Patients undergoing immune effector cell therapy (IECT) are at high risk for infections. We assessed seropositivity against pneumococcus, tetanus, and diphtheria in patients before and after IECT and the patients’ response to vaccination. We enrolled patients who underwent IECT from January 2020 to March 2022. Antibody levels for diphtheria, tetanus, and pneumococcus were measured before IECT, at 1 month, and 3–6 months after. Eligible patients were vaccinated after IECT. In non-seroprotected patients, we discontinued testing. Before IECT, most patients had seroprotective antibody levels against tetanus (68/69, 99%) and diphtheria (65/69, 94%), but fewer did against pneumococcus (24/67, 36%). After IECT, all patients had seroprotective antibody levels for tetanus at 1 month (68/68) and 3–6 months (56/56). For diphtheria, 65/65 patients (100%) had seroprotective antibody levels at 1 month, and 48/53 (91%) did at 3–6 months. For pneumococcus, seroprotective antibody levels were identified in 91% (21/23) of patients at 1 month and 79% (15/19) at 3–6 months following IECT. Fifteen patients received a pneumococcal vaccine after IECT, but none achieved seroprotective response. One patient received the tetanus-diphtheria vaccine and had a seroprotective antibody response. Because some patients experience loss of immunity after IECT, studies evaluating vaccination strategies post-IECT are needed.

- Importance: Many COVID-19 prognostic factors for disease severity have been identified and many scores have already been proposed to predict death and other outcomes. However, hospitals in developing countries often cannot measure some of the variables that have been reported as useful. - Objective: To assess the sensitivity, specificity, and predictive values of the novel LOW-HARM score ( L ymphopenia, O xygen saturation, W hite blood cells, H ypertension, A ge, R enal injury, and M yocardial injury). - Design: The score was designed using data from already published cohorts of patients diagnosed with COVID-19. Afterwards, it was calculated it in 438 consecutive hospital admissions at twelve different institutions in ten different cities in Mexico. - Setting: Twelve hospitals in ten different cities in Mexico. - Participants: Data from 438 patients was collected. Data from 400 patients (200 deaths and 200 survivors) was included in the analysis. - Exposure: All patients had an infection with SARS-CoV-2 confirmed by PCR. - Main Outcome: The sensitivity, specificity, and predictive values of different cut-offs of the LOW-HARM score to predict death. - Results: Mean scores at admission and their distributions were significantly lower in patients who were discharged compared to those who died during their hospitalization 10 (SD: 17) vs 70 (SD: 28). The overall AUC of the model was 95%. A cut-off > 65 points had a specificity of 98% and a positive predictive value of 96%. More than a third of the cases (36%) in the sample had a LOW-HARM score > 65 points. - Conclusions and relevance: The LOW-HARM score measured at admission is highly specific and useful for predicting mortality. It is easy to calculate and can be updated with individual clinical progression. KEY POINTS: Question: Is it possible to predict mortality in patients diagnosed with COVID-19 using easy-to-access and easy-to-measure variables? Findings: The LOW-HARM score ( L ymphopenia, O xygen saturation, W hite blood cells, H ypertension, A ge, R enal injury, and M yocardial injury) is a one-hundred-point score that, when measured at admission, had an overall AUC of 95% for predicting mortality. A cut-off of ≥ 65 points had a specificity of 98% and a positive predictive value of 96%. Meaning: The LOW-HARM score measured at admission is highly specific and useful for predicting mortality in patients diagnosed with COVID-19. In our sample, more than a third of patients met the proposed cut-off.