents both similar and opposite trends of topic evolution. Few mask-related news items were published in the initial 6 months (January 2020 to June 2020), followed by a sharp increase afterward for all the topics. In the first half of our analysis, January 2020 to June 2020, news relating to T2, T4, and T7 appeared more frequently. Then T2 and T4 were predominant with a peak in January 2021 (77 items for T2 and 70 items for T4).During the COVID-19 pandemic, national mainstream media organizations were at the forefront of reporting mask-related stories in Australia. We conducted a series of LDA analyses of our corpus on mask-related news items, using quantitative and qualitative measures to identify the best-fitted model (the best number of topics). Even though both coherence score and perplexity measure were used to quantitatively assess our LDA model performances, the utility of perplexity measure was deemed negligible in our LDA model selection. Based on the evaluation matrices, we identified 8 topics related to face masks, with 3 key topics: mask-related international affairs (T1), introducing mask mandate in places such as Victoria and Sydney (T2), and antimask sentiment (T4). Both T2 and T4 were dominant and peaked in January 2021. This study demonstrated the utility of a data-driven approach to analyzing news media and identified how it communicated health-related information during a public health crisis.During the study period, there were 2 distinct waves of mask-related news publications in Australia. The second wave was much stronger than the first and was mostly caused by local spikes in COVID-19 cases and the introduction of mandatory mask-wearing in different states. In a comparative cluster analysis, Yang et al  found a Similar to our study methodology, Suh et al  used an Topic wise, T1  was one of the major topics identified in our corpus, with 334 news titles. The most representative news title under this topic showed that Australian web-based media coverage of mask-related international events was mostly from the US political arena. Considering the escalating conflicts between politicians and the later politicization of mask use in the US election, this topic reflects the centralized role of the United States in overall “mask madness” . Lee et T2 of our LDA model was about introducing mask mandates, mainly in response to the new cases of COVID-19 in Victoria and Greater Sydney. This topic gained the highest media coverage, with a total of 384 news titles. On the temporal trend analysis, this topic reflected the government-led agenda on mask-wearing and evolved along with the mask-relevant policy changes across the states in Australia. The highest amount of T2 specific news coverage (77 items) was recorded during the mask mandate in the Greater Sydney region in January 2021, followed by the Melbourne mask mandate 56 items) in July 2020. The predominance of the second topic around the policy change implied that the reporting by Australian media was timely and in line with a policy maker’s guideline to promote mask-wearing  items in identifiOur third topic (T3) was related to mask mandates in the Greater Sydney area, reflecting mostly actions taken by law-enforcement agencies. This topic also depicted different attitudes of the political leaders and public figures toward face masks and associated policy development. Over time, T3 was consistent from the time of the Melbourne outbreak in July 2020. Following the outbreak in the Greater Sydney region in January 2021, this topic exhibited an increased number of related news publications.Besides T2, the next major topic was related to antimask sentiments (T4). In our study, a total of 352 news titles were recorded under this topic. Lee et al  had a siWith 295 relevant news articles, T6 was about news encouraging mask-wearing in public places and at events. Similarly, T8 described mask-related policy implementation while reopening offices and educational institutions. With 252 mask-related articles, this topic drew more attention during September 2020. Overall, T6 and T8 focused on the universal adoption of face masks and integrating the concept of mask-wearing in regular and recreational events. These topics suggest the importance of mask-wearing to minimize COVID-19 transmission while getting “back to normal.” In the United States, mask-wearing policies related to school-reopening strategies effectively reduced the community transmission of COVID-19 . In inteThe next topic in our study, T7, was about the innovative promotion of mask-wearing. With 245 news titles, this topic developed since the recommendation of the US CDC on wearing nonmedical face masks in public places. During the second phase of our study, from July 2020, T7 evolved constantly and might contribute to encouraging mask-wearing by framing positive social messages in the news content. Furthermore, these positive social messages can contribute to developing positive social cognitions in the community .Last, T5 was regarded as a miscellaneous topic with the least news coverage. Topic-specific keywords did not cluster under any specific topic. On the temporal analysis, the number of such miscellaneous news gradually decreased, making a place for more structured and topic-specific media messaging in Australian web-based news platforms. In contrast, Suh et al  identifiOur study has several strengths that can be attributed to both the methodology and the outcome of the study. Methodological strengths include the inclusion of both national and local news media reports on face masks in Australia. Although international news articles rarely reflect the Australian national agenda, selective news websites may not represent all the national issues. Additionally, the data collection tool Google News is distinctly advantageous over other news databases such as LexisNexis. Google News provides more reliable data and can capture more local news and nonprint articles that are often overlooked in other database searches . MoreoveThere are several limitations that can be attributed to this study. One of the major limitations is analyzing only the news titles. They might not provide adequate context to capture appropriate topics for corresponding news articles. However, considering the structural integrity of news titles in summarizing news themes, it is likely still meaningful. In future research, we could aim at capturing both the title and the snippet returned by the search engine. By using images from the news and their associated titles, visual topic modeling could also be a novel approach to address the limitations of only news title analysis . FurtherAppropriate preventive strategies, health communication, public education, and active community participation have always been at the center of effective pandemic responses. News media platforms, as primary sources of updated health information, could serve the interests of the government and the community by disseminating information about health policies and healthy behaviors. However, the media can also amplify dissent and uncertainty. This study highlighted the public health recommendations about mask wearing and diverse aspects of mask use (or not) in the media. Timely, targeted, and transformative media messages can rapidly spread around the world, and therefore those messages can facilitate local and global community adoption of mask-wearing which will benefit all.


Big data tools provide opportunities to monitor adverse events  (AEs) in the unstructured text of electronic health care records (EHRs). Writers may explicitly state an apparent association between treatment and adverse outcome (“attributed”) or state the simple treatment and outcome without an association (“unattributed”). Many methods for finding AEs in text rely on predefining possible AEs before searching for prespecified words and phrases or manual labeling (standardization) by investigators. We developed a method to identify possible AEs, even if unknown or unattributed, without any prespecifications or standardization of notes. Our method was inspired by word-frequency analysis methods used to uncover the true authorship of disputed works credited to William Shakespeare. We chose two use cases, “transfusion” and “time-based.” Transfusion was chosen because new transfusion AE types were becoming recognized during the study data period; therefore, we anticipated an opportunity to find unattributed potential AEs (PAEs) in the notes. With the time-based case, we wanted to simulate near real-time surveillance. We chose time periods in the hope of detecting PAEs due to contaminated heparin from mid-2007 to mid-2008 that were announced in early 2008. We hypothesized that the prevalence of contaminated heparin may have been widespread enough to manifest in EHRs through symptoms related to heparin AEs, independent of clinicians’ documentation of attributed AEs.We aimed to develop a new method to identify attributed and unattributed PAEs using the unstructured text of EHRs.We used EHRs for adult critical care admissions at a major teaching hospital (2001-2012). For each case, we formed a group of interest and a comparison group. We concatenated the text notes for each admission into one document sorted by date, and deleted replicate sentences and lists. We identified statistically significant words in the group of interest versus the comparison group. Documents in the group of interest were filtered to those words, followed by topic modeling on the filtered documents to produce topics. For each topic, the three documents with the maximum topic scores were manually reviewed to identify PAEs.Topics centered around medical conditions that were unique to or more common in the group of interest, including PAEs. In each use case, most PAEs were unattributed in the notes. Among the transfusion PAEs was unattributed evidence of transfusion-associated cardiac overload and transfusion-related acute lung injury. Some of the PAEs from mid-2007 to mid-2008 were increased unattributed events consistent with AEs related to heparin contamination.The Shakespeare method could be a useful supplement to AE reporting and surveillance of structured EHR data. Future improvements should include automation of the manual review process. Macbeth , indications, and signs and symptoms are harder to detect than other information such as drug names” Medical entities in EHRs notes “can span across multiple words” “… there is a lot of ambiguity among relevant named entities. Depending upon the context, the same exact phrase can be an ADE, indication, or a sign and symptom” Periods do not always indicate the end of a sentence  “…notes are frequently ungrammatical and are often inconsistently formatted. Ambiguity is common: MS, for example, can mean mitral stenosis or multiple sclerosis” EHRs are “…subject to access restrictions…” “…[N]ot all events and outcomes are consistently captured…” We observed that different medical specialties, nurses, and other health care providers used different vocabulary.We used the Medical Information Mart for Intensive Care III (MIMIC-III) EHR data set ,43 becau...several sentence segmentation tools available in popular NLP [natural language processing] toolkits, such as NLTK31 and spaCy, were tested and did not work well in clinical notes. In clinical notes, sentences do not always end with regular punctuation marks such as a period or question mark. More specifically, both regular punctuation marks and newline characters can serve as sentence breakers; however, newline characters can also be used for text wrap. Moreover, enumeration-like and list-like formats are also common in clinical notes, especially for physical exam and list of medications.Many medical care AEs occur at higher frequency in hospital critical care settings and are related to complex illnesses, invasive procedures, and relatively long lists of treatments ,45.We used EHRs for critical care admissions within an adult hospital, the Beth Israel Deaconess Medical Center in Boston, MA. The Massachusetts Institute of Technology worked with the hospital to process EHRs from 2001 to 2012, including unstructured notes, into the MIMIC-III data set, which is publicly available to those meeting certification requirements. The research was designated as not human subjects research by the FDA Institutional Review Board under the Code of Federal Regulations, Title 45, Part 46  and logistic regression [LR]) and filtering -62 was uTopic modeling is an unsupervised method commonly used in NLP to extract the most relevant terms for each topic (cluster) of similar documents ,64. We cWe performed topic modeling F,G by apTopic modeling resulted in a matrix of scores for each term by each topic, which we refer to as term scores F. An addThe maximum document topic scores distribution was plotted in the maximum topic histogram shown in A small number of documents in the left tail of An important consideration for LDA is that the number of topics must be selected a priori. The results of topic modeling change depend on the number of topics assigned to a corpus—this is an iterative (hyperparameter tuning) process that requires human judgment to interpret the topics (based on the top terms in each topic) and determine which number of topics best fits the corpus. With too few topics assigned, topics are not cohesive and do not add any clarity or information to an analysis. With too many topics assigned, “incoherent” topics that do not capture terms common to the member documents proliferate; additionally, useful topics are likely split among smaller, more specific topics, although that does not limit the ability to analyze true clusters in the corpus.To tune the hyperparameters of the LDA model, we calculated models with the following numbers of topics: 25, 35, 45, 55, 65, 75, and 85. We observed (data not shown):As the number of topics rose, at first, clinically meaningful topics were added. Still, at higher numbers, the additional topics were incoherent, and the large, meaningful topics tended to split in ways that were not meaningful.The top words in topics were generally consistent for topics that were alike across multiple topics. For example, a mechanical ventilation topic was present whether the topic number was 9, 10, or 26.Although particular documents changed, the documents with high top topic scores had the top topic terms.Topics that had high document topic scores had overlapping concepts in the highest-scoring terms.Several topics were difficult to interpret and had low maximum values for both word scores and document topic scores.There were 1 to 2 dozen known TAEs ,67.Many documents had several topics, reflecting the clinical complexity of patients in the critical care unit .To evaluate whether topics described PTAEs, we selected the following records for manual document review: the three top-scoring documents for each of the 45 topics C, and 24We tested comparisons with the Fisher exact test .Despite the inclusion of n-grams with a length of 1 to 5 in the vectorization, the terms that we extracted during classification were unigrams.A histogram of maximum topic scores A showed There was no strict relationship between top word score and the frequency distribution of document topic scores . Table 1Table S1  shows, fTable S2  presentsThe tabulation of the presence or absence of the notes expected to have the most clinical information showed that 122 had a discharge summary, 66 had a nursing note, and 21 had a physician progress note. None of the documents attributed an AE to transfusion in the billing codes.New or worsening PTAEs occurring within 1 to 2 days in the T group were:In the heart category: atrial fibrillation, tachycardia, bradycardia, other heart rhythm abnormalities, hypotension;In the lung category: hypoxia, mechanical ventilation, bilateral pleural effusions, pulmonary edema;In the volume category: edema, diuresis therapy, acute kidney failure;In the absence of evidence for other infections: fever or chills.Many documents (n=40) could not be evaluated for TAEs because either the transfusion dates were missing or there was no identified treatment when transfusion could be presumed. For others, there was a clear alternate reason for heart or lung problems: advanced cancer (n=7), thrombotic thrombocytopenic purpura present at admission (n=1), liver failure (n=1), and lung infection (n=1).Out of the remaining 85 documents with transfusion data, 52 had evidence of PTAEs; the most common were heart PTAEs (n=35) and lung PTAEs (n=33), while non–infection-related fever or chills (n=12) and fluid overload (n=12) were less common. A few documents explicitly considered transfusion as the cause of AEs: in topic 30 (blood disease), one attributed disseminated intravascular coagulation to transfusion and another listed but discarded the possibility of TRALI or TACO, a document in topic 3 (bone trauma from motor vehicle accident) proposed PTAEs, and a document in topic 40 attributed a drop in platelets to transfusion. In 2 documents, the PTAEs were attributed to contrast , a brand name for metronidazole , and surgery (3 cases of bone trauma from a motor vehicle accident).Documents with transfusion timing but no apparent TAE were in the following topics: 10 , 2 , 7 (spine surgery), 18 , 31, and 8. For 10 documents, separate transfusion and PTAE codes were present but were not conceptually linked.We read 24 randomly selected documents to obtain 20 that did not have advanced cancer, cirrhosis, or severe lung trauma. They are summarized at the bottom of Table S2 .P=.02). The analogous analysis for 14 documents in the lung failure topic group showed a higher rate of any lung PTAEs .The documents in the cardiovascular topic group were more likely than the random group to have any of the heart PTAEs , and the notes, but not codes, indicated the patient had a delayed transfusion reaction.The document with pulmonary and volume PTAEs had the following topics with scores ≥0.1: topic 42 (heart attack), topic 24 (tPA [tissue plasminogen activator] to lyse thrombus), topic 10 (cirrhosis), and topic 1 (x-ray confirmation of device placement). The notes attributed worsening acute kidney failure to an antibiotic.The document with only pulmonary PTAEs had the following topics with scores ≥0.1: topic 24 (tPA to lyse thrombus), topic 10 , and topic 37 (kidney failure).The Shakespeare method successfully identified PTAEs. The three top-scoring documents in cardiovascular topics  were associated with cardiovascular PTAEs: atrial fibrillation, tachycardia, bradycardia, other heart rhythm abnormality, or hypotension, which are features of TAEs ,67.Mechanical ventilation and nitric oxide therapy  were used to treat lung failure , which wOther PTAEs that correspond with known TAEs were also observed in the top three documents of topics:Features of the volume overload component of TACO  ;A feature of hemolytic transfusion reaction and febrile nonhemolytic transfusion reaction (fever without other signs of infection) .Incoherent topics had few or no documents with high topic document scores; most documents scored at or close to zero  as described in We then divided the study population into three cohorts: admissions starting between July 1, 2001, and June 30, 2006 ; July 1, 2006, to June 30, 2007 , and July 1, 2007, to June 30, 2008 .To focus on new or increasing AEs, we reduced the number of words to analyze by filtering by whether they were unusual and increasing (or new) in period 3 compared to period 2  and the top 5000 features from NB (those with the lowest log probability ratio). Combining the lists resulted in a set of 9896 terms.We used frequency analysis to find emerging rare clinical events. We identified two groups of terms: (1) those which appeared in fewer than 10% of documents in period 2 and saw a 30% increase in raw frequency in period 3, and (2) any terms that never appeared in period 2 and did appear in period 3. For those new terms appearing in period 3, we filtered out digit-only terms (a large number of terms in this group).For the final feature set, we took the intersection of terms identified from the binary classification and frequency analysis processes. This resulted in 6122 significant terms identified from the initial 117,049 unique terms in the documents from period 3 (5.2% of terms). We revectorized E the 12-The co-occurrence of words in documents in the last time period was analyzed with LDA topic analysis . We chosDocuments from selected individual admissions, as well as summary data from July 2001 to June 2008, were used to evaluate whether any topics formed around AEs. Most topics inspired time plots of selected words, diagnosis codes, or procedure codes  for rare conditions, drugs, events, and languages since the year of admission is being presented. Related substitute words  were used as synonyms.For the most common topics, the admissions with the top three topic match scores are summarized in Table S5 . For theThe three top-scoring documents for topic 18 described long complex stays, which included large numbers of notes. The general words in the topic  were nearly ubiquitous in periods 2 and 3. The words indicating mechanical ventilation  were present in between 51% and 58% of the admissions per quarter in periods 2 and 3, with a slight, clinically insignificant increase for period 3. The lengths of stay and numbers of notes also did not vary between periods 2 and 3.We noticed that among the five records in Table S5  that menTopics 3 and 7 both have cardiac catheterization for heart problems in common; for 5 out of 6 instances, the procedure or heparin administration was followed by hypotension (4 instances) that needed to be treated or heart rhythm deterioration (1 instance). To investigate whether these potential heparin AEs were increasing between July 2001 and June 2008, we plotted two measures of exposure (an invasive cardiac procedure code and “heparin”) and a measure of AE (“hypotension”). The proportion of admissions that had invasive cardiovascular procedure codes A,B decliTopic 19 (and 13) corresponded with trauma. The brain topic  was centered around admissions for brain injury . Topic 4 describes prolonged drainage after abdominal surgery. The index surgeries were performed before admission for 2 instances and during hospitalization for the third. Condition01 was the subject of the three admissions with the top match scores for topic 12. The codes and words were generally rare for the three periods and showed a local increase between periods 2 and 3.Summaries of admissions with topic matching scores for the less common topics are shown in Table S6 . We examA total of 14 PAEs evident in the notes were distributed among the less common topics: 13 related to medical therapy  and 2 were nonmedical. Five drug and all of the medical device PAEs were published in the product labels and/or in the medical literature. Of the PAEs, 9 occurred outside the hospital and were related to the reason for admission. The diagnosis and procedure codes generally did not give enough information to understand the specific cause and associated PAE. The other rare and infrequent terms, related diagnosis or procedure codes, and foreign language sentences were rare throughout all three time periods and increased during period 3.We succeeded in our expectation of finding increases in clinical events and our hope of finding increases in PAEs, especially PAEs that were not attributed and thus likely not reported. We found increases in hypotension following heparin or presumed heparin exposure. Hypotension occurring in the cardiac catheterization lab could be a vasovagal reaction . HoweverOther types of clinical event changes we detected from periods 2 to 3 were increases in patients with common conditions , increases in rare conditions, change in administration (foreign language portion), and PAEs of concern. The increases in common conditions may have reflected hospital marketing . The incNine of the PAEs happened outside the hospital and illustrate the utility of hospital records for monitoring severe reactions that occur in other health facilities or outside the health care system. Our method was useful for detecting words that are rare in hospital records, partly reflecting events that normally occur outside the hospital.The topic with the highest document score exhibited behavior typical of a topic containing words that are common to most documents. The filter that was removing words comprised of only digits also removed digits from some words. This resulted in some high-frequency words entering the vocabulary. When topic modeling, this resulted in high scores for these common words in the topics where they were correlated  and created a common word topic (topic 18). This topic is a noise topic; the LDA model will put words that are low scoring and not correlated with other topics into their own noise topic in order to deal with noise and frequent words. Because this topic included words that were frequent in almost all documents, the document topic scores for this topic were high as expected . This waOur method worked despite:The known challenges posed by clinical text notes;Restriction to one major hospital;Lack of all surgical and non–critical care unit nursing notes, and variable lack of physician, nursing, or discharge summary notes, probably reflecting the hospital policy of gradually converting types of notes to EHRs ;Errors up to several weeks in dates.Different, and hopefully improved, results may be derived from EHR databases that are more complete and have actual dates.LDA topic modeling has been used for a variety of NLP tasks ,64  appeared to play a significant role in distinguishing transfusion from comparison texts. We believe it is possible that enough unigrams that were part of meaningful phrases were also in other phrases or were significant on their own to result in relatively higher scores. For example, although “mechanical ventilation” conveys more meaning than just “mechanical” or “ventilation,” each word occurs singly or in phrases other than “mechanical ventilation.” We observed in the time-based case that similarly only unigrams survived classification.Because bigrams and phrases were important in other LDA studies ,109, we Filtering the vectors to only terms that were important for focusing the topics on clinical conditions specific to the index condition, including reasons for and consequences of the condition, was important for identifying PAEs.We observed that the notes contained much more AE data than explicit discussion. We also found more AE data in the notes than in the diagnosis and procedure codes. Our prior analysis of diagnosis codes  demonstrOur method was successful despite the limitations of this data set. The extent of records for each admission grew during the time that the data were collected because of the hospital’s policy of gradually adding more types of records to EHRs . There wMuch of our manual work to evaluate topics could be reduced with a combination of NLP and dictionaries of clinical terms. Dictionaries should include standard acronyms and common abbreviations, and should try to account for context when the meaning of a term could be ambiguous. The ability to decipher ongoing care notes will be important for noticing unrecognized signals of AEs.Topic analysis of statistically significant words in target documents found records indicative of PAEs, even if the clinician did not explicitly state an outcome was a suspected AE.Among the PTAEs were unattributed evidence of TACO and TRALI. Some of the mid-2007 to mid-2008 PAEs were increased unattributed events consistent with heparin contamination–related AEs. Our results suggest that heparin contamination may have started before it was officially recognized in the winter of 2007-2008.This method succeeded despite a wide variety of vocabulary  and formats  used in the text. The Shakespeare method would likely generalize to other EHR notes and other types of medical texts. The computing tools are accessible and openly available. Their application to EHRs broadens the number of types of entities that could independently conduct surveillance of AEs.It will be useful to adapt NLP methods to automate the abstraction of the notes; the tools will need to be tailored to the various formats used in the notes by different disciplines and individual clinicians. The expansion of vocabulary and acronym lists will also be useful. Automation tools will help to understand how PAEs are distributed within and among topics.


The development of national action plans (NAPs) for antimicrobial resistance (AMR) has been promoted and supported by the WHO, with recent support in the form of costing and budgeting tools to aid in finance-allocation decisions within governments.In this brief report we review this WHO costing and budgeting tool, discuss the strengths and weaknesses, and consider its place alongside other health economics and policy-support tools developed.We call for future analyses of the costs of AMR NAPs to consider costs beyond that of only implementation, through use of other available, open-access data and tools. These include the Global Antimicrobial Resistance and Use Surveillance System (GLASS) data and One Health tools already within the existing ‘WHO toolbox’.We suggest that future work on evaluating AMR along the impact pipeline use this toolbox where possible, ensuring empirical work is in turn open access. The WHO is endeavouring to facilitate the implementation of NAPs; to that end, in Autumn 2021 they released a costing and budgeting tool.3In 2015, the WHO called on every member country to develop a One Health national action plan (NAP) on antimicrobial resistance (AMR), which, as of October 2021, is a target that has been met by 148 countries.4 Here, we summarize this new tool (referred to in this paper as the AMR-NAP tool), discuss its potential strengths and weaknesses, and situate this costing and budgeting tool within the context of other evaluation resources available through WHO-funded or associated tools.The tool purports to allow for users to cost technical activities for the AMR NAPs. This tool is joining a suite of other relevant tools and data available from the WHO.5 The technical specifications of the model are developed in Microsoft Excel (in 2010 or later versions), and the tool guides users through the process of inputting cost and financing components, and inflation and currency assumptions, in order to combine and compare cost and budgeting estimates over a 1–5 year period. The backend has more complex functions developed in Visual Basic for Application (VBA). Currently the tool is in English, but with plans to expand to French and Spanish.3According to the WHO, the AMR-NAP tool can be used to ‘generate detailed costs for the technical activities included in AMR NAPs. The tool can be used to cost priority activities that still need to be funded.’JAC-AMR Online). Of note, the ‘building blocks’ for the cost matrices for each activity include ‘meetings’, ‘consultant’, ‘field visit’, ‘HR’, ‘procurement’ and ‘other’. These categories reflect the narrow, activity-based lens of this costing tool. However, potentially incorporating the costs and funding of policies across other health programmes (such as vaccine programmes) is said to be possible.3 Different ministries and/or departments can work on individual worksheets to allow for the continuation of siloed, status-quo working, with easier subsequent consolidation on a combined dashboard through the ‘module consolidator’ Excel component.3 Although, practically, this tool is sensitive to small deviations from the manual , the authors advise intended users to save versions pre- and post- setting up the cost matrices, as otherwise users may have to fill in from scratch to accommodate any changes made to the NAP inputs at a later date.Practically, users need to source and calculate unit costs separately  within a country. This may lead to misalignment in costing and funding estimates across local regions in practice, since the tool asks for point estimation of inputs, without the opportunity to input ranges. Scaling up and decentralized funding concerns across ‘subnations’ are highlighted as potential issues with using the tool.Additionally, although the tool’s frontend (the user interface) is fit for purpose for the intended end users (policymakers and advisors), it would be helpful for follow-on tools to have clearer backend documentation and navigation , to allow for other developers to repurpose tools where necessary. This will also help to reduce research waste.before the costing is done. This is important; practically, it is challenging to make the case for prioritization within a government department’s lump sum budget without having an understanding of the cost and how it links to impact. Moreover, although AMR NAPs may be 5 year pre-set commitments, the stated aim of this tool is to help with the policy prioritization and implementation process; the policy decisions of what to prioritize in a particular budget cycle are negotiations and ‘wish lists’, and often iterative processes, so if the tool were to allow for easier comparison across scenarios (and taking into consideration wider impact) that might make it more useful in the process of AMR ‘winning’ policy and budgetary space within the pre-prioritization dialogue.A broader critique is that the tool specifies that the end user needs to select the order of policy priorities 6 The risk of using such a framework is that the costs and benefits that are not captured may not be advocated for within government, even if these may provide longer-term benefits; rhetoric and attention can be governed by—and govern—the policies that are taken on board8 However, focused cost inputs and outputs used in—or produced by—the tool could subsequently feed into economic evaluations of intervention impact, so could provide a wider use in costing impact.9Technically, the cost matrices are centred around set specific human and capital resources (like laboratory technicians or equipment), but AMR is complex, and the biggest gains in AMR will likely require transformational change at the structural level. This includes water management or health systems strengthening, which are known to be immensely challenging to cost in such a way.10–13This tool exists within a toolbox of other options available to policymakers, including those in Figure 13 These are needed for flagging priority areas, and in epidemiology and economic models of policy impact. The NAP resources available (including the AMR-NAP tool) provide supporting material for constructing NAPs and calculating the potential costs of policy implementation.10 Other WHO tools such as the One Health tool, which has epidemiology (Spectrum) and economic  modules, provide an overview of the impacts of different scenarios  can provide estimates of AMR and antimicrobial use.The AMR-NAP tool provides a useful framework for costing and budgeting. However, its use for post-prioritization and point-estimation means the tool should be considered and used within the wider suite of resources available. AMR is a complex, system-wide problem, and understanding the limitations of such costing tools is important. Whilst it is understandable to focus on what is measurable, policymakers need to be aware that structural, effective interventions may not fall within this remit, and ensure that important considerations do not fall off the policy table simply because they are currently difficult to cost.3 There may ultimately be a problem of too many tools. Although the WHO does provide a tools directory on their website,4 it would be useful to highlight when to use which tool across the AMR policy process.Fundamentally, when supranational health bodies endeavour to intervene in national government policy development, they should endeavour to create tools that are user friendly, work across multiple interfaces, and truly support countries to adopt the policies and programmes that are right for them. We should consider moving toward open-access and transparent model code and data, which would increase costing and evaluation capacity, and data linkage opportunities, decreasing cost for future tweaks/build-ons to suit need. Although the current tool is compatible with input/output ‘copy and pasting’ with other WHO impact assessment tools, the latter may use different proprietary software, and issues of compatibility with standard in-house budgeting software are already seen with the Microsoft Excel-based tool available.Overall, this WHO AMR costing and budgeting tool accomplishes its stated aims. This tool should facilitate early-stage AMR NAP efforts for countries that have struggled to make headway in NAP implementation, but is limited in scope for the definition of ‘cost’. By combining this tool with others available, whilst expanding disease-scope of current health and economic impact tools available, national-level capacity in developing, implementing and evaluating AMR NAPs may be maximized.dlad064_Supplementary_DataClick here for additional data file.